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9.8. Import Metadata From Text File	9.8. Import Metadata From Text File 9.8.1. Import Metadata From Text File The Teiid Designer provides various import options for parsing comma delimited text file metadata into models. This is accomplished via the Import > Teiid Designer > Designer Text File >> Source or View Models option. In Teiid Designer , Click File > Import... action Select the import option Teiid Designer > Designer Text File >> Source or View Models and click > . Select an import type from the drop-down menu shown below. Figure 9.29. Import Wizard These steps are required for each type are defined below: Relation Model Text Import Relational Table Text Import Virtual Table Text Import 9.8.2. Import Relational Model (XML Format) To create relational tables from imported XML text file metadata, perform steps 1 to 3 from the Import Metadata from Text File section and then perform following steps: Select the Relational Model (XML Format) import type, then click > . Figure 9.30. Select Import Type - Relational Model (XML Format) On the page, select the XML file on your local file system via the Browse... button. Select a target model to which the imported relational objects will be added via the second Browse... button. The dialog allows selecting an existing relational model or creating a new model. Note the contents of your selected XML file will be display in the File Contents viewer. Click Finish . Figure 9.31. Select Source Text File and Target Relational Model Page If the target model contains named children (tables, views, procedures) that conflict with the objects being imported, a dialog will be displayed giving you options on how to proceed including: replacing specific existing objects, creating new same named objects or cancel import entirely. Figure 9.32. Duplicate Objects Dialog 9.8.3. Import Relational Tables (CSV Format) To create relational tables from imported text file metadata, perform steps 1 to 3 from the Import Metadata from Text File section and then perform following steps: Select the Relational Tables (CSV Format) import type, then click > . Figure 9.33. Select Import Type - Relational Tables (CSV Format) In the page, you'll need to provide a source text file containing the metadata formatted to the specifications on the page. Figure 9.34. Select Source Text File and Target Relational Model Select an existing relational model as the target location for your new relational components using the Browse... button to open the Relational Model Selector dialog. Select a relational model from your workspace or specify a unique name to create a new model. Select any additional options and click Finish . 9.8.4. Import Relational View Tables (CSV Format) To create relational virtual tables from imported text file metadata, perform steps 1 to 3 from the Import Metadata from Text File section and then perform following steps: Select the Relational Virtual Tables (CSV Format) import type, then click > . Figure 9.35. Select Import Type - Relational Virtual Tables (CSV Format) In the page, you'll need to provide a source text file containing the metadata formatted to the specifications on the page. Figure 9.36. Select Source Text File and Target Virtual Relational Model Select an existing relational virtual model as the target location for your new model components using the Browse... button to open the Virtual Model Selector dialog. Select a virtual relational model from your workspace or specify a unique name to create a new model. Click Finish .	null	https://docs.redhat.com/en/documentation/red_hat_jboss_data_virtualization/6.4/html/user_guide_volume_1_teiid_designer/sect-import_metadata_from_text_file
Chapter 4. Updating Red Hat OpenShift Data Foundation 4.15.x to 4.15.y	Chapter 4. Updating Red Hat OpenShift Data Foundation 4.15.x to 4.15.y This chapter helps you to upgrade between the z-stream release for all Red Hat OpenShift Data Foundation deployments (Internal, Internal-Attached and External). The upgrade process remains the same for all deployments. The Only difference is what gets upgraded and what's not. For Internal and Internal-attached deployments, upgrading OpenShift Data Foundation upgrades all OpenShift Data Foundation services including the backend Red Hat Ceph Storage (RHCS) cluster. For External mode deployments, upgrading OpenShift Data Foundation only upgrades the OpenShift Data Foundation service while the backend Ceph storage cluster remains untouched and needs to be upgraded separately. Hence, we recommend upgrading RHCS along with OpenShift Data Foundation in order to get new feature support, security fixes, and other bug fixes. Since we do not have a strong dependency on RHCS upgrade, you can upgrade the OpenShift Data Foundation operator first followed by RHCS upgrade or vice-versa. See solution to know more about RHCS releases. When a new z-stream release becomes available, the upgrade process triggers automatically if the update strategy was set to Automatic . If the update strategy is set to Manual then use the following procedure. Prerequisites Ensure that the OpenShift Container Platform cluster has been updated to the latest stable release of version 4.15.X, see Updating Clusters . Ensure that the OpenShift Data Foundation cluster is healthy and data is resilient. Navigate to Storage Data Foundation Storage Systems tab and then click on the storage system name. Check for the green tick on the status card of Overview - Block and File and Object tabs. Green tick indicates that the storage cluster, object service and data resiliency is healthy. Ensure that all OpenShift Data Foundation Pods, including the operator pods, are in Running state in the openshift-storage namespace. To view the state of the pods, on the OpenShift Web Console, click Workloads Pods . Select openshift-storage from the Project drop-down list. Note If the Show default projects option is disabled, use the toggle button to list all the default projects. Ensure that you have sufficient time to complete the OpenShift Data Foundation update process, as the update time varies depending on the number of OSDs that run in the cluster. Procedure On the OpenShift Web Console, navigate to Operators Installed Operators . Select openshift-storage project. Note If the Show default projects option is disabled, use the toggle button to list all the default projects. Click the OpenShift Data Foundation operator name. Click the Subscription tab. If the Upgrade Status shows require approval , click on requires approval link. On the InstallPlan Details page, click Preview Install Plan . Review the install plan and click Approve . Wait for the Status to change from Unknown to Created . After the operator is successfully upgraded, a pop-up with a message, Web console update is available appears on the user interface. Click Refresh web console from this pop-up for the console changes to reflect. Verification steps Check the Version below the OpenShift Data Foundation name and check the operator status. Navigate to Operators Installed Operators and select the openshift-storage project. When the upgrade completes, the version updates to a new version number for OpenShift Data Foundation and status changes to Succeeded with a green tick. Verify that the OpenShift Data Foundation cluster is healthy and data is resilient. Navigate to Storage Data Foundation Storage Systems tab and then click on the storage system name. Check for the green tick on the status card of Overview - Block and File and Object tabs. Green tick indicates that the storage cluster, object service and data resiliency is healthy If verification steps fail, contact Red Hat Support .	null	https://docs.redhat.com/en/documentation/red_hat_openshift_data_foundation/4.15/html/updating_openshift_data_foundation/updating-zstream-odf_rhodf
Providing feedback on Red Hat documentation	Providing feedback on Red Hat documentation If you have a suggestion to improve this documentation, or find an error, you can contact technical support at https://access.redhat.com to open a request.	null	https://docs.redhat.com/en/documentation/red_hat_ansible_automation_platform/2.4/html/deploying_the_red_hat_ansible_automation_platform_operator_on_openshift_container_platform/providing-feedback
3.6. Suspending an XFS File System	3.6. Suspending an XFS File System To suspend or resume write activity to a file system, use the following command: Suspending write activity allows hardware-based device snapshots to be used to capture the file system in a consistent state. Note The xfs_freeze utility is provided by the xfsprogs package, which is only available on x86_64. To suspend (that is, freeze) an XFS file system, use: To unfreeze an XFS file system, use: When taking an LVM snapshot, it is not necessary to use xfs_freeze to suspend the file system first. Rather, the LVM management tools will automatically suspend the XFS file system before taking the snapshot. For more information about freezing and unfreezing an XFS file system, see man xfs_freeze .	[ "xfs_freeze mount-point", "xfs_freeze -f /mount/point", "xfs_freeze -u /mount/point" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/storage_administration_guide/xfsfreeze
Preface	Preface This feature is available in this release as a Technology Preview , and therefore is not fully supported by Red Hat. It should only be used for testing, and should not be deployed in a production environment. For more information about Technology Preview features, see Scope of Coverage Details .	null	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/16.0/html/quick_start_guide/pr01
Chapter 2. Important Changes to External Kernel Parameters	Chapter 2. Important Changes to External Kernel Parameters This chapter provides system administrators with a summary of significant changes in the kernel shipped with Red Hat Enterprise Linux 6.8. These changes include added or updated proc entries, sysctl , and sysfs default values, boot parameters, kernel configuration options, or any noticeable behavior changes. force_hrtimer_reprogram [KNL] Force the reprogramming of expired timers in the hrtimer_reprogram() function. softirq_2ms_loop [KNL] Set softirq handling to 2 ms maximum. The default time is the existing Red Hat Enterprise Linux 6 behaviour. tpm_suspend_pcr=[HW,TPM] Specify that, at suspend time, the tpm driver should extend the specified principal components regression ( PCR ) with zeros as a workaround for some chips which fail to flush the last written PCR on a TPM_SaveState operation. This guarantees that all the other PCR s are saved. Format: integer pcr id /proc/fs/fscache/stats Table 2.1. class Ops: new: ini=N Number of async ops initialised changed: rel=N will be equal to ini=N when idle Table 2.2. new class CacheEv nsp=N Number of object lookups or creations rejected due to a lack of space stl=N Number of stale objects deleted rtr=N Number of objects retired when relinquished cul=N Number of objects culled /proc/sys/net/core/default_qdisc The default queuing discipline to use for network devices. This allows overriding the default queue discipline of pfifo_fast with an alternative. Since the default queuing discipline is created with no additional parameters, it is best suited to queuing disciplines that work well without configuration, for example, a stochastic fair queue ( sfq ). Do not use queuing disciplines like Hierarchical Token Bucket or Deficit Round Robin, which require setting up classes and bandwidths. Default: pfifo_fast /sys/kernel/mm/ksm/max_page_sharing Maximum sharing allowed for each KSM page. This enforces a deduplication limit to avoid the virtual memory rmap lists to grow too large. The minimum value is 2 as a newly created KSM page will have at least two sharers. The rmap walk has O(N) complexity where N is the number of rmap_items , that is virtual mappings that are sharing the page, which is in turn capped by max_page_sharing . So this effectively spreads the linear O(N) computational complexity from rmap walk context over different KSM pages. The ksmd walk over the stable_node chains is also O(N), but N is the number of stable_node dups , not the number of rmap_items , so it has not a significant impact on ksmd performance. In practice the best stable_node dups candidate is kept and found at the head of the dups list. The higher this value the faster KSM merges the memory, because there will be fewer stable_node dups queued into the stable_node chain->hlist to check for pruning. And the higher the deduplication factor is, but the slowest the worst case rmap walk could be for any given KSM page. Slowing down the rmap walk means there will be higher latency for certain virtual memory operations happening during swapping, compaction, NUMA balancing, and page migration, in turn decreasing responsiveness for the caller of those virtual memory operations. The scheduler latency of other tasks not involved with the VM operations doing the rmap walk is not affected by this parameter as the rmap walks are always scheduled friendly themselves. /proc/sys/net/core/default_qdisc The default queuing discipline to use for network devices. This allows overriding the default queue discipline of pfifo_fast with an alternative. Since the default queuing discipline is created with no additional parameters so is best suited to queuing disciplines that work well without configuration, for example, a stochastic fair queue ( sfq ). Do not use queuing disciplines like Hierarchical Token Bucket or Deficit Round Robin which require setting up classes and bandwidths. Default: pfifo_fast /sys/kernel/mm/ksm/stable_node_chains_prune_millisecs How frequently to walk the whole list of stable_node "dups" linked in the stable_node chains in order to prune stale stable_node . Smaller milllisecs values will free up the KSM metadata with lower latency, but they will make ksmd use more CPU during the scan. This only applies to the stable_node chains so it is a noop unless a single KSM page hits max_page_sharing . In such a case there are no stable_node chains. /sys/kernel/mm/ksm/stable_node_chains Number of stable node chains allocated. this is effectively the number of KSM pages that hit the max_page_sharing limit. /sys/kernel/mm/ksm/stable_node_dups Number of stable node dups queued into the stable_node chains.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.8_technical_notes/chap-red_hat_enterprise_linux-6.8_technical_notes-kernel_parameters_changes
Chapter 11. Messaging Endpoints	Chapter 11. Messaging Endpoints Abstract The messaging endpoint patterns describe various features and qualities of service that can be configured on an endpoint. 11.1. Messaging Mapper Overview The messaging mapper pattern describes how to map domain objects to and from a canonical message format, where the message format is chosen to be as platform neutral as possible. The chosen message format should be suitable for transmission through a Section 6.5, "Message Bus" , where the message bus is the backbone for integrating a variety of different systems, some of which might not be object-oriented. Many different approaches are possible, but not all of them fulfill the requirements of a messaging mapper. For example, an obvious way to transmit an object is to use object serialization , which enables you to write an object to a data stream using an unambiguous encoding (supported natively in Java). However, this is not a suitable approach to use for the messaging mapper pattern because the serialization format is understood only by Java applications. Java object serialization creates an impedance mismatch between the original application and the other applications in the messaging system. The requirements for a messaging mapper can be summarized as follows: The canonical message format used to transmit domain objects should be suitable for consumption by non-object oriented applications. The mapper code should be implemented separately from both the domain object code and the messaging infrastructure. Apache Camel helps fulfill this requirement by providing hooks that can be used to insert mapper code into a route. The mapper might need to find an effective way of dealing with certain object-oriented concepts such as inheritance, object references, and object trees. The complexity of these issues varies from application to application, but the aim of the mapper implementation must always be to create messages that can be processed effectively by non-object-oriented applications. Finding objects to map You can use one of the following mechanisms to find the objects to map: Find a registered bean. - For singleton objects and small numbers of objects, you could use the CamelContext registry to store references to beans. For example, if a bean instance is instantiated using Spring XML, it is automatically entered into the registry, where the bean is identified by the value of its id attribute. Select objects using the JoSQL language. - If all of the objects you want to access are already instantiated at runtime, you could use the JoSQL language to locate a specific object (or objects). For example, if you have a class, org.apache.camel.builder.sql.Person , with a name bean property and the incoming message has a UserName header, you could select the object whose name property equals the value of the UserName header using the following code: Where the syntax, : HeaderName , is used to substitute the value of a header in a JoSQL expression. Dynamic - For a more scalable solution, it might be necessary to read object data from a database. In some cases, the existing object-oriented application might already provide a finder object that can load objects from the database. In other cases, you might have to write some custom code to extract objects from a database, and in these cases the JDBC component and the SQL component might be useful. 11.2. Event Driven Consumer Overview The event-driven consumer pattern, shown in Figure 11.1, "Event Driven Consumer Pattern" , is a pattern for implementing the consumer endpoint in a Apache Camel component, and is only relevant to programmers who need to develop a custom component in Apache Camel. Existing components already have a consumer implementation pattern hard-wired into them. Figure 11.1. Event Driven Consumer Pattern Consumers that conform to this pattern provide an event method that is automatically called by the messaging channel or transport layer whenever an incoming message is received. One of the characteristics of the event-driven consumer pattern is that the consumer endpoint itself does not provide any threads to process the incoming messages. Instead, the underlying transport or messaging channel implicitly provides a processor thread when it invokes the exposed event method (which blocks for the duration of the message processing). For more details about this implementation pattern, see Section 38.1.3, "Consumer Patterns and Threading" and Chapter 41, Consumer Interface . 11.3. Polling Consumer Overview The polling consumer pattern, shown in Figure 11.2, "Polling Consumer Pattern" , is a pattern for implementing the consumer endpoint in a Apache Camel component, so it is only relevant to programmers who need to develop a custom component in Apache Camel. Existing components already have a consumer implementation pattern hard-wired into them. Consumers that conform to this pattern expose polling methods, receive() , receive(long timeout) , and receiveNoWait() that return a new exchange object, if one is available from the monitored resource. A polling consumer implementation must provide its own thread pool to perform the polling. For more details about this implementation pattern, see Section 38.1.3, "Consumer Patterns and Threading" , Chapter 41, Consumer Interface , and Section 37.3, "Using the Consumer Template" . Figure 11.2. Polling Consumer Pattern Scheduled poll consumer Many of the Apache Camel consumer endpoints employ a scheduled poll pattern to receive messages at the start of a route. That is, the endpoint appears to implement an event-driven consumer interface, but internally a scheduled poll is used to monitor a resource that provides the incoming messages for the endpoint. See Section 41.2, "Implementing the Consumer Interface" for details of how to implement this pattern. Quartz component You can use the quartz component to provide scheduled delivery of messages using the Quartz enterprise scheduler. See Quartz in the Apache Camel Component Reference Guide and Quartz Component for details. 11.4. Competing Consumers Overview The competing consumers pattern, shown in Figure 11.3, "Competing Consumers Pattern" , enables multiple consumers to pull messages from the same queue, with the guarantee that each message is consumed once only . This pattern can be used to replace serial message processing with concurrent message processing (bringing a corresponding reduction in response latency). Figure 11.3. Competing Consumers Pattern The following components demonstrate the competing consumers pattern: JMS based competing consumers SEDA based competing consumers JMS based competing consumers A regular JMS queue implicitly guarantees that each message can only be consumed at once. Hence, a JMS queue automatically supports the competing consumers pattern. For example, you could define three competing consumers that pull messages from the JMS queue, HighVolumeQ , as follows: Where the CXF (Web services) endpoints, replica01 , replica02 , and replica03 , process messages from the HighVolumeQ queue in parallel. Alternatively, you can set the JMS query option, concurrentConsumers , to create a thread pool of competing consumers. For example, the following route creates a pool of three competing threads that pick messages from the specified queue: And the concurrentConsumers option can also be specified in XML DSL, as follows: Note JMS topics cannot support the competing consumers pattern. By definition, a JMS topic is intended to send multiple copies of the same message to different consumers. Therefore, it is not compatible with the competing consumers pattern. SEDA based competing consumers The purpose of the SEDA component is to simplify concurrent processing by breaking the computation into stages. A SEDA endpoint essentially encapsulates an in-memory blocking queue (implemented by java.util.concurrent.BlockingQueue ). Therefore, you can use a SEDA endpoint to break a route into stages, where each stage might use multiple threads. For example, you can define a SEDA route consisting of two stages, as follows: Where the first stage contains a single thread that consumes message from a file endpoint, file://var/messages , and routes them to a SEDA endpoint, seda:fanout . The second stage contains three threads: a thread that routes exchanges to cxf:bean:replica01 , a thread that routes exchanges to cxf:bean:replica02 , and a thread that routes exchanges to cxf:bean:replica03 . These three threads compete to take exchange instances from the SEDA endpoint, which is implemented using a blocking queue. Because the blocking queue uses locking to prevent more than one thread from accessing the queue at a time, you are guaranteed that each exchange instance can only be consumed once. For a discussion of the differences between a SEDA endpoint and a thread pool created by thread() , see SEDA component in the Apache Camel Component Reference Guide . 11.5. Message Dispatcher Overview The message dispatcher pattern, shown in Figure 11.4, "Message Dispatcher Pattern" , is used to consume messages from a channel and then distribute them locally to performers , which are responsible for processing the messages. In a Apache Camel application, performers are usually represented by in-process endpoints, which are used to transfer messages to another section of the route. Figure 11.4. Message Dispatcher Pattern You can implement the message dispatcher pattern in Apache Camel using one of the following approaches: JMS selectors JMS selectors in ActiveMQ Content-based router JMS selectors If your application consumes messages from a JMS queue, you can implement the message dispatcher pattern using JMS selectors . A JMS selector is a predicate expression involving JMS headers and JMS properties. If the selector evaluates to true , the JMS message is allowed to reach the consumer, and if the selector evaluates to false , the JMS message is blocked. In many respects, a JMS selector is like a Section 8.2, "Message Filter" , but it has the additional advantage that the filtering is implemented inside the JMS provider. This means that a JMS selector can block messages before they are transmitted to the Apache Camel application. This provides a significant efficiency advantage. In Apache Camel, you can define a JMS selector on a consumer endpoint by setting the selector query option on a JMS endpoint URI. For example: Where the predicates that appear in a selector string are based on a subset of the SQL92 conditional expression syntax (for full details, see the JMS specification ). The identifiers appearing in a selector string can refer either to JMS headers or to JMS properties. For example, in the preceding routes, the sender sets a JMS property called CountryCode . If you want to add a JMS property to a message from within your Apache Camel application, you can do so by setting a message header (either on In message or on Out messages). When reading or writing to JMS endpoints, Apache Camel maps JMS headers and JMS properties to, and from, its native message headers. Technically, the selector strings must be URL encoded according to the application/x-www-form-urlencoded MIME format (see the HTML specification ). In practice, the & (ampersand) character might cause difficulties because it is used to delimit each query option in the URI. For more complex selector strings that might need to embed the & character, you can encode the strings using the java.net.URLEncoder utility class. For example: Where the UTF-8 encoding must be used. JMS selectors in ActiveMQ You can also define JMS selectors on ActiveMQ endpoints. For example: For more details, see ActiveMQ: JMS Selectors and ActiveMQ Message Properties . Content-based router The essential difference between the content-based router pattern and the message dispatcher pattern is that a content-based router dispatches messages to physically separate destinations (remote endpoints), and a message dispatcher dispatches messages locally, within the same process space. In Apache Camel, the distinction between these two patterns is determined by the target endpoint. The same router logic is used to implement both a content-based router and a message dispatcher. When the target endpoint is remote, the route defines a content-based router. When the target endpoint is in-process, the route defines a message dispatcher. For details and examples of how to use the content-based router pattern see Section 8.1, "Content-Based Router" . 11.6. Selective Consumer Overview The selective consumer pattern, shown in Figure 11.5, "Selective Consumer Pattern" , describes a consumer that applies a filter to incoming messages, so that only messages meeting specific selection criteria are processed. Figure 11.5. Selective Consumer Pattern You can implement the selective consumer pattern in Apache Camel using one of the following approaches: JMS selector JMS selector in ActiveMQ Message filter JMS selector A JMS selector is a predicate expression involving JMS headers and JMS properties. If the selector evaluates to true , the JMS message is allowed to reach the consumer, and if the selector evaluates to false , the JMS message is blocked. For example, to consume messages from the queue, selective , and select only those messages whose country code property is equal to US , you can use the following Java DSL route: Where the selector string, CountryCode='US' , must be URL encoded (using UTF-8 characters) to avoid trouble with parsing the query options. This example presumes that the JMS property, CountryCode , is set by the sender. For more details about JMS selectors, see the section called "JMS selectors" . Note If a selector is applied to a JMS queue, messages that are not selected remain on the queue and are potentially available to other consumers attached to the same queue. JMS selector in ActiveMQ You can also define JMS selectors on ActiveMQ endpoints. For example: For more details, see ActiveMQ: JMS Selectors and ActiveMQ Message Properties . Message filter If it is not possible to set a selector on the consumer endpoint, you can insert a filter processor into your route instead. For example, you can define a selective consumer that processes only messages with a US country code using Java DSL, as follows: The same route can be defined using XML configuration, as follows: For more information about the Apache Camel filter processor, see Section 8.2, "Message Filter" . Warning Be careful about using a message filter to select messages from a JMS queue . When using a filter processor, blocked messages are simply discarded. Hence, if the messages are consumed from a queue (which allows each message to be consumed only once - see Section 11.4, "Competing Consumers" ), then blocked messages are not processed at all. This might not be the behavior you want. 11.7. Durable Subscriber Overview A durable subscriber , as shown in Figure 11.6, "Durable Subscriber Pattern" , is a consumer that wants to receive all of the messages sent over a particular Section 6.2, "Publish-Subscribe Channel" channel, including messages sent while the consumer is disconnected from the messaging system. This requires the messaging system to store messages for later replay to the disconnected consumer. There also has to be a mechanism for a consumer to indicate that it wants to establish a durable subscription. Generally, a publish-subscribe channel (or topic) can have both durable and non-durable subscribers, which behave as follows: non-durable subscriber - Can have two states: connected and disconnected . While a non-durable subscriber is connected to a topic, it receives all of the topic's messages in real time. However, a non-durable subscriber never receives messages sent to the topic while the subscriber is disconnected. durable subscriber - Can have two states: connected and inactive . The inactive state means that the durable subscriber is disconnected from the topic, but wants to receive the messages that arrive in the interim. When the durable subscriber reconnects to the topic, it receives a replay of all the messages sent while it was inactive. Figure 11.6. Durable Subscriber Pattern JMS durable subscriber The JMS component implements the durable subscriber pattern. In order to set up a durable subscription on a JMS endpoint, you must specify a client ID , which identifies this particular connection, and a durable subscription name , which identifies the durable subscriber. For example, the following route sets up a durable subscription to the JMS topic, news , with a client ID of conn01 and a durable subscription name of John.Doe : You can also set up a durable subscription using the ActiveMQ endpoint: If you want to process the incoming messages concurrently, you can use a SEDA endpoint to fan out the route into multiple, parallel segments, as follows: Where each message is processed only once, because the SEDA component supports the competing consumers pattern. Alternative example Another alternative is to combine the Section 11.5, "Message Dispatcher" or Section 8.1, "Content-Based Router" with File or JPA components for durable subscribers then something like SEDA for non-durable. Here is a simple example of creating durable subscribers to a JMS topic Using the Fluent Builders Using the Spring XML Extensions Here is another example of JMS durable subscribers, but this time using virtual topics (recommended by AMQ over durable subscriptions) Using the Fluent Builders Using the Spring XML Extensions 11.8. Idempotent Consumer Overview The idempotent consumer pattern is used to filter out duplicate messages. For example, consider a scenario where the connection between a messaging system and a consumer endpoint is abruptly lost due to some fault in the system. If the messaging system was in the middle of transmitting a message, it might be unclear whether or not the consumer received the last message. To improve delivery reliability, the messaging system might decide to redeliver such messages as soon as the connection is re-established. Unfortunately, this entails the risk that the consumer might receive duplicate messages and, in some cases, the effect of duplicating a message may have undesirable consequences (such as debiting a sum of money twice from your account). In this scenario, an idempotent consumer could be used to weed out undesired duplicates from the message stream. Camel provides the following Idempotent Consumer implementations: MemoryIdempotentRepository KafkaIdempotentRepository File Hazelcast SQL JPA Idempotent consumer with in-memory cache In Apache Camel, the idempotent consumer pattern is implemented by the idempotentConsumer() processor, which takes two arguments: messageIdExpression - An expression that returns a message ID string for the current message. messageIdRepository - A reference to a message ID repository, which stores the IDs of all the messages received. As each message comes in, the idempotent consumer processor looks up the current message ID in the repository to see if this message has been seen before. If yes, the message is discarded; if no, the message is allowed to pass and its ID is added to the repository. The code shown in Example 11.1, "Filtering Duplicate Messages with an In-memory Cache" uses the TransactionID header to filter out duplicates. Example 11.1. Filtering Duplicate Messages with an In-memory Cache Where the call to memoryMessageIdRepository(200) creates an in-memory cache that can hold up to 200 message IDs. You can also define an idempotent consumer using XML configuration. For example, you can define the preceding route in XML, as follows: Note From Camel 2.17, Idempotent Repository supports optional serialized headers. Idempotent consumer with JPA repository The in-memory cache suffers from the disadvantages of easily running out of memory and not working in a clustered environment. To overcome these disadvantages, you can use a Java Persistent API (JPA) based repository instead. The JPA message ID repository uses an object-oriented database to store the message IDs. For example, you can define a route that uses a JPA repository for the idempotent consumer, as follows: The JPA message ID repository is initialized with two arguments: JpaTemplate instance - Provides the handle for the JPA database. processor name - Identifies the current idempotent consumer processor. The SpringRouteBuilder.bean() method is a shortcut that references a bean defined in the Spring XML file. The JpaTemplate bean provides a handle to the underlying JPA database. See the JPA documentation for details of how to configure this bean. For more details about setting up a JPA repository, see JPA Component documentation, the Spring JPA documentation, and the sample code in the Camel JPA unit test . Spring XML example The following example uses the myMessageId header to filter out duplicates: Idempotent consumer with JDBC repository A JDBC repository is also supported for storing message IDs in the idempotent consumer pattern. The implementation of the JDBC repository is provided by the SQL component, so if you are using the Maven build system, add a dependency on the camel-sql artifact. You can use the SingleConnectionDataSource JDBC wrapper class from the Spring persistence API in order to instantiate the connection to a SQL database. For example, to instantiate a JDBC connection to a HyperSQL database instance, you could define the following JDBC data source: Note The preceding JDBC data source uses the HyperSQL mem protocol, which creates a memory-only database instance. This is a toy implementation of the HyperSQL database which is not actually persistent. Using the preceding data source, you can define an idempotent consumer pattern that uses the JDBC message ID repository, as follows: How to handle duplicate messages in the route Available as of Camel 2.8 You can now set the skipDuplicate option to false which instructs the idempotent consumer to route duplicate messages as well. However the duplicate message has been marked as duplicate by having a property on the the section called "Exchanges" set to true. We can leverage this fact by using a Section 8.1, "Content-Based Router" or Section 8.2, "Message Filter" to detect this and handle duplicate messages. For example in the following example we use the Section 8.2, "Message Filter" to send the message to a duplicate endpoint, and then stop continue routing that message. The sample example in XML DSL would be: How to handle duplicate message in a clustered environment with a data grid If you have running Camel in a clustered environment, a in memory idempotent repository doesn't work (see above). You can setup either a central database or use the idempotent consumer implementation based on the Hazelcast data grid. Hazelcast finds the nodes over multicast (which is default - configure Hazelcast for tcp-ip) and creates automatically a map based repository: You have to define how long the repository should hold each message id (default is to delete it never). To avoid that you run out of memory you should create an eviction strategy based on the Hazelcast configuration . For additional information see Hazelcast . See this link:http://camel.apache.org/hazelcast-idempotent-repository-tutorial.html[Idempotent Repository tutorial] to learn more about how to setup such an idempotent repository on two cluster nodes using Apache Karaf. Options The Idempotent Consumer has the following options: Option Default Description eager true Camel 2.0: Eager controls whether Camel adds the message to the repository before or after the exchange has been processed. If enabled before then Camel will be able to detect duplicate messages even when messages are currently in progress. By disabling Camel will only detect duplicates when a message has successfully been processed. messageIdRepositoryRef null A reference to a IdempotentRepository to lookup in the registry. This option is mandatory when using XML DSL. skipDuplicate true Camel 2.8: Sets whether to skip duplicate messages. If set to false then the message will be continued. However the the section called "Exchanges" has been marked as a duplicate by having the Exchange.DUPLICATE_MESSAG exchange property set to a Boolean.TRUE value. completionEager false Camel 2.16: Sets whether to complete the Idempotent consumer eager, when the exchange is done. If you set the completeEager option true, then the Idempotent Consumer triggers its completion when the exchange reaches till the end of the idempotent consumer pattern block. However, if the exchange continues to route even after the end block, then it does not affect the state of the idempotent consumer. If you set the completeEager option false, then the Idempotent Consumer triggers its completion after the exchange is done and is being routed. However, if the exchange continues to route even after the block ends, then it also affects the state of the idempotent consumer. For example, due to an exception if the exchange fails, then the state of the idempotent consumer will be a rollback. 11.9. Transactional Client Overview The transactional client pattern, shown in Figure 11.7, "Transactional Client Pattern" , refers to messaging endpoints that can participate in a transaction. Apache Camel supports transactions using Spring transaction management . Figure 11.7. Transactional Client Pattern Transaction oriented endpoints Not all Apache Camel endpoints support transactions. Those that do are called transaction oriented endpoints (or TOEs). For example, both the JMS component and the ActiveMQ component support transactions. To enable transactions on a component, you must perform the appropriate initialization before adding the component to the CamelContext . This entails writing code to initialize your transactional components explicitly. References The details of configuring transactions in Apache Camel are beyond the scope of this guide. For full details of how to use transactions, see the Apache Camel Transaction Guide . 11.10. Messaging Gateway Overview The messaging gateway pattern, shown in Figure 11.8, "Messaging Gateway Pattern" , describes an approach to integrating with a messaging system, where the messaging system's API remains hidden from the programmer at the application level. One of the more common example is when you want to translate synchronous method calls into request/reply message exchanges, without the programmer being aware of this. Figure 11.8. Messaging Gateway Pattern The following Apache Camel components provide this kind of integration with the messaging system: CXF Bean component 11.11. Service Activator Overview The service activator pattern, shown in Figure 11.9, "Service Activator Pattern" , describes the scenario where a service's operations are invoked in response to an incoming request message. The service activator identifies which operation to call and extracts the data to use as the operation's parameters. Finally, the service activator invokes an operation using the data extracted from the message. The operation invocation can be either oneway (request only) or two-way (request/reply). Figure 11.9. Service Activator Pattern In many respects, a service activator resembles a conventional remote procedure call (RPC), where operation invocations are encoded as messages. The main difference is that a service activator needs to be more flexible. An RPC framework standardizes the request and reply message encodings (for example, Web service operations are encoded as SOAP messages), whereas a service activator typically needs to improvise the mapping between the messaging system and the service's operations. Bean integration The main mechanism that Apache Camel provides to support the service activator pattern is bean integration . Bean integration provides a general framework for mapping incoming messages to method invocations on Java objects. For example, the Java fluent DSL provides the processors bean() and beanRef() that you can insert into a route to invoke methods on a registered Java bean. The detailed mapping of message data to Java method parameters is determined by the bean binding , which can be implemented by adding annotations to the bean class. For example, consider the following route which calls the Java method, BankBean.getUserAccBalance() , to service requests incoming on a JMS/ActiveMQ queue: The messages pulled from the ActiveMQ endpoint, activemq:BalanceQueries , have a simple XML format that provides the user ID of a bank account. For example: The first processor in the route, setProperty() , extracts the user ID from the In message and stores it in the userid exchange property. This is preferable to storing it in a header, because the In headers are not available after invoking the bean. The service activation step is performed by the beanRef() processor, which binds the incoming message to the getUserAccBalance() method on the Java object identified by the bankBean bean ID. The following code shows a sample implementation of the BankBean class: Where the binding of message data to method parameter is enabled by the @XPath annotation, which injects the content of the UserID XML element into the user method parameter. On completion of the call, the return value is inserted into the body of the Out message which is then copied into the In message for the step in the route. In order for the bean to be accessible to the beanRef() processor, you must instantiate an instance in Spring XML. For example, you can add the following lines to the META-INF/spring/camel-context.xml configuration file to instantiate the bean: Where the bean ID, bankBean , identifes this bean instance in the registry. The output of the bean invocation is injected into a Velocity template, to produce a properly formatted result message. The Velocity endpoint, velocity:file:src/scripts/acc_balance.vm , specifies the location of a velocity script with the following contents: The exchange instance is available as the Velocity variable, exchange , which enables you to retrieve the userid exchange property, using USD{exchange.getProperty("userid")} . The body of the current In message, USD{body} , contains the result of the getUserAccBalance() method invocation.	[ "import static org.apache.camel.builder.sql.SqlBuilder.sql; import org.apache.camel.Expression; Expression expression = sql(\"SELECT * FROM org.apache.camel.builder.sql.Person where name = :UserName\"); Object value = expression.evaluate(exchange);", "from(\"jms:HighVolumeQ\").to(\"cxf:bean:replica01\"); from(\"jms:HighVolumeQ\").to(\"cxf:bean:replica02\"); from(\"jms:HighVolumeQ\").to(\"cxf:bean:replica03\");", "from(\"jms:HighVolumeQ?concurrentConsumers=3\").to(\"cxf:bean:replica01\");", "<route> <from uri=\"jms:HighVolumeQ?concurrentConsumers=3\"/> <to uri=\"cxf:bean:replica01\"/> </route>", "// Stage 1: Read messages from file system. from(\"file://var/messages\").to(\"seda:fanout\"); // Stage 2: Perform concurrent processing (3 threads). from(\"seda:fanout\").to(\"cxf:bean:replica01\"); from(\"seda:fanout\").to(\"cxf:bean:replica02\"); from(\"seda:fanout\").to(\"cxf:bean:replica03\");", "from(\"jms:dispatcher?selector=CountryCode='US'\").to(\"cxf:bean:replica01\"); from(\"jms:dispatcher?selector=CountryCode='IE'\").to(\"cxf:bean:replica02\"); from(\"jms:dispatcher?selector=CountryCode='DE'\").to(\"cxf:bean:replica03\");", "from(\"jms:dispatcher?selector=\" + java.net.URLEncoder.encode(\"CountryCode='US'\",\"UTF-8\")). to(\"cxf:bean:replica01\");", "from(\"activemq:dispatcher?selector=CountryCode='US'\").to(\"cxf:bean:replica01\"); from(\"activemq:dispatcher?selector=CountryCode='IE'\").to(\"cxf:bean:replica02\"); from(\"activemq:dispatcher?selector=CountryCode='DE'\").to(\"cxf:bean:replica03\");", "from(\"jms:selective?selector=\" + java.net.URLEncoder.encode(\"CountryCode='US'\",\"UTF-8\")). to(\"cxf:bean:replica01\");", "from(\"acivemq:selective?selector=\" + java.net.URLEncoder.encode(\"CountryCode='US'\",\"UTF-8\")). to(\"cxf:bean:replica01\");", "from(\"seda:a\").filter(header(\"CountryCode\").isEqualTo(\"US\")).process(myProcessor);", "<camelContext id=\"buildCustomProcessorWithFilter\" xmlns=\"http://camel.apache.org/schema/spring\"> <route> <from uri=\"seda:a\"/> <filter> <xpath>USDCountryCode = 'US'</xpath> <process ref=\"#myProcessor\"/> </filter> </route> </camelContext>", "from(\"jms:topic:news?clientId=conn01&durableSubscriptionName=John.Doe\"). to(\"cxf:bean:newsprocessor\");", "from(\"activemq:topic:news?clientId=conn01&durableSubscriptionName=John.Doe\"). to(\"cxf:bean:newsprocessor\");", "from(\"jms:topic:news?clientId=conn01&durableSubscriptionName=John.Doe\"). to(\"seda:fanout\"); from(\"seda:fanout\").to(\"cxf:bean:newsproc01\"); from(\"seda:fanout\").to(\"cxf:bean:newsproc02\"); from(\"seda:fanout\").to(\"cxf:bean:newsproc03\");", "from(\"direct:start\").to(\"activemq:topic:foo\"); from(\"activemq:topic:foo?clientId=1&durableSubscriptionName=bar1\").to(\"mock:result1\"); from(\"activemq:topic:foo?clientId=2&durableSubscriptionName=bar2\").to(\"mock:result2\");", "<route> <from uri=\"direct:start\"/> <to uri=\"activemq:topic:foo\"/> </route> <route> <from uri=\"activemq:topic:foo?clientId=1&durableSubscriptionName=bar1\"/> <to uri=\"mock:result1\"/> </route> <route> <from uri=\"activemq:topic:foo?clientId=2&durableSubscriptionName=bar2\"/> <to uri=\"mock:result2\"/> </route>", "from(\"direct:start\").to(\"activemq:topic:VirtualTopic.foo\"); from(\"activemq:queue:Consumer.1.VirtualTopic.foo\").to(\"mock:result1\"); from(\"activemq:queue:Consumer.2.VirtualTopic.foo\").to(\"mock:result2\");", "<route> <from uri=\"direct:start\"/> <to uri=\"activemq:topic:VirtualTopic.foo\"/> </route> <route> <from uri=\"activemq:queue:Consumer.1.VirtualTopic.foo\"/> <to uri=\"mock:result1\"/> </route> <route> <from uri=\"activemq:queue:Consumer.2.VirtualTopic.foo\"/> <to uri=\"mock:result2\"/> </route>", "import static org.apache.camel.processor.idempotent.MemoryMessageIdRepository.memoryMessageIdRepository; RouteBuilder builder = new RouteBuilder() { public void configure() { from(\"seda:a\") .idempotentConsumer( header(\"TransactionID\"), memoryMessageIdRepository(200) ).to(\"seda:b\"); } };", "<camelContext id=\"buildIdempotentConsumer\" xmlns=\"http://camel.apache.org/schema/spring\"> <route> <from uri=\"seda:a\"/> <idempotentConsumer messageIdRepositoryRef=\"MsgIDRepos\"> <simple>header.TransactionID</simple> <to uri=\"seda:b\"/> </idempotentConsumer> </route> </camelContext> <bean id=\"MsgIDRepos\" class=\"org.apache.camel.processor.idempotent.MemoryMessageIdRepository\"> <!-- Specify the in-memory cache size. --> <constructor-arg type=\"int\" value=\"200\"/> </bean>", "import org.springframework.orm.jpa.JpaTemplate; import org.apache.camel.spring.SpringRouteBuilder; import static org.apache.camel.processor.idempotent.jpa.JpaMessageIdRepository.jpaMessageIdRepository; RouteBuilder builder = new SpringRouteBuilder() { public void configure() { from(\"seda:a\").idempotentConsumer( header(\"TransactionID\"), jpaMessageIdRepository(bean(JpaTemplate.class), \"myProcessorName\") ).to(\"seda:b\"); } };", "<!-- repository for the idempotent consumer --> <bean id=\"myRepo\" class=\"org.apache.camel.processor.idempotent.MemoryIdempotentRepository\"/> <camelContext xmlns=\"http://camel.apache.org/schema/spring\"> <route> <from uri=\"direct:start\"/> <idempotentConsumer messageIdRepositoryRef=\"myRepo\"> <!-- use the messageId header as key for identifying duplicate messages --> <header>messageId</header> <!-- if not a duplicate send it to this mock endpoint --> <to uri=\"mock:result\"/> </idempotentConsumer> </route> </camelContext>", "<bean id=\"dataSource\" class=\"org.springframework.jdbc.datasource.SingleConnectionDataSource\"> <property name=\"driverClassName\" value=\"org.hsqldb.jdbcDriver\"/> <property name=\"url\" value=\"jdbc:hsqldb:mem:camel_jdbc\"/> <property name=\"username\" value=\"sa\"/> <property name=\"password\" value=\"\"/> </bean>", "<bean id=\"messageIdRepository\" class=\"org.apache.camel.processor.idempotent.jdbc.JdbcMessageIdRepository\"> <constructor-arg ref=\"dataSource\" /> <constructor-arg value=\"myProcessorName\" /> </bean> <camel:camelContext> <camel:errorHandler id=\"deadLetterChannel\" type=\"DeadLetterChannel\" deadLetterUri=\"mock:error\"> <camel:redeliveryPolicy maximumRedeliveries=\"0\" maximumRedeliveryDelay=\"0\" logStackTrace=\"false\" /> </camel:errorHandler> <camel:route id=\"JdbcMessageIdRepositoryTest\" errorHandlerRef=\"deadLetterChannel\"> <camel:from uri=\"direct:start\" /> <camel:idempotentConsumer messageIdRepositoryRef=\"messageIdRepository\"> <camel:header>messageId</camel:header> <camel:to uri=\"mock:result\" /> </camel:idempotentConsumer> </camel:route> </camel:camelContext>", "from(\"direct:start\") // instruct idempotent consumer to not skip duplicates as we will filter then our self .idempotentConsumer(header(\"messageId\")).messageIdRepository(repo).skipDuplicate(false) .filter(property(Exchange.DUPLICATE_MESSAGE).isEqualTo(true)) // filter out duplicate messages by sending them to someplace else and then stop .to(\"mock:duplicate\") .stop() .end() // and here we process only new messages (no duplicates) .to(\"mock:result\");", "<!-- idempotent repository, just use a memory based for testing --> <bean id=\"myRepo\" class=\"org.apache.camel.processor.idempotent.MemoryIdempotentRepository\"/> <camelContext xmlns=\"http://camel.apache.org/schema/spring\"> <route> <from uri=\"direct:start\"/> <!-- we do not want to skip any duplicate messages --> <idempotentConsumer messageIdRepositoryRef=\"myRepo\" skipDuplicate=\"false\"> <!-- use the messageId header as key for identifying duplicate messages --> <header>messageId</header> <!-- we will to handle duplicate messages using a filter --> <filter> <!-- the filter will only react on duplicate messages, if this property is set on the Exchange --> <property>CamelDuplicateMessage</property> <!-- and send the message to this mock, due its part of an unit test --> <!-- but you can of course do anything as its part of the route --> <to uri=\"mock:duplicate\"/> <!-- and then stop --> <stop/> </filter> <!-- here we route only new messages --> <to uri=\"mock:result\"/> </idempotentConsumer> </route> </camelContext>", "HazelcastIdempotentRepository idempotentRepo = new HazelcastIdempotentRepository(\"myrepo\"); from(\"direct:in\").idempotentConsumer(header(\"messageId\"), idempotentRepo).to(\"mock:out\");", "from(\"activemq:BalanceQueries\") .setProperty(\"userid\", xpath(\"/Account/BalanceQuery/UserID\").stringResult()) .beanRef(\"bankBean\", \"getUserAccBalance\") .to(\"velocity:file:src/scripts/acc_balance.vm\") .to(\"activemq:BalanceResults\");", "<?xml version='1.0' encoding='UTF-8'?> <Account> <BalanceQuery> <UserID>James.Strachan</UserID> </BalanceQuery> </Account>", "package tutorial; import org.apache.camel.language.XPath; public class BankBean { public int getUserAccBalance( @XPath(\"/Account/BalanceQuery/UserID\") String user) { if (user.equals(\"James.Strachan\")) { return 1200; } else { return 0; } } }", "<?xml version=\"1.0\" encoding=\"UTF-8\"?> <beans ... > <bean id=\"bankBean\" class=\"tutorial.BankBean\"/> </beans>", "<?xml version='1.0' encoding='UTF-8'?> <Account> <BalanceResult> <UserID>USD{exchange.getProperty(\"userid\")}</UserID> <Balance>USD{body}</Balance> </BalanceResult> </Account>" ]	https://docs.redhat.com/en/documentation/red_hat_fuse/7.13/html/apache_camel_development_guide/msgend
Chapter 10. Provisioning [metal3.io/v1alpha1]	Chapter 10. Provisioning [metal3.io/v1alpha1] Description Provisioning contains configuration used by the Provisioning service (Ironic) to provision baremetal hosts. Provisioning is created by the OpenShift installer using admin or user provided information about the provisioning network and the NIC on the server that can be used to PXE boot it. This CR is a singleton, created by the installer and currently only consumed by the cluster-baremetal-operator to bring up and update containers in a metal3 cluster. Type object 10.1. Specification Property Type Description apiVersion string APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#resources kind string Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds metadata ObjectMeta Standard object's metadata. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata spec object ProvisioningSpec defines the desired state of Provisioning status object ProvisioningStatus defines the observed state of Provisioning 10.1.1. .spec Description ProvisioningSpec defines the desired state of Provisioning Type object Property Type Description bootIsoSource string BootIsoSource provides a way to set the location where the iso image to boot the nodes will be served from. By default the boot iso image is cached locally and served from the Provisioning service (Ironic) nodes using an auxiliary httpd server. If the boot iso image is already served by an httpd server, setting this option to http allows to directly provide the image from there; in this case, the network (either internal or external) where the httpd server that hosts the boot iso is needs to be accessible by the metal3 pod. disableVirtualMediaTLS boolean DisableVirtualMediaTLS turns off TLS on the virtual media server, which may be required for hardware that cannot accept HTTPS links. preProvisioningOSDownloadURLs object PreprovisioningOSDownloadURLs is set of CoreOS Live URLs that would be necessary to provision a worker either using virtual media or PXE. provisioningDHCPExternal boolean ProvisioningDHCPExternal indicates whether the DHCP server for IP addresses in the provisioning DHCP range is present within the metal3 cluster or external to it. This field is being deprecated in favor of provisioningNetwork. provisioningDHCPRange string ProvisioningDHCPRange needs to be interpreted along with ProvisioningDHCPExternal. If the value of provisioningDHCPExternal is set to False, then ProvisioningDHCPRange represents the range of IP addresses that the DHCP server running within the metal3 cluster can use while provisioning baremetal servers. If the value of ProvisioningDHCPExternal is set to True, then the value of ProvisioningDHCPRange will be ignored. When the value of ProvisioningDHCPExternal is set to False, indicating an internal DHCP server and the value of ProvisioningDHCPRange is not set, then the DHCP range is taken to be the default range which goes from .10 to .100 of the ProvisioningNetworkCIDR. This is the only value in all of the Provisioning configuration that can be changed after the installer has created the CR. This value needs to be two comma sererated IP addresses within the ProvisioningNetworkCIDR where the 1st address represents the start of the range and the 2nd address represents the last usable address in the range. provisioningDNS boolean ProvisioningDNS allows sending the DNS information via DHCP on the provisionig network. It is off by default since the Provisioning service itself (Ironic) does not require DNS, but it may be useful for layered products (e.g. ZTP). provisioningIP string ProvisioningIP is the IP address assigned to the provisioningInterface of the baremetal server. This IP address should be within the provisioning subnet, and outside of the DHCP range. provisioningInterface string ProvisioningInterface is the name of the network interface on a baremetal server to the provisioning network. It can have values like eth1 or ens3. provisioningMacAddresses array (string) ProvisioningMacAddresses is a list of mac addresses of network interfaces on a baremetal server to the provisioning network. Use this instead of ProvisioningInterface to allow interfaces of different names. If not provided it will be populated by the BMH.Spec.BootMacAddress of each master. provisioningNetwork string ProvisioningNetwork provides a way to indicate the state of the underlying network configuration for the provisioning network. This field can have one of the following values - Managed - when the provisioning network is completely managed by the Baremetal IPI solution. Unmanaged - when the provsioning network is present and used but the user is responsible for managing DHCP. Virtual media provisioning is recommended but PXE is still available if required. Disabled - when the provisioning network is fully disabled. User can bring up the baremetal cluster using virtual media or assisted installation. If using metal3 for power management, BMCs must be accessible from the machine networks. User should provide two IPs on the external network that would be used for provisioning services. provisioningNetworkCIDR string ProvisioningNetworkCIDR is the network on which the baremetal nodes are provisioned. The provisioningIP and the IPs in the dhcpRange all come from within this network. When using IPv6 and in a network managed by the Baremetal IPI solution this cannot be a network larger than a /64. provisioningOSDownloadURL string ProvisioningOSDownloadURL is the location from which the OS Image used to boot baremetal host machines can be downloaded by the metal3 cluster. virtualMediaViaExternalNetwork boolean VirtualMediaViaExternalNetwork flag when set to "true" allows for workers to boot via Virtual Media and contact metal3 over the External Network. When the flag is set to "false" (which is the default), virtual media deployments can still happen based on the configuration specified in the ProvisioningNetwork i.e when in Disabled mode, over the External Network and over Provisioning Network when in Managed mode. PXE deployments will always use the Provisioning Network and will not be affected by this flag. watchAllNamespaces boolean WatchAllNamespaces provides a way to explicitly allow use of this Provisioning configuration across all Namespaces. It is an optional configuration which defaults to false and in that state will be used to provision baremetal hosts in only the openshift-machine-api namespace. When set to true, this provisioning configuration would be used for baremetal hosts across all namespaces. 10.1.2. .spec.preProvisioningOSDownloadURLs Description PreprovisioningOSDownloadURLs is set of CoreOS Live URLs that would be necessary to provision a worker either using virtual media or PXE. Type object Property Type Description initramfsURL string InitramfsURL Image URL to be used for PXE deployments isoURL string IsoURL Image URL to be used for Live ISO deployments kernelURL string KernelURL is an Image URL to be used for PXE deployments rootfsURL string RootfsURL Image URL to be used for PXE deployments 10.1.3. .status Description ProvisioningStatus defines the observed state of Provisioning Type object Property Type Description conditions array conditions is a list of conditions and their status conditions[] object OperatorCondition is just the standard condition fields. generations array generations are used to determine when an item needs to be reconciled or has changed in a way that needs a reaction. generations[] object GenerationStatus keeps track of the generation for a given resource so that decisions about forced updates can be made. observedGeneration integer observedGeneration is the last generation change you've dealt with readyReplicas integer readyReplicas indicates how many replicas are ready and at the desired state version string version is the level this availability applies to 10.1.4. .status.conditions Description conditions is a list of conditions and their status Type array 10.1.5. .status.conditions[] Description OperatorCondition is just the standard condition fields. Type object Property Type Description lastTransitionTime string message string reason string status string type string 10.1.6. .status.generations Description generations are used to determine when an item needs to be reconciled or has changed in a way that needs a reaction. Type array 10.1.7. .status.generations[] Description GenerationStatus keeps track of the generation for a given resource so that decisions about forced updates can be made. Type object Property Type Description group string group is the group of the thing you're tracking hash string hash is an optional field set for resources without generation that are content sensitive like secrets and configmaps lastGeneration integer lastGeneration is the last generation of the workload controller involved name string name is the name of the thing you're tracking namespace string namespace is where the thing you're tracking is resource string resource is the resource type of the thing you're tracking 10.2. API endpoints The following API endpoints are available: /apis/metal3.io/v1alpha1/provisionings DELETE : delete collection of Provisioning GET : list objects of kind Provisioning POST : create a Provisioning /apis/metal3.io/v1alpha1/provisionings/{name} DELETE : delete a Provisioning GET : read the specified Provisioning PATCH : partially update the specified Provisioning PUT : replace the specified Provisioning /apis/metal3.io/v1alpha1/provisionings/{name}/status GET : read status of the specified Provisioning PATCH : partially update status of the specified Provisioning PUT : replace status of the specified Provisioning 10.2.1. /apis/metal3.io/v1alpha1/provisionings Table 10.1. Global query parameters Parameter Type Description pretty string If 'true', then the output is pretty printed. HTTP method DELETE Description delete collection of Provisioning Table 10.2. Query parameters Parameter Type Description allowWatchBookmarks boolean allowWatchBookmarks requests watch events with type "BOOKMARK". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset sendInitialEvents boolean sendInitialEvents=true may be set together with watch=true . In that case, the watch stream will begin with synthetic events to produce the current state of objects in the collection. Once all such events have been sent, a synthetic "Bookmark" event will be sent. The bookmark will report the ResourceVersion (RV) corresponding to the set of objects, and be marked with "k8s.io/initial-events-end": "true" annotation. Afterwards, the watch stream will proceed as usual, sending watch events corresponding to changes (subsequent to the RV) to objects watched. When sendInitialEvents option is set, we require resourceVersionMatch option to also be set. The semantic of the watch request is as following: - resourceVersionMatch = NotOlderThan is interpreted as "data at least as new as the provided resourceVersion`" and the bookmark event is send when the state is synced to a `resourceVersion at least as fresh as the one provided by the ListOptions. If resourceVersion is unset, this is interpreted as "consistent read" and the bookmark event is send when the state is synced at least to the moment when request started being processed. - resourceVersionMatch set to any other value or unset Invalid error is returned. Defaults to true if resourceVersion="" or resourceVersion="0" (for backward compatibility reasons) and to false otherwise. timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. watch boolean Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. Table 10.3. HTTP responses HTTP code Reponse body 200 - OK Status schema 401 - Unauthorized Empty HTTP method GET Description list objects of kind Provisioning Table 10.4. Query parameters Parameter Type Description allowWatchBookmarks boolean allowWatchBookmarks requests watch events with type "BOOKMARK". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset sendInitialEvents boolean sendInitialEvents=true may be set together with watch=true . In that case, the watch stream will begin with synthetic events to produce the current state of objects in the collection. Once all such events have been sent, a synthetic "Bookmark" event will be sent. The bookmark will report the ResourceVersion (RV) corresponding to the set of objects, and be marked with "k8s.io/initial-events-end": "true" annotation. Afterwards, the watch stream will proceed as usual, sending watch events corresponding to changes (subsequent to the RV) to objects watched. When sendInitialEvents option is set, we require resourceVersionMatch option to also be set. The semantic of the watch request is as following: - resourceVersionMatch = NotOlderThan is interpreted as "data at least as new as the provided resourceVersion`" and the bookmark event is send when the state is synced to a `resourceVersion at least as fresh as the one provided by the ListOptions. If resourceVersion is unset, this is interpreted as "consistent read" and the bookmark event is send when the state is synced at least to the moment when request started being processed. - resourceVersionMatch set to any other value or unset Invalid error is returned. Defaults to true if resourceVersion="" or resourceVersion="0" (for backward compatibility reasons) and to false otherwise. timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. watch boolean Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. Table 10.5. HTTP responses HTTP code Reponse body 200 - OK ProvisioningList schema 401 - Unauthorized Empty HTTP method POST Description create a Provisioning Table 10.6. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 10.7. Body parameters Parameter Type Description body Provisioning schema Table 10.8. HTTP responses HTTP code Reponse body 200 - OK Provisioning schema 201 - Created Provisioning schema 202 - Accepted Provisioning schema 401 - Unauthorized Empty 10.2.2. /apis/metal3.io/v1alpha1/provisionings/{name} Table 10.9. Global path parameters Parameter Type Description name string name of the Provisioning Table 10.10. Global query parameters Parameter Type Description pretty string If 'true', then the output is pretty printed. HTTP method DELETE Description delete a Provisioning Table 10.11. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed gracePeriodSeconds integer The duration in seconds before the object should be deleted. Value must be non-negative integer. The value zero indicates delete immediately. If this value is nil, the default grace period for the specified type will be used. Defaults to a per object value if not specified. zero means delete immediately. orphanDependents boolean Deprecated: please use the PropagationPolicy, this field will be deprecated in 1.7. Should the dependent objects be orphaned. If true/false, the "orphan" finalizer will be added to/removed from the object's finalizers list. Either this field or PropagationPolicy may be set, but not both. propagationPolicy string Whether and how garbage collection will be performed. Either this field or OrphanDependents may be set, but not both. The default policy is decided by the existing finalizer set in the metadata.finalizers and the resource-specific default policy. Acceptable values are: 'Orphan' - orphan the dependents; 'Background' - allow the garbage collector to delete the dependents in the background; 'Foreground' - a cascading policy that deletes all dependents in the foreground. Table 10.12. Body parameters Parameter Type Description body DeleteOptions schema Table 10.13. HTTP responses HTTP code Reponse body 200 - OK Status schema 202 - Accepted Status schema 401 - Unauthorized Empty HTTP method GET Description read the specified Provisioning Table 10.14. Query parameters Parameter Type Description resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset Table 10.15. HTTP responses HTTP code Reponse body 200 - OK Provisioning schema 401 - Unauthorized Empty HTTP method PATCH Description partially update the specified Provisioning Table 10.16. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . This field is required for apply requests (application/apply-patch) but optional for non-apply patch types (JsonPatch, MergePatch, StrategicMergePatch). fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. force boolean Force is going to "force" Apply requests. It means user will re-acquire conflicting fields owned by other people. Force flag must be unset for non-apply patch requests. Table 10.17. Body parameters Parameter Type Description body Patch schema Table 10.18. HTTP responses HTTP code Reponse body 200 - OK Provisioning schema 401 - Unauthorized Empty HTTP method PUT Description replace the specified Provisioning Table 10.19. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 10.20. Body parameters Parameter Type Description body Provisioning schema Table 10.21. HTTP responses HTTP code Reponse body 200 - OK Provisioning schema 201 - Created Provisioning schema 401 - Unauthorized Empty 10.2.3. /apis/metal3.io/v1alpha1/provisionings/{name}/status Table 10.22. Global path parameters Parameter Type Description name string name of the Provisioning Table 10.23. Global query parameters Parameter Type Description pretty string If 'true', then the output is pretty printed. HTTP method GET Description read status of the specified Provisioning Table 10.24. Query parameters Parameter Type Description resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset Table 10.25. HTTP responses HTTP code Reponse body 200 - OK Provisioning schema 401 - Unauthorized Empty HTTP method PATCH Description partially update status of the specified Provisioning Table 10.26. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . This field is required for apply requests (application/apply-patch) but optional for non-apply patch types (JsonPatch, MergePatch, StrategicMergePatch). fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. force boolean Force is going to "force" Apply requests. It means user will re-acquire conflicting fields owned by other people. Force flag must be unset for non-apply patch requests. Table 10.27. Body parameters Parameter Type Description body Patch schema Table 10.28. HTTP responses HTTP code Reponse body 200 - OK Provisioning schema 401 - Unauthorized Empty HTTP method PUT Description replace status of the specified Provisioning Table 10.29. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 10.30. Body parameters Parameter Type Description body Provisioning schema Table 10.31. HTTP responses HTTP code Reponse body 200 - OK Provisioning schema 201 - Created Provisioning schema 401 - Unauthorized Empty	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.14/html/provisioning_apis/provisioning-metal3-io-v1alpha1
Chapter 3. Deployment of the Ceph File System	Chapter 3. Deployment of the Ceph File System As a storage administrator, you can deploy Ceph File Systems (CephFS) in a storage environment and have clients mount those Ceph File Systems to meet the storage needs. Basically, the deployment workflow is three steps: Create Ceph File Systems on a Ceph Monitor node. Create a Ceph client user with the appropriate capabilities, and make the client key available on the node where the Ceph File System will be mounted. Mount CephFS on a dedicated node, using either a kernel client or a File System in User Space (FUSE) client. Prerequisites A running, and healthy Red Hat Ceph Storage cluster. Installation and configuration of the Ceph Metadata Server daemon ( ceph-mds ). 3.1. Layout, quota, snapshot, and network restrictions These user capabilities can help you restrict access to a Ceph File System (CephFS) based on the needed requirements. Important All user capability flags, except rw , must be specified in alphabetical order. Layouts and Quotas When using layouts or quotas, clients require the p flag, in addition to rw capabilities. Setting the p flag restricts all the attributes being set by special extended attributes, those with a ceph. prefix. Also, this restricts other means of setting these fields, such as openc operations with layouts. Example In this example, client.0 can modify layouts and quotas on the file system cephfs_a , but client.1 cannot. Snapshots When creating or deleting snapshots, clients require the s flag, in addition to rw capabilities. When the capability string also contains the p flag, the s flag must appear after it. Example In this example, client.0 can create or delete snapshots in the temp directory of file system cephfs_a . Network Restricting clients connecting from a particular network. Example The optional network and prefix length is in CIDR notation, for example, 10.3.0.0/16 . Additional Resources See the Creating client users for a Ceph File System section in the Red Hat Ceph Storage File System Guide for details on setting the Ceph user capabilities. 3.2. Creating Ceph File Systems You can create multiple Ceph File Systems (CephFS) on a Ceph Monitor node. Prerequisites A running, and healthy Red Hat Ceph Storage cluster. Installation and configuration of the Ceph Metadata Server daemon ( ceph-mds ). Root-level access to a Ceph Monitor node. Root-level access to a Ceph client node. Procedure Configure the client node to use the Ceph storage cluster. Enable the Red Hat Ceph Storage Tools repository: Red Hat Enterprise Linux 8 Red Hat Enterprise Linux 9 Install the ceph-fuse package: Copy the Ceph client keyring from the Ceph Monitor node to the client node: Syntax Replace MONITOR_NODE_NAME with the Ceph Monitor host name or IP address. Example Copy the Ceph configuration file from a Ceph Monitor node to the client node: Syntax Replace MONITOR_NODE_NAME with the Ceph Monitor host name or IP address. Example Set the appropriate permissions for the configuration file: Create a Ceph File System: Syntax Example Repeat this step to create additional file systems. Note By running this command, Ceph automatically creates the new pools, and deploys a new Ceph Metadata Server (MDS) daemon to support the new file system. This also configures the MDS affinity accordingly. Verify access to the new Ceph File System from a Ceph client. Authorize a Ceph client to access the new file system: Syntax Example Note Optionally, you can add a safety measure by specifying the root_squash option. This prevents accidental deletion scenarios by disallowing clients with a uid=0 or gid=0 to do write operations, but still allows read operations. Example In this example, root_squash is enabled for the file system cephfs01 , except within the /volumes directory tree. Important The Ceph client can only see the CephFS it is authorized for. Copy the Ceph user's keyring to the Ceph client node: Syntax Example On the Ceph client node, create a new directory: Syntax Example On the Ceph client node, mount the new Ceph File System: Syntax Example On the Ceph client node, list the directory contents of the new mount point, or create a file on the new mount point. Additional Resources See the Creating client users for a Ceph File System section in the Red Hat Ceph Storage File System Guide for more details. See the Mounting the Ceph File System as a kernel client section in the Red Hat Ceph Storage File System Guide for more details. See the Mounting the Ceph File System as a FUSE client section in the Red Hat Ceph Storage File System Guide for more details. See Ceph File System limitations and the POSIX standards section in the Red Hat Ceph Storage File System Guide for more details. See the Pools chapter in the Red Hat Ceph Storage Storage Strategies Guide for more details. 3.3. Adding an erasure-coded pool to a Ceph File System By default, Ceph uses replicated pools for data pools. You can also add an additional erasure-coded data pool to the Ceph File System, if needed. Ceph File Systems (CephFS) backed by erasure-coded pools use less overall storage compared to Ceph File Systems backed by replicated pools. While erasure-coded pools use less overall storage, they also use more memory and processor resources than replicated pools. Important CephFS EC pools are for archival purpose only. Important For production environments, Red Hat recommends using the default replicated data pool for CephFS. The creation of inodes in CephFS creates at least one object in the default data pool. It is better to use a replicated pool for the default data to improve small-object write performance, and to improve read performance for updating backtraces. Prerequisites A running Red Hat Ceph Storage cluster. An existing Ceph File System. Pools using BlueStore OSDs. Root-level access to a Ceph Monitor node. Installation of the attr package. Procedure Create an erasure-coded data pool for CephFS: Syntax Example Verify the pool was added: Example Enable overwrites on the erasure-coded pool: Syntax Example Verify the status of the Ceph File System: Syntax Example Add the erasure-coded data pool to the existing CephFS: Syntax Example This example adds the new data pool, cephfs-data-ec01 , to the existing erasure-coded file system, cephfs-ec . Verify that the erasure-coded pool was added to the Ceph File System: Syntax Example Set the file layout on a new directory: Syntax Example In this example, all new files created in the /mnt/cephfs/newdir directory inherit the directory layout and places the data in the newly added erasure-coded pool. Additional Resources See The Ceph File System Metadata Server chapter in the Red Hat Ceph Storage File System Guide for more information about CephFS MDS. See the Creating Ceph File Systems section in the Red Hat Ceph Storage File System Guide for more information. See the Erasure Code Pools chapter in the Red Hat Ceph Storage Storage Strategies Guide for more information. See the Erasure Coding with Overwrites section in the Red Hat Ceph Storage Storage Strategies Guide for more information. 3.4. Creating client users for a Ceph File System Red Hat Ceph Storage uses cephx for authentication, which is enabled by default. To use cephx with the Ceph File System, create a user with the correct authorization capabilities on a Ceph Monitor node and make its key available on the node where the Ceph File System will be mounted. Prerequisites A running Red Hat Ceph Storage cluster. Installation and configuration of the Ceph Metadata Server daemon (ceph-mds). Root-level access to a Ceph Monitor node. Root-level access to a Ceph client node. Procedure Log into the Cephadm shell on the monitor node: Example On a Ceph Monitor node, create a client user: Syntax To restrict the client to only writing in the temp directory of filesystem cephfs_a : Example To completely restrict the client to the temp directory, remove the root ( / ) directory: Example Note Supplying all or asterisk as the file system name grants access to every file system. Typically, it is necessary to quote the asterisk to protect it from the shell. Verify the created key: Syntax Example Copy the keyring to the client. On the Ceph Monitor node, export the keyring to a file: Syntax Example Copy the client keyring from the Ceph Monitor node to the /etc/ceph/ directory on the client node: Syntax Replace CLIENT_NODE_NAME with the Ceph client node name or IP. Example From the client node, set the appropriate permissions for the keyring file: Syntax Example Additional Resources See the Ceph user management chapter in the Red Hat Ceph Storage Administration Guide for more details. 3.5. Mounting the Ceph File System as a kernel client You can mount the Ceph File System (CephFS) as a kernel client, either manually or automatically on system boot. Important Clients running on other Linux distributions, aside from Red Hat Enterprise Linux, are permitted but not supported. If issues are found in the CephFS Metadata Server or other parts of the storage cluster when using these clients, Red Hat will address them. If the cause is found to be on the client side, then the issue will have to be addressed by the kernel vendor of the Linux distribution. Prerequisites Root-level access to a Linux-based client node. Root-level access to a Ceph Monitor node. An existing Ceph File System. Procedure Configure the client node to use the Ceph storage cluster. Enable the Red Hat Ceph Storage 6 Tools repository: Red Hat Enterprise Linux 8 Red Hat Enterprise Linux 9 Install the ceph-common package: Log into the Cephadm shell on the monitor node: Example Copy the Ceph client keyring from the Ceph Monitor node to the client node: Syntax Replace CLIENT_NODE_NAME with the Ceph client host name or IP address. Example Copy the Ceph configuration file from a Ceph Monitor node to the client node: Syntax Replace CLIENT_NODE_NAME with the Ceph client host name or IP address. Example From the client node, set the appropriate permissions for the configuration file: Choose either automatically or manually mounting. Manually Mounting Create a mount directory on the client node: Syntax Example Mount the Ceph File System. To specify multiple Ceph Monitor addresses, separate them with commas in the mount command, specify the mount point, and set the client name: Note As of Red Hat Ceph Storage 4.1, mount.ceph can read keyring files directly. As such, a secret file is no longer necessary. Just specify the client ID with name= CLIENT_ID , and mount.ceph will find the right keyring file. Syntax Example Note You can configure a DNS server so that a single host name resolves to multiple IP addresses. Then you can use that single host name with the mount command, instead of supplying a comma-separated list. Note You can also replace the Monitor host names with the string :/ and mount.ceph will read the Ceph configuration file to determine which Monitors to connect to. Note You can set the nowsync option to asynchronously execute file creation and removal on the Red Hat Ceph Storage clusters. This improves the performance of some workloads by avoiding round-trip latency for these system calls without impacting consistency. The nowsync option requires kernel clients with Red Hat Enterprise Linux 9.0 or later. Example Verify that the file system is successfully mounted: Syntax Example Automatically Mounting On the client host, create a new directory for mounting the Ceph File System. Syntax Example Edit the /etc/fstab file as follows: Syntax The first column sets the Ceph Monitor host names and the port number. The second column sets the mount point The third column sets the file system type, in this case, ceph , for CephFS. The fourth column sets the various options, such as, the user name and the secret file using the name and secretfile options. You can also set specific volumes, sub-volume groups, and sub-volumes using the ceph.client_mountpoint option. Set the _netdev option to ensure that the file system is mounted after the networking subsystem starts to prevent hanging and networking issues. If you do not need access time information, then setting the noatime option can increase performance. Set the fifth and sixth columns to zero. Example The Ceph File System will be mounted on the system boot. Note As of Red Hat Ceph Storage 4.1, mount.ceph can read keyring files directly. As such, a secret file is no longer necessary. Just specify the client ID with name= CLIENT_ID , and mount.ceph will find the right keyring file. Note You can also replace the Monitor host names with the string :/ and mount.ceph will read the Ceph configuration file to determine which Monitors to connect to. Additional Resources See the mount(8) manual page. See the Ceph user management chapter in the Red Hat Ceph Storage Administration Guide for more details on creating a Ceph user. See the Creating Ceph File Systems section of the Red Hat Ceph Storage File System Guide for details. 3.6. Mounting the Ceph File System as a FUSE client You can mount the Ceph File System (CephFS) as a File System in User Space (FUSE) client, either manually or automatically on system boot. Prerequisites Root-level access to a Linux-based client node. Root-level access to a Ceph Monitor node. An existing Ceph File System. Procedure Configure the client node to use the Ceph storage cluster. Enable the Red Hat Ceph Storage 6 Tools repository: Red Hat Enterprise Linux 8 Red Hat Enterprise Linux 9 Install the ceph-fuse package: Log into the Cephadm shell on the monitor node: Example Copy the Ceph client keyring from the Ceph Monitor node to the client node: Syntax Replace CLIENT_NODE_NAME with the Ceph client host name or IP address. Example Copy the Ceph configuration file from a Ceph Monitor node to the client node: Syntax Replace CLIENT_NODE_NAME with the Ceph client host name or IP address. Example From the client node, set the appropriate permissions for the configuration file: Choose either automatically or manually mounting. Manually Mounting On the client node, create a directory for the mount point: Syntax Example Note If you used the path option with MDS capabilities, then the mount point must be within what is specified by the path . Use the ceph-fuse utility to mount the Ceph File System. Syntax Example Note If you do not use the default name and location of the user keyring, that is /etc/ceph/ceph.client. CLIENT_ID .keyring , then use the --keyring option to specify the path to the user keyring, for example: Example Note Use the -r option to instruct the client to treat that path as its root: Syntax Example Note If you want to automatically reconnect an evicted Ceph client, then add the --client_reconnect_stale=true option. Example Verify that the file system is successfully mounted: Syntax Example Automatically Mounting On the client node, create a directory for the mount point: Syntax Example Note If you used the path option with MDS capabilities, then the mount point must be within what is specified by the path . Edit the /etc/fstab file as follows: Syntax The first column sets the Ceph Monitor host names and the port number. The second column sets the mount point The third column sets the file system type, in this case, fuse.ceph , for CephFS. The fourth column sets the various options, such as the user name and the keyring using the ceph.name and ceph.keyring options. You can also set specific volumes, sub-volume groups, and sub-volumes using the ceph.client_mountpoint option. To specify which Ceph File System to access, use the ceph.client_fs option. Set the _netdev option to ensure that the file system is mounted after the networking subsystem starts to prevent hanging and networking issues. If you do not need access time information, then setting the noatime option can increase performance. If you want to automatically reconnect after an eviction, then set the client_reconnect_stale=true option. Set the fifth and sixth columns to zero. Example The Ceph File System will be mounted on the system boot. Additional Resources The ceph-fuse(8) manual page. See the Ceph user management chapter in the Red Hat Ceph Storage Administration Guide for more details on creating a Ceph user. See the Creating Ceph File Systems section of the Red Hat Ceph Storage File System Guide for details. Additional Resources See Section 2.5, "Management of MDS service using the Ceph Orchestrator" to install Ceph Metadata servers. See Section 3.2, "Creating Ceph File Systems" for details. See Section 3.4, "Creating client users for a Ceph File System" for details. See Section 3.5, "Mounting the Ceph File System as a kernel client" for details. See Section 3.6, "Mounting the Ceph File System as a FUSE client" for details. See Chapter 2, The Ceph File System Metadata Server for details on configuring the CephFS Metadata Server daemon.	[ "client.0 key: AQAz7EVWygILFRAAdIcuJ10opU/JKyfFmxhuaw== caps: [mds] allow rwp caps: [mon] allow r caps: [osd] allow rw tag cephfs data=cephfs_a client.1 key: AQAz7EVWygILFRAAdIcuJ11opU/JKyfFmxhuaw== caps: [mds] allow rw caps: [mon] allow r caps: [osd] allow rw tag cephfs data=cephfs_a", "client.0 key: AQAz7EVWygILFRAAdIcuJ10opU/JKyfFmxhuaw== caps: [mds] allow rw, allow rws path=/temp caps: [mon] allow r caps: [osd] allow rw tag cephfs data=cephfs_a", "client.0 key: AQAz7EVWygILFRAAdIcuJ10opU/JKyfFmxhuaw== caps: [mds] allow r network 10.0.0.0/8, allow rw path=/bar network 10.0.0.0/8 caps: [mon] allow r network 10.0.0.0/8 caps: [osd] allow rw tag cephfs data=cephfs_a network 10.0.0.0/8", "subscription-manager repos --enable=rhceph-6-tools-for-rhel-8-x86_64-rpms", "subscription-manager repos --enable=rhceph-6-tools-for-rhel-9-x86_64-rpms", "dnf install ceph-fuse", "scp root@ MONITOR_NODE_NAME :/etc/ceph/ KEYRING_FILE /etc/ceph/", "scp [email protected]:/etc/ceph/ceph.client.1.keyring /etc/ceph/", "scp root@ MONITOR_NODE_NAME :/etc/ceph/ceph.conf /etc/ceph/ceph.conf", "scp [email protected]:/etc/ceph/ceph.conf /etc/ceph/ceph.conf", "chmod 644 /etc/ceph/ceph.conf", "ceph fs volume create FILE_SYSTEM_NAME", "ceph fs volume create cephfs01", "ceph fs authorize FILE_SYSTEM_NAME CLIENT_NAME DIRECTORY PERMISSIONS", "ceph fs authorize cephfs01 client.1 / rw [client.1] key = BQAmthpf81M+JhAAiHDYQkMiCq3x+J0n9e8REK== ceph auth get client.1 exported keyring for client.1 [client.1] key = BQAmthpf81M+JhAAiHDYQkMiCq3x+J0n9e8REK== caps mds = \"allow rw fsname=cephfs01\" caps mon = \"allow r fsname=cephfs01\" caps osd = \"allow rw tag cephfs data=cephfs01\"", "ceph fs authorize cephfs01 client.1 / rw root_squash /volumes rw [client.1] key = BQAmthpf81M+JhAAiHDYQkMiCq3x+J0n9e8REK== ceph auth get client.1 [client.1] key = BQAmthpf81M+JhAAiHDYQkMiCq3x+J0n9e8REK== caps mds = \"allow rw fsname=cephfs01 root_squash, allow rw fsname=cephfs01 path=/volumes\" caps mon = \"allow r fsname=cephfs01\" caps osd = \"allow rw tag cephfs data=cephfs01\"", "ceph auth get CLIENT_NAME > OUTPUT_FILE_NAME scp OUTPUT_FILE_NAME TARGET_NODE_NAME :/etc/ceph", "ceph auth get client.1 > ceph.client.1.keyring exported keyring for client.1 scp ceph.client.1.keyring client:/etc/ceph root@client's password: ceph.client.1.keyring 100% 178 333.0KB/s 00:00", "mkdir PATH_TO_NEW_DIRECTORY_NAME", "mkdir /mnt/mycephfs", "ceph-fuse PATH_TO_NEW_DIRECTORY_NAME -n CEPH_USER_NAME --client-fs=_FILE_SYSTEM_NAME", "ceph-fuse /mnt/mycephfs/ -n client.1 --client-fs=cephfs01 ceph-fuse[555001]: starting ceph client 2022-05-09T07:33:27.158+0000 7f11feb81200 -1 init, newargv = 0x55fc4269d5d0 newargc=15 ceph-fuse[555001]: starting fuse", "ceph osd pool create DATA_POOL_NAME erasure", "ceph osd pool create cephfs-data-ec01 erasure pool 'cephfs-data-ec01' created", "ceph osd lspools", "ceph osd pool set DATA_POOL_NAME allow_ec_overwrites true", "ceph osd pool set cephfs-data-ec01 allow_ec_overwrites true set pool 15 allow_ec_overwrites to true", "ceph fs status FILE_SYSTEM_NAME", "ceph fs status cephfs-ec cephfs-ec - 14 clients ========= RANK STATE MDS ACTIVITY DNS INOS DIRS CAPS 0 active cephfs-ec.example.ooymyq Reqs: 0 /s 8231 8233 891 921 POOL TYPE USED AVAIL cephfs-metadata-ec metadata 787M 8274G cephfs-data-ec data 2360G 12.1T STANDBY MDS cephfs-ec.example.irsrql cephfs-ec.example.cauuaj", "ceph fs add_data_pool FILE_SYSTEM_NAME DATA_POOL_NAME", "ceph fs add_data_pool cephfs-ec cephfs-data-ec01", "ceph fs status FILE_SYSTEM_NAME", "ceph fs status cephfs-ec cephfs-ec - 14 clients ========= RANK STATE MDS ACTIVITY DNS INOS DIRS CAPS 0 active cephfs-ec.example.ooymyq Reqs: 0 /s 8231 8233 891 921 POOL TYPE USED AVAIL cephfs-metadata-ec metadata 787M 8274G cephfs-data-ec data 2360G 12.1T cephfs-data-ec01 data 0 12.1T STANDBY MDS cephfs-ec.example.irsrql cephfs-ec.example.cauuaj", "mkdir PATH_TO_DIRECTORY setfattr -n ceph.dir.layout.pool -v DATA_POOL_NAME PATH_TO_DIRECTORY", "mkdir /mnt/cephfs/newdir setfattr -n ceph.dir.layout.pool -v cephfs-data-ec01 /mnt/cephfs/newdir", "cephadm shell", "ceph fs authorize FILE_SYSTEM_NAME client. CLIENT_NAME / DIRECTORY CAPABILITY [/ DIRECTORY CAPABILITY ] PERMISSIONS", "ceph fs authorize cephfs_a client.1 / r /temp rw client.1 key = AQBSdFhcGZFUDRAAcKhG9Cl2HPiDMMRv4DC43A==", "ceph fs authorize cephfs_a client.1 /temp rw", "ceph auth get client. ID", "ceph auth get client.1 client.1 key = AQBSdFhcGZFUDRAAcKhG9Cl2HPiDMMRv4DC43A== caps mds = \"allow r, allow rw path=/temp\" caps mon = \"allow r\" caps osd = \"allow rw tag cephfs data=cephfs_a\"", "ceph auth get client. ID -o ceph.client. ID .keyring", "ceph auth get client.1 -o ceph.client.1.keyring exported keyring for client.1", "scp /ceph.client. ID .keyring root@ CLIENT_NODE_NAME :/etc/ceph/ceph.client. ID .keyring", "scp /ceph.client.1.keyring root@client01:/etc/ceph/ceph.client.1.keyring", "chmod 644 ceph.client. ID .keyring", "chmod 644 /etc/ceph/ceph.client.1.keyring", "subscription-manager repos --enable=rhceph-6-tools-for-rhel-8-x86_64-rpms", "subscription-manager repos --enable=rhceph-6-tools-for-rhel-9-x86_64-rpms", "dnf install ceph-common", "cephadm shell", "scp /ceph.client. ID .keyring root@ CLIENT_NODE_NAME :/etc/ceph/ceph.client. ID .keyring", "scp /ceph.client.1.keyring root@client01:/etc/ceph/ceph.client.1.keyring", "scp /etc/ceph/ceph.conf root@ CLIENT_NODE_NAME :/etc/ceph/ceph.conf", "scp /etc/ceph/ceph.conf root@client01:/etc/ceph/ceph.conf", "chmod 644 /etc/ceph/ceph.conf", "mkdir -p MOUNT_POINT", "mkdir -p /mnt/cephfs", "mount -t ceph MONITOR-1_NAME :6789, MONITOR-2_NAME :6789, MONITOR-3_NAME :6789:/ MOUNT_POINT -o name= CLIENT_ID ,fs= FILE_SYSTEM_NAME", "mount -t ceph mon1:6789,mon2:6789,mon3:6789:/ /mnt/cephfs -o name=1,fs=cephfs01", "mount -t ceph mon1:6789,mon2:6789,mon3:6789:/ /mnt/cephfs -o nowsync,name=1,fs=cephfs01", "stat -f MOUNT_POINT", "stat -f /mnt/cephfs", "mkdir -p MOUNT_POINT", "mkdir -p /mnt/cephfs", "#DEVICE PATH TYPE OPTIONS MON_0_HOST : PORT , MOUNT_POINT ceph name= CLIENT_ID , MON_1_HOST : PORT , ceph.client_mountpoint=/ VOL / SUB_VOL_GROUP / SUB_VOL / UID_SUB_VOL , fs= FILE_SYSTEM_NAME , MON_2_HOST : PORT :/q[_VOL_]/ SUB_VOL / UID_SUB_VOL , [ ADDITIONAL_OPTIONS ]", "#DEVICE PATH TYPE OPTIONS DUMP FSCK mon1:6789, /mnt/cephfs ceph name=1, 0 0 mon2:6789, ceph.client_mountpoint=/my_vol/my_sub_vol_group/my_sub_vol/0, mon3:6789:/ fs=cephfs01, _netdev,noatime", "subscription-manager repos --enable=6-tools-for-rhel-8-x86_64-rpms", "subscription-manager repos --enable=6-tools-for-rhel-9-x86_64-rpms", "dnf install ceph-fuse", "cephadm shell", "scp /ceph.client. ID .keyring root@ CLIENT_NODE_NAME :/etc/ceph/ceph.client. ID .keyring", "scp /ceph.client.1.keyring root@client01:/etc/ceph/ceph.client.1.keyring", "scp /etc/ceph/ceph.conf root@ CLIENT_NODE_NAME :/etc/ceph/ceph.conf", "scp /etc/ceph/ceph.conf root@client01:/etc/ceph/ceph.conf", "chmod 644 /etc/ceph/ceph.conf", "mkdir PATH_TO_MOUNT_POINT", "mkdir /mnt/mycephfs", "ceph-fuse -n client. CLIENT_ID --client_fs FILE_SYSTEM_NAME MOUNT_POINT", "ceph-fuse -n client.1 --client_fs cephfs01 /mnt/mycephfs", "ceph-fuse -n client.1 --keyring=/etc/ceph/client.1.keyring /mnt/mycephfs", "ceph-fuse -n client. CLIENT_ID MOUNT_POINT -r PATH", "ceph-fuse -n client.1 /mnt/cephfs -r /home/cephfs", "ceph-fuse -n client.1 /mnt/cephfs --client_reconnect_stale=true", "stat -f MOUNT_POINT", "stat -f /mnt/cephfs", "mkdir PATH_TO_MOUNT_POINT", "mkdir /mnt/mycephfs", "#DEVICE PATH TYPE OPTIONS DUMP FSCK HOST_NAME : PORT , MOUNT_POINT fuse.ceph ceph.id= CLIENT_ID , 0 0 HOST_NAME : PORT , ceph.client_mountpoint=/ VOL / SUB_VOL_GROUP / SUB_VOL / UID_SUB_VOL , HOST_NAME : PORT :/ ceph.client_fs= FILE_SYSTEM_NAME ,ceph.name= USERNAME ,ceph.keyring=/etc/ceph/ KEYRING_FILE , [ ADDITIONAL_OPTIONS ]", "#DEVICE PATH TYPE OPTIONS DUMP FSCK mon1:6789, /mnt/mycephfs fuse.ceph ceph.id=1, 0 0 mon2:6789, ceph.client_mountpoint=/my_vol/my_sub_vol_group/my_sub_vol/0, mon3:6789:/ ceph.client_fs=cephfs01,ceph.name=client.1,ceph.keyring=/etc/ceph/client1.keyring, _netdev,defaults" ]	https://docs.redhat.com/en/documentation/red_hat_ceph_storage/6/html/file_system_guide/deployment-of-the-ceph-file-system
Chapter 3. Generating API keys to automate the functional certification processes	Chapter 3. Generating API keys to automate the functional certification processes A valid Pyxis API key is a token used to access partner-specific certification data through the REST API. With this key, you can directly access your certification components available in the Red Hat Partner Certification tool and seamlessly upload certification results without the need for repeated authentication. Note API keys are tied to specific Organization IDs, allowing access only to the product listings associated with that particular organization. Prerequisites Have access to the Red Hat Partner Certification tool. A valid component ID for your certification components on the Red Hat Partner Certification tool. Procedure Follow the procedure to generate the API keys: After logging in to the Red Hat Partner Certification tool, go to the Certification management tab. From the Resources listing, click API keys . The API Keys page opens. Click Add API key . The Add API Keys dialog opens. Enter a unique key in the Name text box. Enter a brief description about the newly created key including its purpose in the Description text box. Click Confirm . A new token is generated. The Copy Token wizard opens, allowing you to copy the generated API key. Click the copy icon to the generated API key to save it in a secured location. Important Red Hat doesn't store your API keys. If you don't save the key now, you can't retrieve it after closing this wizard. Verification The new API key is listed on the API Keys page including the following details: Name Description User Name Created Time Actions - Click Revoke , to delete the key.	null	https://docs.redhat.com/en/documentation/red_hat_software_certification/2025/html/red_hat_software_certification_workflow_guide/generating-api-keys-to-automate-the-functional-certification-processes_openshift-sw-cert-workflow-onboarding-certification-partners
Chapter 30. High Availability Using Server Hinting	Chapter 30. High Availability Using Server Hinting In Red Hat JBoss Data Grid, Server Hinting ensures that backed up copies of data are not stored on the same physical server, rack, or data center as the original. Server Hinting does not apply to total replication because total replication mandates complete replicas on every server, rack, and data center. Data distribution across nodes is controlled by the Consistent Hashing mechanism. JBoss Data Grid offers a pluggable policy to specify the consistent hashing algorithm. For details see Section 30.4, "ConsistentHashFactories" Setting a machineId , rackId , or siteId in the transport configuration will trigger the use of TopologyAwareConsistentHashFactory , which is the equivalent of the DefaultConsistentHashFactory with Server Hinting enabled. Server Hinting is particularly important when ensuring the high availability of your JBoss Data Grid implementation. Report a bug 30.1. Establishing Server Hinting with JGroups When setting up a clustered environment in Red Hat JBoss Data Grid, Server Hinting is configured when establishing JGroups configuration. JBoss Data Grid ships with several JGroups files pre-configured for clustered mode. These files can be used as a starting point when configuring Server Hinting in JBoss Data Grid. See Also: Section 26.2.2, "Pre-Configured JGroups Files" Report a bug	null	https://docs.redhat.com/en/documentation/red_hat_data_grid/6.6/html/administration_and_configuration_guide/chap-High_Availability_Using_Server_Hinting
Appendix A. General configuration options	Appendix A. General configuration options These are the general configuration options for Ceph. Note Typically, these will be set automatically by deployment tools, such as cephadm . fsid Description The file system ID. One per cluster. Type UUID Required No. Default N/A. Usually generated by deployment tools. admin_socket Description The socket for executing administrative commands on a daemon, irrespective of whether Ceph monitors have established a quorum. Type String Required No Default /var/run/ceph/USDcluster-USDname.asok pid_file Description The file in which the monitor or OSD will write its PID. For instance, /var/run/USDcluster/USDtype.USDid.pid will create /var/run/ceph/mon.a.pid for the mon with id a running in the ceph cluster. The pid file is removed when the daemon stops gracefully. If the process is not daemonized (meaning it runs with the -f or -d option), the pid file is not created. Type String Required No Default No chdir Description The directory Ceph daemons change to once they are up and running. Default / directory recommended. Type String Required No Default / max_open_files Description If set, when the Red Hat Ceph Storage cluster starts, Ceph sets the max_open_fds at the OS level (that is, the max # of file descriptors). It helps prevent Ceph OSDs from running out of file descriptors. Type 64-bit Integer Required No Default 0 fatal_signal_handlers Description If set, we will install signal handlers for SEGV, ABRT, BUS, ILL, FPE, XCPU, XFSZ, SYS signals to generate a useful log message. Type Boolean Default true	null	https://docs.redhat.com/en/documentation/red_hat_ceph_storage/6/html/configuration_guide/general-configuration-options_conf
5.261. python-rhsm	5.261. python-rhsm 5.261.1. RHBA-2012:0805 - python-rhsm bug fix and enhancement update Updated python-rhsm packages that fix several bugs and add one enhancement are now available for Red Hat Enterprise Linux 6. The python-rhsm package contains a library for communicating with the representational state transfer (REST) interface of Red Hat's subscription and content service. This interface is used by the Subscription Management tools for management of system entitlements, certificates, and access to content. Bug Fixes BZ# 720372 Previously, Subscription Manager had the fakamai-cp1.pem certificate installed in the /etc/rhsm/ca/fakamai-cp1.pem directory after installation. However, the certificate serves only for testing purposes and is not needed by the tool itself. With this update, the certificate has been removed. BZ# 744654 If the subscription-manager command was issued with an incorrect or empty --server.port option, the command failed with a traceback. With this update, the tool now sets the provided port value as expected and no traceback is returned. BZ# 803773 If the activation key contained non-ASCII characters, the registration failed with the following error: This happened due to an incorrect conversion of the key into the URL address. With this update, subscription-manager converts the characters correctly and the registration succeeds in the scenario described. BZ# 807721 Several configuration settings had no default value defined in the Red Hat Subscription Manager (RHSM), which could cause some commands to return a traceback. The default RHSM values are now set as expected and the problem no longer occurs. BZ# 822965 When the user defined a proxy server in rhsm.conf, the Subscription Manager did not work and returned the "unknown URL type" error. This happened because the "Host" header was not sent up to the CDN when acquiring the list of releases using a proxy. With this update, the "Host" header is sent to the CDN and the proxy definition in rhsm.conf is processed as expected. Enhancement BZ# 785247 The bug fixes and some of the new features introduced in the python-rhsm package on Red Hat Enterprise Linux 5.8 have been backported into the python-rhsm on Red Hat Enterprise Linux 6.3. All users of python-rhsm are advised to upgrade to these updated packages, which fix these bugs and add this enhancement.	[ "Network error. Please check the connection details, or see /var/log/rhsm/rhsm.log for more information." ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.3_technical_notes/python-rhsm
Chapter 1. Release schedule	Chapter 1. Release schedule The following table lists the dates of the Red Hat OpenStack Platform 17.1 GA, along with the dates of each subsequent asynchronous release for core components: Table 1.1. Red Hat OpenStack Platform 17.1 core component release schedule Release Date 17.1.0 (General Availability) 17 August, 2023	null	https://docs.redhat.com/en/documentation/red_hat_openstack_platform/17.1/html/package_manifest/ch01
Chapter 15. URL Handlers	Chapter 15. URL Handlers There are many contexts in Red Hat Fuse where you need to provide a URL to specify the location of a resource (for example, as the argument to a console command). In general, when specifying a URL, you can use any of the schemes supported by Fuse's built-in URL handlers. This appendix describes the syntax for all of the available URL handlers. 15.1. File URL Handler 15.1.1. Syntax A file URL has the syntax, file: PathName , where PathName is the relative or absolute pathname of a file that is available on the Classpath. The provided PathName is parsed by Java's built-in file URL handler . Hence, the PathName syntax is subject to the usual conventions of a Java pathname: in particular, on Windows, each backslash must either be escaped by another backslash or replaced by a forward slash. 15.1.2. Examples For example, consider the pathname, C:\Projects\camel-bundle\target\foo-1.0-SNAPSHOT.jar , on Windows. The following example shows the correct alternatives for the file URL on Windows: The following example shows some incorrect alternatives for the file URL on Windows: 15.2. HTTP URL Handler 15.2.1. Syntax A HTTP URL has the standard syntax, http: Host [: Port ]/[ Path ][# AnchorName ][? Query ] . You can also specify a secure HTTP URL using the https scheme. The provided HTTP URL is parsed by Java's built-in HTTP URL handler, so the HTTP URL behaves in the normal way for a Java application. 15.3. Mvn URL Handler 15.3.1. Overview If you use Maven to build your bundles or if you know that a particular bundle is available from a Maven repository, you can use the Mvn handler scheme to locate the bundle. Note To ensure that the Mvn URL handler can find local and remote Maven artifacts, you might find it necessary to customize the Mvn URL handler configuration. For details, see Section 15.3.5, "Configuring the Mvn URL handler" . 15.3.2. Syntax An Mvn URL has the following syntax: Where repositoryUrl optionally specifies the URL of a Maven repository. The groupId , artifactId , version , packaging , and classifier are the standard Maven coordinates for locating Maven artifacts. 15.3.3. Omitting coordinates When specifying an Mvn URL, only the groupId and the artifactId coordinates are required. The following examples reference a Maven bundle with the groupId , org.fusesource.example , and with the artifactId , bundle-demo : When the version is omitted, as in the first example, it defaults to LATEST , which resolves to the latest version based on the available Maven metadata. In order to specify a classifier value without specifying a packaging or a version value, it is permissible to leave gaps in the Mvn URL. Likewise, if you want to specify a packaging value without a version value. For example: 15.3.4. Specifying a version range When specifying the version value in an Mvn URL, you can specify a version range (using standard Maven version range syntax) in place of a simple version number. You use square brackets- [ and ] -to denote inclusive ranges and parentheses- ( and ) -to denote exclusive ranges. For example, the range, [1.0.4,2.0) , matches any version, v , that satisfies 1.0.4 ⇐ v < 2.0 . You can use this version range in an Mvn URL as follows: 15.3.5. Configuring the Mvn URL handler Before using Mvn URLs for the first time, you might need to customize the Mvn URL handler settings, as follows: Section 15.3.6, "Check the Mvn URL settings" . Section 15.3.7, "Edit the configuration file" . Section 15.3.8, "Customize the location of the local repository" . 15.3.6. Check the Mvn URL settings The Mvn URL handler resolves a reference to a local Maven repository and maintains a list of remote Maven repositories. When resolving an Mvn URL, the handler searches first the local repository and then the remote repositories in order to locate the specified Maven artifiact. If there is a problem with resolving an Mvn URL, the first thing you should do is to check the handler settings to see which local repository and remote repositories it is using to resolve URLs. To check the Mvn URL settings, enter the following commands at the console: The config:edit command switches the focus of the config utility to the properties belonging to the org.ops4j.pax.url.mvn persistent ID. The config:proplist command outputs all of the property settings for the current persistent ID. With the focus on org.ops4j.pax.url.mvn , you should see a listing similar to the following: Where the localRepository setting shows the local repository location currently used by the handler and the repositories setting shows the remote repository list currently used by the handler. 15.3.7. Edit the configuration file To customize the property settings for the Mvn URL handler, edit the following configuration file: The settings in this file enable you to specify explicitly the location of the local Maven repository, remove Maven repositories, Maven proxy server settings, and more. Please see the comments in the configuration file for more details about these settings. 15.3.8. Customize the location of the local repository In particular, if your local Maven repository is in a non-default location, you might find it necessary to configure it explicitly in order to access Maven artifacts that you build locally. In your org.ops4j.pax.url.mvn.cfg configuration file, uncomment the org.ops4j.pax.url.mvn.localRepository property and set it to the location of your local Maven repository. For example: 15.3.9. Reference For more details about the mvn URL syntax, see the original Pax URL Mvn Protocol documentation. 15.4. Wrap URL Handler 15.4.1. Overview If you need to reference a JAR file that is not already packaged as a bundle, you can use the Wrap URL handler to convert it dynamically. The implementation of the Wrap URL handler is based on Peter Krien's open source Bnd utility. 15.4.2. Syntax A Wrap URL has the following syntax: The locationURL can be any URL that locates a JAR (where the referenced JAR is not formatted as a bundle). The optional instructionsURL references a Bnd properties file that specifies how the bundle conversion is performed. The optional instructions is an ampersand, & , delimited list of Bnd properties that specify how the bundle conversion is performed. 15.4.3. Default instructions In most cases, the default Bnd instructions are adequate for wrapping an API JAR file. By default, Wrap adds manifest headers to the JAR's META-INF/Manifest.mf file as shown in Table 15.1, "Default Instructions for Wrapping a JAR" . Table 15.1. Default Instructions for Wrapping a JAR Manifest Header Default Value Import-Package ;resolution:=optional Export-Package All packages from the wrapped JAR. Bundle-SymbolicName The name of the JAR file, where any characters not in the set [a-zA-Z0-9_-] are replaced by underscore, _ . 15.4.4. Examples The following Wrap URL locates version 1.1 of the commons-logging JAR in a Maven repository and converts it to an OSGi bundle using the default Bnd properties: The following Wrap URL uses the Bnd properties from the file, E:\Data\Examples\commons-logging-1.1.bnd : The following Wrap URL specifies the Bundle-SymbolicName property and the Bundle-Version property explicitly: If the preceding URL is used as a command-line argument, it might be necessary to escape the dollar sign, \USD , to prevent it from being processed by the command line, as follows: 15.4.5. Reference For more details about the wrap URL handler, see the following references: The Bnd tool documentation , for more details about Bnd properties and Bnd instruction files. The original Pax URL Wrap Protocol documentation. 15.5. War URL Handler 15.5.1. Overview If you need to deploy a WAR file in an OSGi container, you can automatically add the requisite manifest headers to the WAR file by prefixing the WAR URL with war: , as described here. 15.5.2. Syntax A War URL is specified using either of the following syntaxes: The first syntax, using the war scheme, specifies a WAR file that is converted into a bundle using the default instructions. The warURL can be any URL that locates a WAR file. The second syntax, using the warref scheme, specifies a Bnd properties file, instructionsURL , that contains the conversion instructions (including some instructions that are specific to this handler). In this syntax, the location of the referenced WAR file does not appear explicitly in the URL. The WAR file is specified instead by the (mandatory) WAR-URL property in the properties file. 15.5.3. WAR-specific properties/instructions Some of the properties in the .bnd instructions file are specific to the War URL handler, as follows: WAR-URL (Mandatory) Specifies the location of the War file that is to be converted into a bundle. Web-ContextPath Specifies the piece of the URL path that is used to access this Web application, after it has been deployed inside the Web container. Note Earlier versions of PAX Web used the property, Webapp-Context , which is now deprecated . 15.5.4. Default instructions By default, the War URL handler adds manifest headers to the WAR's META-INF/Manifest.mf file as shown in Table 15.2, "Default Instructions for Wrapping a WAR File" . Table 15.2. Default Instructions for Wrapping a WAR File Manifest Header Default Value Import-Package javax. ,org.xml. ,org.w3c. Export-Package No packages are exported. Bundle-SymbolicName The name of the WAR file, where any characters not in the set [a-zA-Z0-9_-\.] are replaced by period, . . Web-ContextPath No default value. But the WAR extender will use the value of Bundle-SymbolicName by default. Bundle-ClassPath In addition to any class path entries specified explicitly, the following entries are added automatically: . WEB-INF/classes All of the JARs from the WEB-INF/lib directory. 15.5.5. Examples The following War URL locates version 1.4.7 of the wicket-examples WAR in a Maven repository and converts it to an OSGi bundle using the default instructions: The following Wrap URL specifies the Web-ContextPath explicitly: The following War URL converts the WAR file referenced by the WAR-URL property in the wicket-examples-1.4.7.bnd file and then converts the WAR into an OSGi bundle using the other instructions in the .bnd file: 15.5.6. Reference For more details about the war URL syntax, see the original Pax URL War Protocol documentation.	[ "file:C:/Projects/camel-bundle/target/foo-1.0-SNAPSHOT.jar file:C:\\\\Projects\\\\camel-bundle\\\\target\\\\foo-1.0-SNAPSHOT.jar", "file:C:\\Projects\\camel-bundle\\target\\foo-1.0-SNAPSHOT.jar // WRONG! file://C:/Projects/camel-bundle/target/foo-1.0-SNAPSHOT.jar // WRONG! file://C:\\\\Projects\\\\camel-bundle\\\\target\\\\foo-1.0-SNAPSHOT.jar // WRONG!", "mvn:[ repositoryUrl !] groupId / artifactId [/[ version ][/[ packaging ][/[ classifier ]]]]", "mvn:org.fusesource.example/bundle-demo mvn:org.fusesource.example/bundle-demo/1.1", "mvn: groupId / artifactId /// classifier mvn: groupId / artifactId / version // classifier mvn: groupId / artifactId // packaging / classifier mvn: groupId / artifactId // packaging", "mvn:org.fusesource.example/bundle-demo/[1.0.4,2.0)", "JBossFuse:karaf@root> config:edit org.ops4j.pax.url.mvn JBossFuse:karaf@root> config:proplist", "org.ops4j.pax.url.mvn.defaultRepositories = file:/path/to/JBossFuse/jboss-fuse-7.13.0.fuse-7_13_0-00012-redhat-00001/system@snapshots@id=karaf.system,file:/home/userid/.m2/repository@snapshots@id=local,file:/path/to/JBossFuse/jboss-fuse-7.13.0.fuse-7_13_0-00012-redhat-00001/local-repo@snapshots@id=karaf.local-repo,file:/path/to/JBossFuse/jboss-fuse-7.13.0.fuse-7_13_0-00012-redhat-00001/system@snapshots@id=child.karaf.system org.ops4j.pax.url.mvn.globalChecksumPolicy = warn org.ops4j.pax.url.mvn.globalUpdatePolicy = daily org.ops4j.pax.url.mvn.localRepository = /path/to/JBossFuse/jboss-fuse-7.13.0.fuse-7_13_0-00012-redhat-00001/data/repository org.ops4j.pax.url.mvn.repositories = http://repo1.maven.org/maven2@id=maven.central.repo, https://maven.repository.redhat.com/ga@id=redhat.ga.repo, https://maven.repository.redhat.com/earlyaccess/all@id=redhat.ea.repo, https://repository.jboss.org/nexus/content/groups/ea@id=fuseearlyaccess org.ops4j.pax.url.mvn.settings = /path/to/jboss-fuse-7.13.0.fuse-7_13_0-00012-redhat-00001/etc/maven-settings.xml org.ops4j.pax.url.mvn.useFallbackRepositories = false service.pid = org.ops4j.pax.url.mvn", "InstallDir /etc/org.ops4j.pax.url.mvn.cfg", "Path to the local maven repository which is used to avoid downloading artifacts when they already exist locally. The value of this property will be extracted from the settings.xml file above, or defaulted to: System.getProperty( \"user.home\" ) + \"/.m2/repository\" # org.ops4j.pax.url.mvn.localRepository=file:E:/Data/.m2/repository", "wrap: locationURL [, instructionsURL ][USD instructions ]", "wrap:mvn:commons-logging/commons-logging/1.1", "wrap:mvn:commons-logging/commons-logging/1.1,file:E:/Data/Examples/commons-logging-1.1.bnd", "wrap:mvn:commons-logging/commons-logging/1.1USDBundle-SymbolicName=apache-comm-log&Bundle-Version=1.1", "wrap:mvn:commons-logging/commons-logging/1.1\\USDBundle-SymbolicName=apache-comm-log&Bundle-Version=1.1", "war: warURL warref: instructionsURL", "war:mvn:org.apache.wicket/wicket-examples/1.4.7/war", "war:mvn:org.apache.wicket/wicket-examples/1.4.7/war?Web-ContextPath=wicket", "warref:file:E:/Data/Examples/wicket-examples-1.4.7.bnd" ]	https://docs.redhat.com/en/documentation/red_hat_fuse/7.13/html/deploying_into_apache_karaf/urlhandlers
Chapter 13. Finding and cleaning stale subvolumes (Technology Preview)	Chapter 13. Finding and cleaning stale subvolumes (Technology Preview) Sometimes stale subvolumes don't have a respective k8s reference attached. These subvolumes are of no use and can be deleted. You can find and delete stale subvolumes using the ODF CLI tool. Important Deleting stale subvolumes using the ODF CLI tool is a Technology Preview feature. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information, see Technology Preview Features Support Scope . Prerequisites Download the OpenShift Data Foundation command line interface (CLI) tool. With the Data Foundation CLI tool, you can effectively manage and troubleshoot your Data Foundation environment from a terminal. You can find a compatible version and download the CLI tool from the customer portal . Procedure Find the stale subvolumes by using the --stale flag with the subvolumes command: Example output: Delete the stale subvolumes: Replace <subvolumes> with a comma separated list of subvolumes from the output of the first command. The subvolumes must be of the same filesystem and subvolumegroup. Replace <filesystem> and <subvolumegroup> with the filesystem and subvolumegroup from the output of the first command. For example: Example output:	[ "odf subvolume ls --stale", "Filesystem Subvolume Subvolumegroup State ocs-storagecluster-cephfilesystem csi-vol-427774b4-340b-11ed-8d66-0242ac110004 csi stale ocs-storagecluster-cephfilesystem csi-vol-427774b4-340b-11ed-8d66-0242ac110005 csi stale", "odf subvolume delete <subvolumes> <filesystem> <subvolumegroup>", "odf subvolume delete csi-vol-427774b4-340b-11ed-8d66-0242ac110004,csi-vol-427774b4-340b-11ed-8d66-0242ac110005 ocs-storagecluster csi", "Info: subvolume csi-vol-427774b4-340b-11ed-8d66-0242ac110004 deleted Info: subvolume csi-vol-427774b4-340b-11ed-8d66-0242ac110004 deleted" ]	https://docs.redhat.com/en/documentation/red_hat_openshift_data_foundation/4.18/html/managing_and_allocating_storage_resources/finding-and-cleaning-subvolumes_rhodf
Chapter 2. Creating a mirror registry with mirror registry for Red Hat OpenShift	Chapter 2. Creating a mirror registry with mirror registry for Red Hat OpenShift The mirror registry for Red Hat OpenShift is a small and streamlined container registry that you can use as a target for mirroring the required container images of OpenShift Container Platform for disconnected installations. If you already have a container image registry, such as Red Hat Quay, you can skip this section and go straight to Mirroring the OpenShift Container Platform image repository . 2.1. Prerequisites An OpenShift Container Platform subscription. Red Hat Enterprise Linux (RHEL) 8 and 9 with Podman 3.4.2 or later and OpenSSL installed. Fully qualified domain name for the Red Hat Quay service, which must resolve through a DNS server. Key-based SSH connectivity on the target host. SSH keys are automatically generated for local installs. For remote hosts, you must generate your own SSH keys. 2 or more vCPUs. 8 GB of RAM. About 12 GB for OpenShift Container Platform 4.14 release images, or about 358 GB for OpenShift Container Platform 4.14 release images and OpenShift Container Platform 4.14 Red Hat Operator images. Up to 1 TB per stream or more is suggested. Important These requirements are based on local testing results with only release images and Operator images. Storage requirements can vary based on your organization's needs. You might require more space, for example, when you mirror multiple z-streams. You can use standard Red Hat Quay functionality or the proper API callout to remove unnecessary images and free up space. 2.2. Mirror registry for Red Hat OpenShift introduction For disconnected deployments of OpenShift Container Platform, a container registry is required to carry out the installation of the clusters. To run a production-grade registry service on such a cluster, you must create a separate registry deployment to install the first cluster. The mirror registry for Red Hat OpenShift addresses this need and is included in every OpenShift subscription. It is available for download on the OpenShift console Downloads page. The mirror registry for Red Hat OpenShift allows users to install a small-scale version of Red Hat Quay and its required components using the mirror-registry command line interface (CLI) tool. The mirror registry for Red Hat OpenShift is deployed automatically with preconfigured local storage and a local database. It also includes auto-generated user credentials and access permissions with a single set of inputs and no additional configuration choices to get started. The mirror registry for Red Hat OpenShift provides a pre-determined network configuration and reports deployed component credentials and access URLs upon success. A limited set of optional configuration inputs like fully qualified domain name (FQDN) services, superuser name and password, and custom TLS certificates are also provided. This provides users with a container registry so that they can easily create an offline mirror of all OpenShift Container Platform release content when running OpenShift Container Platform in restricted network environments. Use of the mirror registry for Red Hat OpenShift is optional if another container registry is already available in the install environment. 2.2.1. Mirror registry for Red Hat OpenShift limitations The following limitations apply to the mirror registry for Red Hat OpenShift : The mirror registry for Red Hat OpenShift is not a highly-available registry and only local file system storage is supported. It is not intended to replace Red Hat Quay or the internal image registry for OpenShift Container Platform. The mirror registry for Red Hat OpenShift is not intended to be a substitute for a production deployment of Red Hat Quay. The mirror registry for Red Hat OpenShift is only supported for hosting images that are required to install a disconnected OpenShift Container Platform cluster, such as Release images or Red Hat Operator images. It uses local storage on your Red Hat Enterprise Linux (RHEL) machine, and storage supported by RHEL is supported by the mirror registry for Red Hat OpenShift . Note Because the mirror registry for Red Hat OpenShift uses local storage, you should remain aware of the storage usage consumed when mirroring images and use Red Hat Quay's garbage collection feature to mitigate potential issues. For more information about this feature, see "Red Hat Quay garbage collection". Support for Red Hat product images that are pushed to the mirror registry for Red Hat OpenShift for bootstrapping purposes are covered by valid subscriptions for each respective product. A list of exceptions to further enable the bootstrap experience can be found on the Self-managed Red Hat OpenShift sizing and subscription guide . Content built by customers should not be hosted by the mirror registry for Red Hat OpenShift . Using the mirror registry for Red Hat OpenShift with more than one cluster is discouraged because multiple clusters can create a single point of failure when updating your cluster fleet. It is advised to leverage the mirror registry for Red Hat OpenShift to install a cluster that can host a production-grade, highly-available registry such as Red Hat Quay, which can serve OpenShift Container Platform content to other clusters. 2.3. Mirroring on a local host with mirror registry for Red Hat OpenShift This procedure explains how to install the mirror registry for Red Hat OpenShift on a local host using the mirror-registry installer tool. By doing so, users can create a local host registry running on port 443 for the purpose of storing a mirror of OpenShift Container Platform images. Note Installing the mirror registry for Red Hat OpenShift using the mirror-registry CLI tool makes several changes to your machine. After installation, a USDHOME/quay-install directory is created, which has installation files, local storage, and the configuration bundle. Trusted SSH keys are generated in case the deployment target is the local host, and systemd files on the host machine are set up to ensure that container runtimes are persistent. Additionally, an initial user named init is created with an automatically generated password. All access credentials are printed at the end of the install routine. Procedure Download the mirror-registry.tar.gz package for the latest version of the mirror registry for Red Hat OpenShift found on the OpenShift console Downloads page. Install the mirror registry for Red Hat OpenShift on your local host with your current user account by using the mirror-registry tool. For a full list of available flags, see "mirror registry for Red Hat OpenShift flags". USD ./mirror-registry install \ --quayHostname <host_example_com> \ --quayRoot <example_directory_name> Use the user name and password generated during installation to log into the registry by running the following command: USD podman login -u init \ -p <password> \ <host_example_com>:8443> \ --tls-verify=false 1 1 You can avoid running --tls-verify=false by configuring your system to trust the generated rootCA certificates. See "Using SSL to protect connections to Red Hat Quay" and "Configuring the system to trust the certificate authority" for more information. Note You can also log in by accessing the UI at https://<host.example.com>:8443 after installation. You can mirror OpenShift Container Platform images after logging in. Depending on your needs, see either the "Mirroring the OpenShift Container Platform image repository" or the "Mirroring Operator catalogs for use with disconnected clusters" sections of this document. Note If there are issues with images stored by the mirror registry for Red Hat OpenShift due to storage layer problems, you can remirror the OpenShift Container Platform images, or reinstall mirror registry on more stable storage. 2.4. Updating mirror registry for Red Hat OpenShift from a local host This procedure explains how to update the mirror registry for Red Hat OpenShift from a local host using the upgrade command. Updating to the latest version ensures new features, bug fixes, and security vulnerability fixes. Important When upgrading from version 1 to version 2, be aware of the following constraints: The worker count is set to 1 because multiple writes are not allowed in SQLite. You must not use the mirror registry for Red Hat OpenShift user interface (UP). Do not access the sqlite-storage Podman volume during the upgrade. There is intermittent downtime of your mirror registry because it is restarted during the upgrade process. PostgreSQL data is backed up under the /USDHOME/quay-instal/quay-postgres-backup/ directory for recovery. Prerequisites You have installed the mirror registry for Red Hat OpenShift on a local host. Procedure If you are upgrading the mirror registry for Red Hat OpenShift from 1.3 2.y, and your installation directory is the default at /etc/quay-install , you can enter the following command: USD sudo ./mirror-registry upgrade -v Note mirror registry for Red Hat OpenShift migrates Podman volumes for Quay storage, Postgres data, and /etc/quay-install data to the new USDHOME/quay-install location. This allows you to use mirror registry for Red Hat OpenShift without the --quayRoot flag during future upgrades. Users who upgrade mirror registry for Red Hat OpenShift with the ./mirror-registry upgrade -v flag must include the same credentials used when creating their mirror registry. For example, if you installed the mirror registry for Red Hat OpenShift with --quayHostname <host_example_com> and --quayRoot <example_directory_name> , you must include that string to properly upgrade the mirror registry. If you are upgrading the mirror registry for Red Hat OpenShift from 1.3 2.y and you used a custom quay configuration and storage directory in your 1.y deployment, you must pass in the --quayRoot and --quayStorage flags. For example: USD sudo ./mirror-registry upgrade --quayHostname <host_example_com> --quayRoot <example_directory_name> --quayStorage <example_directory_name>/quay-storage -v If you are upgrading the mirror registry for Red Hat OpenShift from 1.3 2.y and want to specify a custom SQLite storage path, you must pass in the --sqliteStorage flag, for example: USD sudo ./mirror-registry upgrade --sqliteStorage <example_directory_name>/sqlite-storage -v 2.5. Mirroring on a remote host with mirror registry for Red Hat OpenShift This procedure explains how to install the mirror registry for Red Hat OpenShift on a remote host using the mirror-registry tool. By doing so, users can create a registry to hold a mirror of OpenShift Container Platform images. Note Installing the mirror registry for Red Hat OpenShift using the mirror-registry CLI tool makes several changes to your machine. After installation, a USDHOME/quay-install directory is created, which has installation files, local storage, and the configuration bundle. Trusted SSH keys are generated in case the deployment target is the local host, and systemd files on the host machine are set up to ensure that container runtimes are persistent. Additionally, an initial user named init is created with an automatically generated password. All access credentials are printed at the end of the install routine. Procedure Download the mirror-registry.tar.gz package for the latest version of the mirror registry for Red Hat OpenShift found on the OpenShift console Downloads page. Install the mirror registry for Red Hat OpenShift on your local host with your current user account by using the mirror-registry tool. For a full list of available flags, see "mirror registry for Red Hat OpenShift flags". USD ./mirror-registry install -v \ --targetHostname <host_example_com> \ --targetUsername <example_user> \ -k ~/.ssh/my_ssh_key \ --quayHostname <host_example_com> \ --quayRoot <example_directory_name> Use the user name and password generated during installation to log into the mirror registry by running the following command: USD podman login -u init \ -p <password> \ <host_example_com>:8443> \ --tls-verify=false 1 1 You can avoid running --tls-verify=false by configuring your system to trust the generated rootCA certificates. See "Using SSL to protect connections to Red Hat Quay" and "Configuring the system to trust the certificate authority" for more information. Note You can also log in by accessing the UI at https://<host.example.com>:8443 after installation. You can mirror OpenShift Container Platform images after logging in. Depending on your needs, see either the "Mirroring the OpenShift Container Platform image repository" or the "Mirroring Operator catalogs for use with disconnected clusters" sections of this document. Note If there are issues with images stored by the mirror registry for Red Hat OpenShift due to storage layer problems, you can remirror the OpenShift Container Platform images, or reinstall mirror registry on more stable storage. 2.6. Updating mirror registry for Red Hat OpenShift from a remote host This procedure explains how to update the mirror registry for Red Hat OpenShift from a remote host using the upgrade command. Updating to the latest version ensures bug fixes and security vulnerability fixes. Important When upgrading from version 1 to version 2, be aware of the following constraints: The worker count is set to 1 because multiple writes are not allowed in SQLite. You must not use the mirror registry for Red Hat OpenShift user interface (UP). Do not access the sqlite-storage Podman volume during the upgrade. There is intermittent downtime of your mirror registry because it is restarted during the upgrade process. PostgreSQL data is backed up under the /USDHOME/quay-instal/quay-postgres-backup/ directory for recovery. Prerequisites You have installed the mirror registry for Red Hat OpenShift on a remote host. Procedure To upgrade the mirror registry for Red Hat OpenShift from a remote host, enter the following command: USD ./mirror-registry upgrade -v --targetHostname <remote_host_url> --targetUsername <user_name> -k ~/.ssh/my_ssh_key Note Users who upgrade the mirror registry for Red Hat OpenShift with the ./mirror-registry upgrade -v flag must include the same credentials used when creating their mirror registry. For example, if you installed the mirror registry for Red Hat OpenShift with --quayHostname <host_example_com> and --quayRoot <example_directory_name> , you must include that string to properly upgrade the mirror registry. If you are upgrading the mirror registry for Red Hat OpenShift from 1.3 2.y and want to specify a custom SQLite storage path, you must pass in the --sqliteStorage flag, for example: USD ./mirror-registry upgrade -v --targetHostname <remote_host_url> --targetUsername <user_name> -k ~/.ssh/my_ssh_key --sqliteStorage <example_directory_name>/quay-storage 2.7. Replacing mirror registry for Red Hat OpenShift SSL/TLS certificates In some cases, you might want to update your SSL/TLS certificates for the mirror registry for Red Hat OpenShift . This is useful in the following scenarios: If you are replacing the current mirror registry for Red Hat OpenShift certificate. If you are using the same certificate as the mirror registry for Red Hat OpenShift installation. If you are periodically updating the mirror registry for Red Hat OpenShift certificate. Use the following procedure to replace mirror registry for Red Hat OpenShift SSL/TLS certificates. Prerequisites You have downloaded the ./mirror-registry binary from the OpenShift console Downloads page. Procedure Enter the following command to install the mirror registry for Red Hat OpenShift : USD ./mirror-registry install \ --quayHostname <host_example_com> \ --quayRoot <example_directory_name> This installs the mirror registry for Red Hat OpenShift to the USDHOME/quay-install directory. Prepare a new certificate authority (CA) bundle and generate new ssl.key and ssl.crt key files. For more information, see Using SSL/TLS to protect connections to Red Hat Quay . Assign /USDHOME/quay-install an environment variable, for example, QUAY , by entering the following command: USD export QUAY=/USDHOME/quay-install Copy the new ssl.crt file to the /USDHOME/quay-install directory by entering the following command: USD cp ~/ssl.crt USDQUAY/quay-config Copy the new ssl.key file to the /USDHOME/quay-install directory by entering the following command: USD cp ~/ssl.key USDQUAY/quay-config Restart the quay-app application pod by entering the following command: USD systemctl --user restart quay-app 2.8. Uninstalling the mirror registry for Red Hat OpenShift You can uninstall the mirror registry for Red Hat OpenShift from your local host by running the following command: USD ./mirror-registry uninstall -v \ --quayRoot <example_directory_name> Note Deleting the mirror registry for Red Hat OpenShift will prompt the user before deletion. You can use --autoApprove to skip this prompt. Users who install the mirror registry for Red Hat OpenShift with the --quayRoot flag must include the --quayRoot flag when uninstalling. For example, if you installed the mirror registry for Red Hat OpenShift with --quayRoot example_directory_name , you must include that string to properly uninstall the mirror registry. 2.9. Mirror registry for Red Hat OpenShift flags The following flags are available for the mirror registry for Red Hat OpenShift : Flags Description --autoApprove A boolean value that disables interactive prompts. If set to true , the quayRoot directory is automatically deleted when uninstalling the mirror registry. Defaults to false if left unspecified. --initPassword The password of the init user created during Quay installation. Must be at least eight characters and contain no whitespace. --initUser string Shows the username of the initial user. Defaults to init if left unspecified. --no-color , -c Allows users to disable color sequences and propagate that to Ansible when running install, uninstall, and upgrade commands. --quayHostname The fully-qualified domain name of the mirror registry that clients will use to contact the registry. Equivalent to SERVER_HOSTNAME in the Quay config.yaml . Must resolve by DNS. Defaults to <targetHostname>:8443 if left unspecified. [1] --quayStorage The folder where Quay persistent storage data is saved. Defaults to the quay-storage Podman volume. Root privileges are required to uninstall. --quayRoot , -r The directory where container image layer and configuration data is saved, including rootCA.key , rootCA.pem , and rootCA.srl certificates. Defaults to USDHOME/quay-install if left unspecified. --sqliteStorage The folder where SQLite database data is saved. Defaults to sqlite-storage Podman volume if not specified. Root is required to uninstall. --ssh-key , -k The path of your SSH identity key. Defaults to ~/.ssh/quay_installer if left unspecified. --sslCert The path to the SSL/TLS public key / certificate. Defaults to {quayRoot}/quay-config and is auto-generated if left unspecified. --sslCheckSkip Skips the check for the certificate hostname against the SERVER_HOSTNAME in the config.yaml file. [2] --sslKey The path to the SSL/TLS private key used for HTTPS communication. Defaults to {quayRoot}/quay-config and is auto-generated if left unspecified. --targetHostname , -H The hostname of the target you want to install Quay to. Defaults to USDHOST , for example, a local host, if left unspecified. --targetUsername , -u The user on the target host which will be used for SSH. Defaults to USDUSER , for example, the current user if left unspecified. --verbose , -v Shows debug logs and Ansible playbook outputs. --version Shows the version for the mirror registry for Red Hat OpenShift . --quayHostname must be modified if the public DNS name of your system is different from the local hostname. Additionally, the --quayHostname flag does not support installation with an IP address. Installation with a hostname is required. --sslCheckSkip is used in cases when the mirror registry is set behind a proxy and the exposed hostname is different from the internal Quay hostname. It can also be used when users do not want the certificates to be validated against the provided Quay hostname during installation. 2.10. Mirror registry for Red Hat OpenShift release notes The mirror registry for Red Hat OpenShift is a small and streamlined container registry that you can use as a target for mirroring the required container images of OpenShift Container Platform for disconnected installations. These release notes track the development of the mirror registry for Red Hat OpenShift in OpenShift Container Platform. 2.10.1. Mirror registry for Red Hat OpenShift 2.0 release notes The following sections provide details for each 2.0 release of the mirror registry for Red Hat OpenShift. 2.10.1.1. Mirror registry for Red Hat OpenShift 2.0.5 Issued: 13 January 2025 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.12.5. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2025:0298 - mirror registry for Red Hat OpenShift 2.0.5 2.10.1.2. Mirror registry for Red Hat OpenShift 2.0.4 Issued: 06 January 2025 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.12.4. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2025:0033 - mirror registry for Red Hat OpenShift 2.0.4 2.10.1.3. Mirror registry for Red Hat OpenShift 2.0.3 Issued: 25 November 2024 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.12.3. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2024:10181 - mirror registry for Red Hat OpenShift 2.0.3 2.10.1.4. Mirror registry for Red Hat OpenShift 2.0.2 Issued: 31 October 2024 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.12.2. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2024:8370 - mirror registry for Red Hat OpenShift 2.0.2 2.10.1.5. Mirror registry for Red Hat OpenShift 2.0.1 Issued: 26 September 2024 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.12.1. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2024:7070 - mirror registry for Red Hat OpenShift 2.0.1 2.10.1.6. Mirror registry for Red Hat OpenShift 2.0.0 Issued: 03 September 2024 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.12.0. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2024:5277 - mirror registry for Red Hat OpenShift 2.0.0 2.10.1.6.1. New features With the release of mirror registry for Red Hat OpenShift , the internal database has been upgraded from PostgreSQL to SQLite. As a result, data is now stored on the sqlite-storage Podman volume by default, and the overall tarball size is reduced by 300 MB. New installations use SQLite by default. Before upgrading to version 2.0, see "Updating mirror registry for Red Hat OpenShift from a local host" or "Updating mirror registry for Red Hat OpenShift from a remote host" depending on your environment. A new feature flag, --sqliteStorage has been added. With this flag, you can manually set the location where SQLite database data is saved. Mirror registry for Red Hat OpenShift is now available on IBM Power and IBM Z architectures ( s390x and ppc64le ). 2.10.2. Mirror registry for Red Hat OpenShift 1.3 release notes The following sections provide details for each 1.3.z release of the mirror registry for Red Hat OpenShift 2.10.2.1. Mirror registry for Red Hat OpenShift 1.3.11 Issued: 2024-04-23 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.15. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2024:1758 - mirror registry for Red Hat OpenShift 1.3.11 2.10.2.2. Mirror registry for Red Hat OpenShift 1.3.10 Issued: 2023-12-07 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.14. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:7628 - mirror registry for Red Hat OpenShift 1.3.10 2.10.2.3. Mirror registry for Red Hat OpenShift 1.3.9 Issued: 2023-09-19 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.12. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:5241 - mirror registry for Red Hat OpenShift 1.3.9 2.10.2.4. Mirror registry for Red Hat OpenShift 1.3.8 Issued: 2023-08-16 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.11. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:4622 - mirror registry for Red Hat OpenShift 1.3.8 2.10.2.5. Mirror registry for Red Hat OpenShift 1.3.7 Issued: 2023-07-19 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.10. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:4087 - mirror registry for Red Hat OpenShift 1.3.7 2.10.2.6. Mirror registry for Red Hat OpenShift 1.3.6 Issued: 2023-05-30 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.8. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:3302 - mirror registry for Red Hat OpenShift 1.3.6 2.10.2.7. Mirror registry for Red Hat OpenShift 1.3.5 Issued: 2023-05-18 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.7. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:3225 - mirror registry for Red Hat OpenShift 1.3.5 2.10.2.8. Mirror registry for Red Hat OpenShift 1.3.4 Issued: 2023-04-25 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.6. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:1914 - mirror registry for Red Hat OpenShift 1.3.4 2.10.2.9. Mirror registry for Red Hat OpenShift 1.3.3 Issued: 2023-04-05 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.5. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:1528 - mirror registry for Red Hat OpenShift 1.3.3 2.10.2.10. Mirror registry for Red Hat OpenShift 1.3.2 Issued: 2023-03-21 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.4. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:1376 - mirror registry for Red Hat OpenShift 1.3.2 2.10.2.11. Mirror registry for Red Hat OpenShift 1.3.1 Issued: 2023-03-7 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.3. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:1086 - mirror registry for Red Hat OpenShift 1.3.1 2.10.2.12. Mirror registry for Red Hat OpenShift 1.3.0 Issued: 2023-02-20 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.8.1. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2023:0558 - mirror registry for Red Hat OpenShift 1.3.0 2.10.2.12.1. New features Mirror registry for Red Hat OpenShift is now supported on Red Hat Enterprise Linux (RHEL) 9 installations. IPv6 support is now available on mirror registry for Red Hat OpenShift local host installations. IPv6 is currently unsupported on mirror registry for Red Hat OpenShift remote host installations. A new feature flag, --quayStorage , has been added. By specifying this flag, you can manually set the location for the Quay persistent storage. A new feature flag, --pgStorage , has been added. By specifying this flag, you can manually set the location for the Postgres persistent storage. Previously, users were required to have root privileges ( sudo ) to install mirror registry for Red Hat OpenShift . With this update, sudo is no longer required to install mirror registry for Red Hat OpenShift . When mirror registry for Red Hat OpenShift was installed with sudo , an /etc/quay-install directory that contained installation files, local storage, and the configuration bundle was created. With the removal of the sudo requirement, installation files and the configuration bundle are now installed to USDHOME/quay-install . Local storage, for example Postgres and Quay, are now stored in named volumes automatically created by Podman. To override the default directories that these files are stored in, you can use the command line arguments for mirror registry for Red Hat OpenShift . For more information about mirror registry for Red Hat OpenShift command line arguments, see " Mirror registry for Red Hat OpenShift flags". 2.10.2.12.2. Bug fixes Previously, the following error could be returned when attempting to uninstall mirror registry for Red Hat OpenShift : ["Error: no container with name or ID \"quay-postgres\" found: no such container"], "stdout": "", "stdout_lines": [] * . With this update, the order that mirror registry for Red Hat OpenShift services are stopped and uninstalled have been changed so that the error no longer occurs when uninstalling mirror registry for Red Hat OpenShift . For more information, see PROJQUAY-4629 . 2.10.3. Mirror registry for Red Hat OpenShift 1.2 release notes The following sections provide details for each 1.2.z release of the mirror registry for Red Hat OpenShift 2.10.3.1. Mirror registry for Red Hat OpenShift 1.2.9 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.10. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:7369 - mirror registry for Red Hat OpenShift 1.2.9 2.10.3.2. Mirror registry for Red Hat OpenShift 1.2.8 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.9. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:7065 - mirror registry for Red Hat OpenShift 1.2.8 2.10.3.3. Mirror registry for Red Hat OpenShift 1.2.7 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.8. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:6500 - mirror registry for Red Hat OpenShift 1.2.7 2.10.3.3.1. Bug fixes Previously, getFQDN() relied on the fully-qualified domain name (FQDN) library to determine its FQDN, and the FQDN library tried to read the /etc/hosts folder directly. Consequently, on some Red Hat Enterprise Linux CoreOS (RHCOS) installations with uncommon DNS configurations, the FQDN library would fail to install and abort the installation. With this update, mirror registry for Red Hat OpenShift uses hostname to determine the FQDN. As a result, the FQDN library does not fail to install. ( PROJQUAY-4139 ) 2.10.3.4. Mirror registry for Red Hat OpenShift 1.2.6 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.7. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:6278 - mirror registry for Red Hat OpenShift 1.2.6 2.10.3.4.1. New features A new feature flag, --no-color ( -c ) has been added. This feature flag allows users to disable color sequences and propagate that to Ansible when running install, uninstall, and upgrade commands. 2.10.3.5. Mirror registry for Red Hat OpenShift 1.2.5 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.6. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:6071 - mirror registry for Red Hat OpenShift 1.2.5 2.10.3.6. Mirror registry for Red Hat OpenShift 1.2.4 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.5. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:5884 - mirror registry for Red Hat OpenShift 1.2.4 2.10.3.7. Mirror registry for Red Hat OpenShift 1.2.3 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.4. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:5649 - mirror registry for Red Hat OpenShift 1.2.3 2.10.3.8. Mirror registry for Red Hat OpenShift 1.2.2 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.3. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:5501 - mirror registry for Red Hat OpenShift 1.2.2 2.10.3.9. Mirror registry for Red Hat OpenShift 1.2.1 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.2. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:4986 - mirror registry for Red Hat OpenShift 1.2.1 2.10.3.10. Mirror registry for Red Hat OpenShift 1.2.0 Mirror registry for Red Hat OpenShift is now available with Red Hat Quay 3.7.1. The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:4986 - mirror registry for Red Hat OpenShift 1.2.0 2.10.3.10.1. Bug fixes Previously, all components and workers running inside of the Quay pod Operator had log levels set to DEBUG . As a result, large traffic logs were created that consumed unnecessary space. With this update, log levels are set to WARN by default, which reduces traffic information while emphasizing problem scenarios. ( PROJQUAY-3504 ) 2.10.4. Mirror registry for Red Hat OpenShift 1.1 release notes The following section provides details 1.1.0 release of the mirror registry for Red Hat OpenShift 2.10.4.1. Mirror registry for Red Hat OpenShift 1.1.0 The following advisory is available for the mirror registry for Red Hat OpenShift : RHBA-2022:0956 - mirror registry for Red Hat OpenShift 1.1.0 2.10.4.1.1. New features A new command, mirror-registry upgrade has been added. This command upgrades all container images without interfering with configurations or data. Note If quayRoot was previously set to something other than default, it must be passed into the upgrade command. 2.10.4.1.2. Bug fixes Previously, the absence of quayHostname or targetHostname did not default to the local hostname. With this update, quayHostname and targetHostname now default to the local hostname if they are missing. ( PROJQUAY-3079 ) Previously, the command ./mirror-registry --version returned an unknown flag error. Now, running ./mirror-registry --version returns the current version of the mirror registry for Red Hat OpenShift . ( PROJQUAY-3086 ) Previously, users could not set a password during installation, for example, when running ./mirror-registry install --initUser <user_name> --initPassword <password> --verbose . With this update, users can set a password during installation. ( PROJQUAY-3149 ) Previously, the mirror registry for Red Hat OpenShift did not recreate pods if they were destroyed. Now, pods are recreated if they are destroyed. ( PROJQUAY-3261 ) 2.11. Troubleshooting mirror registry for Red Hat OpenShift To assist in troubleshooting mirror registry for Red Hat OpenShift , you can gather logs of systemd services installed by the mirror registry. The following services are installed: quay-app.service quay-postgres.service quay-redis.service quay-pod.service Prerequisites You have installed mirror registry for Red Hat OpenShift . Procedure If you installed mirror registry for Red Hat OpenShift with root privileges, you can get the status information of its systemd services by entering the following command: USD sudo systemctl status <service> If you installed mirror registry for Red Hat OpenShift as a standard user, you can get the status information of its systemd services by entering the following command: USD systemctl --user status <service> 2.12. Additional resources Red Hat Quay garbage collection Using SSL to protect connections to Red Hat Quay Configuring the system to trust the certificate authority Mirroring the OpenShift Container Platform image repository Mirroring Operator catalogs for use with disconnected clusters	[ "./mirror-registry install --quayHostname <host_example_com> --quayRoot <example_directory_name>", "podman login -u init -p <password> <host_example_com>:8443> --tls-verify=false 1", "sudo ./mirror-registry upgrade -v", "sudo ./mirror-registry upgrade --quayHostname <host_example_com> --quayRoot <example_directory_name> --quayStorage <example_directory_name>/quay-storage -v", "sudo ./mirror-registry upgrade --sqliteStorage <example_directory_name>/sqlite-storage -v", "./mirror-registry install -v --targetHostname <host_example_com> --targetUsername <example_user> -k ~/.ssh/my_ssh_key --quayHostname <host_example_com> --quayRoot <example_directory_name>", "podman login -u init -p <password> <host_example_com>:8443> --tls-verify=false 1", "./mirror-registry upgrade -v --targetHostname <remote_host_url> --targetUsername <user_name> -k ~/.ssh/my_ssh_key", "./mirror-registry upgrade -v --targetHostname <remote_host_url> --targetUsername <user_name> -k ~/.ssh/my_ssh_key --sqliteStorage <example_directory_name>/quay-storage", "./mirror-registry install --quayHostname <host_example_com> --quayRoot <example_directory_name>", "export QUAY=/USDHOME/quay-install", "cp ~/ssl.crt USDQUAY/quay-config", "cp ~/ssl.key USDQUAY/quay-config", "systemctl --user restart quay-app", "./mirror-registry uninstall -v --quayRoot <example_directory_name>", "sudo systemctl status <service>", "systemctl --user status <service>" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.14/html/disconnected_installation_mirroring/installing-mirroring-creating-registry
Chapter 8. Managing pools on the Ceph dashboard	Chapter 8. Managing pools on the Ceph dashboard As a storage administrator, you can create, edit, and delete pools on the Red Hat Ceph Storage dashboard. This section covers the following administrative tasks: Creating pools on the Ceph dashboard . Editing pools on the Ceph dashboard . Deleting pools on the Ceph dashboard . 8.1. Creating pools on the Ceph dashboard When you deploy a storage cluster without creating a pool, Ceph uses the default pools for storing data. You can create pools to logically partition your storage objects on the Red Hat Ceph Storage dashboard. Prerequisites A running Red Hat Ceph Storage cluster. Dashboard is installed. Procedure Log in to the dashboard. On the navigation menu, click Pools . Click Create . In the Create Pool window, set the following parameters: Figure 8.1. Creating pools Set the name of the pool and select the pool type. Select either replicated or Erasure Coded (EC) pool type. Set the Placement Group (PG) number. Optional: If using a replicated pool type, set the replicated size. Optional: If using an EC pool type configure the following additional settings. Optional: To see the settings for the currently selected EC profile, click the question mark. Optional: Add a new EC profile by clicking the plus symbol. Optional: Click the pencil symbol to select an application for the pool. Optional: Set the CRUSH rule, if applicable. Optional: If compression is required, select passive , aggressive , or force . Optional: Set the Quotas. Optional: Set the Quality of Service configuration. Click Create Pool . You get a notification that the pool was created successfully. Additional Resources For more information, see Ceph pools section in the Red Hat Ceph Storage Architecture Guide for more details. 8.2. Editing pools on the Ceph dashboard You can edit the pools on the Red Hat Ceph Storage Dashboard. Prerequisites A running Red Hat Ceph Storage cluster. Dashboard is installed. A pool is created. Procedure Log in to the dashboard. On the navigation menu, click Pools . To edit the pool, click its row. Select Edit In the Edit drop-down. In the Edit Pool window, edit the required parameters and click Edit Pool : Figure 8.2. Editing pools You get a notification that the pool was created successfully. Additional Resources See the Ceph pools in the Red Hat Ceph Storage Architecture Guide for more information. See the Pool values in the Red Hat Ceph Storage Storage Strategies Guide for more information on Compression Modes. 8.3. Deleting pools on the Ceph dashboard You can delete the pools on the Red Hat Ceph Storage Dashboard. Ensure that value of mon_allow_pool_delete is set to True in Manager modules. Prerequisites A running Red Hat Ceph Storage cluster. Dashboard is installed. A pool is created. Procedure Log in to the dashboard. On the navigation bar, in Cluster drop-down menu, click Configuration . In the Level drop-down menu, select Advanced : Search for mon_allow_pool_delete , click Edit Set all the values to true : Figure 8.3. Configuration to delete pools On the navigation bar, click Pools : To delete the pool, click on its row: From Edit drop-down menu, select Delete . In the Delete Pool window, Click the Yes, I am sure box and then Click Delete Pool to save the settings: Figure 8.4. Delete pools Additional Resources See the Ceph pools in the Red Hat Ceph Storage Architecture Guide for more information. See the Pool values in the Red Hat Ceph Storage Storage Strategies Guide for more information on Compression Modes.	null	https://docs.redhat.com/en/documentation/red_hat_ceph_storage/6/html/dashboard_guide/management-of-pools-on-the-ceph-dashboard
Appendix D. Glossary of terms	Appendix D. Glossary of terms D.1. Virtualization terms Administration Portal A web user interface provided by Red Hat Virtualization Manager, based on the oVirt engine web user interface. It allows administrators to manage and monitor cluster resources like networks, storage domains, and virtual machine templates. Hosted Engine The instance of Red Hat Virtualization Manager that manages RHHI for Virtualization. Hosted Engine virtual machine The virtual machine that acts as Red Hat Virtualization Manager. The Hosted Engine virtual machine runs on a virtualization host that is managed by the instance of Red Hat Virtualization Manager that is running on the Hosted Engine virtual machine. Manager node A virtualization host that runs Red Hat Virtualization Manager directly, rather than running it in a Hosted Engine virtual machine. Red Hat Enterprise Linux host A physical machine installed with Red Hat Enterprise Linux plus additional packages to provide the same capabilities as a Red Hat Virtualization host. This type of host is not supported for use with RHHI for Virtualization. Red Hat Virtualization An operating system and management interface for virtualizing resources, processes, and applications for Linux and Microsoft Windows workloads. Red Hat Virtualization host A physical machine installed with Red Hat Virtualization that provides the physical resources to support the virtualization of resources, processes, and applications for Linux and Microsoft Windows workloads. This is the only type of host supported with RHHI for Virtualization. Red Hat Virtualization Manager A server that runs the management and monitoring capabilities of Red Hat Virtualization. Self-Hosted Engine node A virtualization host that contains the Hosted Engine virtual machine. All hosts in a RHHI for Virtualization deployment are capable of becoming Self-Hosted Engine nodes, but there is only one Self-Hosted Engine node at a time. storage domain A named collection of images, templates, snapshots, and metadata. A storage domain can be comprised of block devices or file systems. Storage domains are attached to data centers in order to provide access to the collection of images, templates, and so on to hosts in the data center. virtualization host A physical machine with the ability to virtualize physical resources, processes, and applications for client access. VM Portal A web user interface provided by Red Hat Virtualization Manager. It allows users to manage and monitor virtual machines. D.2. Storage terms brick An exported directory on a server in a trusted storage pool. cache logical volume A small, fast logical volume used to improve the performance of a large, slow logical volume. geo-replication One way asynchronous replication of data from a source Gluster volume to a target volume. Geo-replication works across local and wide area networks as well as the Internet. The target volume can be a Gluster volume in a different trusted storage pool, or another type of storage. gluster volume A logical group of bricks that can be configured to distribute, replicate, or disperse data according to workload requirements. logical volume management (LVM) A method of combining physical disks into larger virtual partitions. Physical volumes are placed in volume groups to form a pool of storage that can be divided into logical volumes as needed. Red Hat Gluster Storage An operating system based on Red Hat Enterprise Linux with additional packages that provide support for distributed, software-defined storage. source volume The Gluster volume that data is being copied from during geo-replication. storage host A physical machine that provides storage for client access. target volume The Gluster volume or other storage volume that data is being copied to during geo-replication. thin provisioning Provisioning storage such that only the space that is required is allocated at creation time, with further space being allocated dynamically according to need over time. thick provisioning Provisioning storage such that all space is allocated at creation time, regardless of whether that space is required immediately. trusted storage pool A group of Red Hat Gluster Storage servers that recognise each other as trusted peers. D.3. Hyperconverged Infrastructure terms Red Hat Hyperconverged Infrastructure (RHHI) for Virtualization RHHI for Virtualization is a single product that provides both virtual compute and virtual storage resources. Red Hat Virtualization and Red Hat Gluster Storage are installed in a converged configuration, where the services of both products are available on each physical machine in a cluster. hyperconverged host A physical machine that provides physical storage, which is virtualized and consumed by virtualized processes and applications run on the same host. All hosts installed with RHHI for Virtualization are hyperconverged hosts. Web Console The web user interface for deploying, managing, and monitoring RHHI for Virtualization. The Web Console is provided by the Web Console service and plugins for Red Hat Virtualization Manager.	null	https://docs.redhat.com/en/documentation/red_hat_hyperconverged_infrastructure_for_virtualization/1.8/html/deploying_red_hat_hyperconverged_infrastructure_for_virtualization/glossary-of-terms
Chapter 7. OLM v1	Chapter 7. OLM v1 7.1. About Operator Lifecycle Manager v1 (Technology Preview) Operator Lifecycle Manager (OLM) has been included with OpenShift Container Platform 4 since its initial release. OpenShift Container Platform 4.18 includes components for a -generation iteration of OLM as a Generally Available (GA) feature, known during this phase as OLM v1 . This updated framework evolves many of the concepts that have been part of versions of OLM and adds new capabilities. Starting in OpenShift Container Platform 4.17, documentation for OLM v1 has been moved to the following new guide: Extensions (OLM v1)	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.18/html/operators/olm-v1
Chapter 2. Embedded caches	Chapter 2. Embedded caches Add Data Grid as a dependency to your Java project and use embedded caches that increase application performance and give you capabilities to handle complex use cases. 2.1. Embedded cache tutorials You can run embedded cache tutorials directly in your IDE or from the command line as follows: USD mvn -s /path/to/maven-settings.xml clean package exec:exec Tutorial link Description Distributed caches Demonstrates how Distributed Caches work. Replicated caches Demonstrates how Replicated Caches work. Invalidated caches Demonstrates how Invalidated Caches work. Transactions Demonstrates how transactions work. Streams Demonstrates how Distributed Streams work. JCache integration Demonstrates how JCache works. Functional Maps Demonstrates how Functional Map API works. Map API Demonstrates how the Map API works with Data Grid caches. Multimap Demonstrates how to use Multimap. Queries Uses Data Grid Query to perform full-text queries on cache values. Clustered Listeners Detects when data changes in an embedded cache with Clustered Listeners. Counters Demonstrates how to use an embedded Clustered Counter. Clustered Locks Demonstrates how to use an embedded Clustered Lock. Clustered execution Demonstrates how to use an embedded Clustered Counter. Data Grid documentation You can find more resources about embedded caches in our documentation at: Embedding Data Grid Caches Querying Data Grid caches 2.2. Kubernetes and Openshift tutorial This tutorial contains instructions on how to run Infinispan library mode (as a microservice) in Kubernetes/OpenShift. Prerequisites: Maven and Docker daemon running in the background. Prerequisites A running Openshift or Kubernetes cluster Building the tutorial This tutorial is built using the maven command: mvn package Note that target/ directory contains additional directories like docker (with generated Dockerfile) and classes/META-INF/jkube with Kubernetes and OpenShift deployment templates. Tip If the Docker Daemon is down, the build will omit processing Dockerfiles. Use docker profile to turn it on manually. Deploying the tutorial to Kubernetes This is handle by the JKube maven plugin, just invoke: mvn k8s:build k8s:push k8s:resource k8s:apply -Doptions.image=<IMAGE_NAME> 1 1 IMAGE_NAME must be replaced with the FQN of the container to deploy to Kubernetes. This container must be created in a repository that you have permissions to push to and is accessible from within your Kubernetes cluster. Viewing and scaling up Everything should be up and running at this point. Now login into the OpenShift or Kubernetes cluster and scale the application kubectl scale --replicas=3 deployment/USD(kubectl get rs --namespace=myproject \| grep infinispan \| awk '{print USD1}') --namespace=myproject Undeploying the tutorial This is handled by the JKube maven plugin, just invoke:	[ "mvn -s /path/to/maven-settings.xml clean package exec:exec", "mvn package", "mvn k8s:build k8s:push k8s:resource k8s:apply -Doptions.image=<IMAGE_NAME> 1", "scale --replicas=3 deployment/USD(kubectl get rs --namespace=myproject \| grep infinispan \| awk '{print USD1}') --namespace=myproject", "mvn k8s:undeploy" ]	https://docs.redhat.com/en/documentation/red_hat_data_grid/8.4/html/data_grid_code_tutorials/embedded-tutorials
Chapter 2. access	Chapter 2. access This chapter describes the commands under the access command. 2.1. access rule delete Delete access rule(s) Usage: Table 2.1. Positional arguments Value Summary <access-rule> Access rule id(s) to delete Table 2.2. Command arguments Value Summary -h, --help Show this help message and exit 2.2. access rule list List access rules Usage: Table 2.3. Command arguments Value Summary -h, --help Show this help message and exit --user <user> User whose access rules to list (name or id) --user-domain <user-domain> Domain the user belongs to (name or id). this can be used in case collisions between user names exist. Table 2.4. Output formatter options Value Summary -f {csv,json,table,value,yaml}, --format {csv,json,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns --sort-column SORT_COLUMN Specify the column(s) to sort the data (columns specified first have a priority, non-existing columns are ignored), can be repeated --sort-ascending Sort the column(s) in ascending order --sort-descending Sort the column(s) in descending order Table 2.5. CSV formatter options Value Summary --quote {all,minimal,none,nonnumeric} When to include quotes, defaults to nonnumeric Table 2.6. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 2.7. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 2.3. access rule show Display access rule details Usage: Table 2.8. Positional arguments Value Summary <access-rule> Access rule id to display Table 2.9. Command arguments Value Summary -h, --help Show this help message and exit Table 2.10. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 2.11. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 2.12. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 2.13. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show. 2.4. access token create Create an access token Usage: Table 2.14. Command arguments Value Summary -h, --help Show this help message and exit --consumer-key <consumer-key> Consumer key (required) --consumer-secret <consumer-secret> Consumer secret (required) --request-key <request-key> Request token to exchange for access token (required) --request-secret <request-secret> Secret associated with <request-key> (required) --verifier <verifier> Verifier associated with <request-key> (required) Table 2.15. Output formatter options Value Summary -f {json,shell,table,value,yaml}, --format {json,shell,table,value,yaml} The output format, defaults to table -c COLUMN, --column COLUMN Specify the column(s) to include, can be repeated to show multiple columns Table 2.16. JSON formatter options Value Summary --noindent Whether to disable indenting the json Table 2.17. Shell formatter options Value Summary --prefix PREFIX Add a prefix to all variable names Table 2.18. Table formatter options Value Summary --max-width <integer> Maximum display width, <1 to disable. you can also use the CLIFF_MAX_TERM_WIDTH environment variable, but the parameter takes precedence. --fit-width Fit the table to the display width. implied if --max- width greater than 0. Set the environment variable CLIFF_FIT_WIDTH=1 to always enable --print-empty Print empty table if there is no data to show.	[ "openstack access rule delete [-h] <access-rule> [<access-rule> ...]", "openstack access rule list [-h] [-f {csv,json,table,value,yaml}] [-c COLUMN] [--quote {all,minimal,none,nonnumeric}] [--noindent] [--max-width <integer>] [--fit-width] [--print-empty] [--sort-column SORT_COLUMN] [--sort-ascending \| --sort-descending] [--user <user>] [--user-domain <user-domain>]", "openstack access rule show [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] <access-rule>", "openstack access token create [-h] [-f {json,shell,table,value,yaml}] [-c COLUMN] [--noindent] [--prefix PREFIX] [--max-width <integer>] [--fit-width] [--print-empty] --consumer-key <consumer-key> --consumer-secret <consumer-secret> --request-key <request-key> --request-secret <request-secret> --verifier <verifier>" ]	https://docs.redhat.com/en/documentation/red_hat_openstack_services_on_openshift/18.0/html/command_line_interface_reference/access
Chapter 6. PriorityClass [scheduling.k8s.io/v1]	Chapter 6. PriorityClass [scheduling.k8s.io/v1] Description PriorityClass defines mapping from a priority class name to the priority integer value. The value can be any valid integer. Type object Required value 6.1. Specification Property Type Description apiVersion string APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#resources description string description is an arbitrary string that usually provides guidelines on when this priority class should be used. globalDefault boolean globalDefault specifies whether this PriorityClass should be considered as the default priority for pods that do not have any priority class. Only one PriorityClass can be marked as globalDefault . However, if more than one PriorityClasses exists with their globalDefault field set to true, the smallest value of such global default PriorityClasses will be used as the default priority. kind string Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds metadata ObjectMeta Standard object's metadata. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata preemptionPolicy string preemptionPolicy is the Policy for preempting pods with lower priority. One of Never, PreemptLowerPriority. Defaults to PreemptLowerPriority if unset. Possible enum values: - "Never" means that pod never preempts other pods with lower priority. - "PreemptLowerPriority" means that pod can preempt other pods with lower priority. value integer value represents the integer value of this priority class. This is the actual priority that pods receive when they have the name of this class in their pod spec. 6.2. API endpoints The following API endpoints are available: /apis/scheduling.k8s.io/v1/priorityclasses DELETE : delete collection of PriorityClass GET : list or watch objects of kind PriorityClass POST : create a PriorityClass /apis/scheduling.k8s.io/v1/watch/priorityclasses GET : watch individual changes to a list of PriorityClass. deprecated: use the 'watch' parameter with a list operation instead. /apis/scheduling.k8s.io/v1/priorityclasses/{name} DELETE : delete a PriorityClass GET : read the specified PriorityClass PATCH : partially update the specified PriorityClass PUT : replace the specified PriorityClass /apis/scheduling.k8s.io/v1/watch/priorityclasses/{name} GET : watch changes to an object of kind PriorityClass. deprecated: use the 'watch' parameter with a list operation instead, filtered to a single item with the 'fieldSelector' parameter. 6.2.1. /apis/scheduling.k8s.io/v1/priorityclasses Table 6.1. Global query parameters Parameter Type Description pretty string If 'true', then the output is pretty printed. HTTP method DELETE Description delete collection of PriorityClass Table 6.2. Query parameters Parameter Type Description continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. gracePeriodSeconds integer The duration in seconds before the object should be deleted. Value must be non-negative integer. The value zero indicates delete immediately. If this value is nil, the default grace period for the specified type will be used. Defaults to a per object value if not specified. zero means delete immediately. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. orphanDependents boolean Deprecated: please use the PropagationPolicy, this field will be deprecated in 1.7. Should the dependent objects be orphaned. If true/false, the "orphan" finalizer will be added to/removed from the object's finalizers list. Either this field or PropagationPolicy may be set, but not both. propagationPolicy string Whether and how garbage collection will be performed. Either this field or OrphanDependents may be set, but not both. The default policy is decided by the existing finalizer set in the metadata.finalizers and the resource-specific default policy. Acceptable values are: 'Orphan' - orphan the dependents; 'Background' - allow the garbage collector to delete the dependents in the background; 'Foreground' - a cascading policy that deletes all dependents in the foreground. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset sendInitialEvents boolean sendInitialEvents=true may be set together with watch=true . In that case, the watch stream will begin with synthetic events to produce the current state of objects in the collection. Once all such events have been sent, a synthetic "Bookmark" event will be sent. The bookmark will report the ResourceVersion (RV) corresponding to the set of objects, and be marked with "k8s.io/initial-events-end": "true" annotation. Afterwards, the watch stream will proceed as usual, sending watch events corresponding to changes (subsequent to the RV) to objects watched. When sendInitialEvents option is set, we require resourceVersionMatch option to also be set. The semantic of the watch request is as following: - resourceVersionMatch = NotOlderThan is interpreted as "data at least as new as the provided resourceVersion`" and the bookmark event is send when the state is synced to a `resourceVersion at least as fresh as the one provided by the ListOptions. If resourceVersion is unset, this is interpreted as "consistent read" and the bookmark event is send when the state is synced at least to the moment when request started being processed. - resourceVersionMatch set to any other value or unset Invalid error is returned. Defaults to true if resourceVersion="" or resourceVersion="0" (for backward compatibility reasons) and to false otherwise. timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. Table 6.3. Body parameters Parameter Type Description body DeleteOptions schema Table 6.4. HTTP responses HTTP code Reponse body 200 - OK Status schema 401 - Unauthorized Empty HTTP method GET Description list or watch objects of kind PriorityClass Table 6.5. Query parameters Parameter Type Description allowWatchBookmarks boolean allowWatchBookmarks requests watch events with type "BOOKMARK". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset sendInitialEvents boolean sendInitialEvents=true may be set together with watch=true . In that case, the watch stream will begin with synthetic events to produce the current state of objects in the collection. Once all such events have been sent, a synthetic "Bookmark" event will be sent. The bookmark will report the ResourceVersion (RV) corresponding to the set of objects, and be marked with "k8s.io/initial-events-end": "true" annotation. Afterwards, the watch stream will proceed as usual, sending watch events corresponding to changes (subsequent to the RV) to objects watched. When sendInitialEvents option is set, we require resourceVersionMatch option to also be set. The semantic of the watch request is as following: - resourceVersionMatch = NotOlderThan is interpreted as "data at least as new as the provided resourceVersion`" and the bookmark event is send when the state is synced to a `resourceVersion at least as fresh as the one provided by the ListOptions. If resourceVersion is unset, this is interpreted as "consistent read" and the bookmark event is send when the state is synced at least to the moment when request started being processed. - resourceVersionMatch set to any other value or unset Invalid error is returned. Defaults to true if resourceVersion="" or resourceVersion="0" (for backward compatibility reasons) and to false otherwise. timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. watch boolean Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. Table 6.6. HTTP responses HTTP code Reponse body 200 - OK PriorityClassList schema 401 - Unauthorized Empty HTTP method POST Description create a PriorityClass Table 6.7. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 6.8. Body parameters Parameter Type Description body PriorityClass schema Table 6.9. HTTP responses HTTP code Reponse body 200 - OK PriorityClass schema 201 - Created PriorityClass schema 202 - Accepted PriorityClass schema 401 - Unauthorized Empty 6.2.2. /apis/scheduling.k8s.io/v1/watch/priorityclasses Table 6.10. Global query parameters Parameter Type Description allowWatchBookmarks boolean allowWatchBookmarks requests watch events with type "BOOKMARK". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. pretty string If 'true', then the output is pretty printed. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset sendInitialEvents boolean sendInitialEvents=true may be set together with watch=true . In that case, the watch stream will begin with synthetic events to produce the current state of objects in the collection. Once all such events have been sent, a synthetic "Bookmark" event will be sent. The bookmark will report the ResourceVersion (RV) corresponding to the set of objects, and be marked with "k8s.io/initial-events-end": "true" annotation. Afterwards, the watch stream will proceed as usual, sending watch events corresponding to changes (subsequent to the RV) to objects watched. When sendInitialEvents option is set, we require resourceVersionMatch option to also be set. The semantic of the watch request is as following: - resourceVersionMatch = NotOlderThan is interpreted as "data at least as new as the provided resourceVersion`" and the bookmark event is send when the state is synced to a `resourceVersion at least as fresh as the one provided by the ListOptions. If resourceVersion is unset, this is interpreted as "consistent read" and the bookmark event is send when the state is synced at least to the moment when request started being processed. - resourceVersionMatch set to any other value or unset Invalid error is returned. Defaults to true if resourceVersion="" or resourceVersion="0" (for backward compatibility reasons) and to false otherwise. timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. watch boolean Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. HTTP method GET Description watch individual changes to a list of PriorityClass. deprecated: use the 'watch' parameter with a list operation instead. Table 6.11. HTTP responses HTTP code Reponse body 200 - OK WatchEvent schema 401 - Unauthorized Empty 6.2.3. /apis/scheduling.k8s.io/v1/priorityclasses/{name} Table 6.12. Global path parameters Parameter Type Description name string name of the PriorityClass Table 6.13. Global query parameters Parameter Type Description pretty string If 'true', then the output is pretty printed. HTTP method DELETE Description delete a PriorityClass Table 6.14. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed gracePeriodSeconds integer The duration in seconds before the object should be deleted. Value must be non-negative integer. The value zero indicates delete immediately. If this value is nil, the default grace period for the specified type will be used. Defaults to a per object value if not specified. zero means delete immediately. orphanDependents boolean Deprecated: please use the PropagationPolicy, this field will be deprecated in 1.7. Should the dependent objects be orphaned. If true/false, the "orphan" finalizer will be added to/removed from the object's finalizers list. Either this field or PropagationPolicy may be set, but not both. propagationPolicy string Whether and how garbage collection will be performed. Either this field or OrphanDependents may be set, but not both. The default policy is decided by the existing finalizer set in the metadata.finalizers and the resource-specific default policy. Acceptable values are: 'Orphan' - orphan the dependents; 'Background' - allow the garbage collector to delete the dependents in the background; 'Foreground' - a cascading policy that deletes all dependents in the foreground. Table 6.15. Body parameters Parameter Type Description body DeleteOptions schema Table 6.16. HTTP responses HTTP code Reponse body 200 - OK Status schema 202 - Accepted Status schema 401 - Unauthorized Empty HTTP method GET Description read the specified PriorityClass Table 6.17. HTTP responses HTTP code Reponse body 200 - OK PriorityClass schema 401 - Unauthorized Empty HTTP method PATCH Description partially update the specified PriorityClass Table 6.18. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . This field is required for apply requests (application/apply-patch) but optional for non-apply patch types (JsonPatch, MergePatch, StrategicMergePatch). fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. force boolean Force is going to "force" Apply requests. It means user will re-acquire conflicting fields owned by other people. Force flag must be unset for non-apply patch requests. Table 6.19. Body parameters Parameter Type Description body Patch schema Table 6.20. HTTP responses HTTP code Reponse body 200 - OK PriorityClass schema 201 - Created PriorityClass schema 401 - Unauthorized Empty HTTP method PUT Description replace the specified PriorityClass Table 6.21. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldManager string fieldManager is a name associated with the actor or entity that is making these changes. The value must be less than or 128 characters long, and only contain printable characters, as defined by https://golang.org/pkg/unicode/#IsPrint . fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 6.22. Body parameters Parameter Type Description body PriorityClass schema Table 6.23. HTTP responses HTTP code Reponse body 200 - OK PriorityClass schema 201 - Created PriorityClass schema 401 - Unauthorized Empty 6.2.4. /apis/scheduling.k8s.io/v1/watch/priorityclasses/{name} Table 6.24. Global path parameters Parameter Type Description name string name of the PriorityClass Table 6.25. Global query parameters Parameter Type Description allowWatchBookmarks boolean allowWatchBookmarks requests watch events with type "BOOKMARK". Servers that do not implement bookmarks may ignore this flag and bookmarks are sent at the server's discretion. Clients should not assume bookmarks are returned at any specific interval, nor may they assume the server will send any BOOKMARK event during a session. If this is not a watch, this field is ignored. continue string The continue option should be set when retrieving more results from the server. Since this value is server defined, clients may only use the continue value from a query result with identical query parameters (except for the value of continue) and the server may reject a continue value it does not recognize. If the specified continue value is no longer valid whether due to expiration (generally five to fifteen minutes) or a configuration change on the server, the server will respond with a 410 ResourceExpired error together with a continue token. If the client needs a consistent list, it must restart their list without the continue field. Otherwise, the client may send another list request with the token received with the 410 error, the server will respond with a list starting from the key, but from the latest snapshot, which is inconsistent from the list results - objects that are created, modified, or deleted after the first list request will be included in the response, as long as their keys are after the " key". This field is not supported when watch is true. Clients may start a watch from the last resourceVersion value returned by the server and not miss any modifications. fieldSelector string A selector to restrict the list of returned objects by their fields. Defaults to everything. labelSelector string A selector to restrict the list of returned objects by their labels. Defaults to everything. limit integer limit is a maximum number of responses to return for a list call. If more items exist, the server will set the continue field on the list metadata to a value that can be used with the same initial query to retrieve the set of results. Setting a limit may return fewer than the requested amount of items (up to zero items) in the event all requested objects are filtered out and clients should only use the presence of the continue field to determine whether more results are available. Servers may choose not to support the limit argument and will return all of the available results. If limit is specified and the continue field is empty, clients may assume that no more results are available. This field is not supported if watch is true. The server guarantees that the objects returned when using continue will be identical to issuing a single list call without a limit - that is, no objects created, modified, or deleted after the first request is issued will be included in any subsequent continued requests. This is sometimes referred to as a consistent snapshot, and ensures that a client that is using limit to receive smaller chunks of a very large result can ensure they see all possible objects. If objects are updated during a chunked list the version of the object that was present at the time the first list result was calculated is returned. pretty string If 'true', then the output is pretty printed. resourceVersion string resourceVersion sets a constraint on what resource versions a request may be served from. See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset resourceVersionMatch string resourceVersionMatch determines how resourceVersion is applied to list calls. It is highly recommended that resourceVersionMatch be set for list calls where resourceVersion is set See https://kubernetes.io/docs/reference/using-api/api-concepts/#resource-versions for details. Defaults to unset sendInitialEvents boolean sendInitialEvents=true may be set together with watch=true . In that case, the watch stream will begin with synthetic events to produce the current state of objects in the collection. Once all such events have been sent, a synthetic "Bookmark" event will be sent. The bookmark will report the ResourceVersion (RV) corresponding to the set of objects, and be marked with "k8s.io/initial-events-end": "true" annotation. Afterwards, the watch stream will proceed as usual, sending watch events corresponding to changes (subsequent to the RV) to objects watched. When sendInitialEvents option is set, we require resourceVersionMatch option to also be set. The semantic of the watch request is as following: - resourceVersionMatch = NotOlderThan is interpreted as "data at least as new as the provided resourceVersion`" and the bookmark event is send when the state is synced to a `resourceVersion at least as fresh as the one provided by the ListOptions. If resourceVersion is unset, this is interpreted as "consistent read" and the bookmark event is send when the state is synced at least to the moment when request started being processed. - resourceVersionMatch set to any other value or unset Invalid error is returned. Defaults to true if resourceVersion="" or resourceVersion="0" (for backward compatibility reasons) and to false otherwise. timeoutSeconds integer Timeout for the list/watch call. This limits the duration of the call, regardless of any activity or inactivity. watch boolean Watch for changes to the described resources and return them as a stream of add, update, and remove notifications. Specify resourceVersion. HTTP method GET Description watch changes to an object of kind PriorityClass. deprecated: use the 'watch' parameter with a list operation instead, filtered to a single item with the 'fieldSelector' parameter. Table 6.26. HTTP responses HTTP code Reponse body 200 - OK WatchEvent schema 401 - Unauthorized Empty	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.14/html/schedule_and_quota_apis/priorityclass-scheduling-k8s-io-v1
9.15. XSD Schema File	9.15. XSD Schema File You can import XML Schema file (XSD) files using the steps below. In Model Explorer, right-click and then click Import... or click the File > Import... action in the toolbar or select a project, folder or model in the tree and click Import... Select the import option Teiid Designer > XML Schemas and click > . Select either Import XSD Schemas from file system or Import XSD Schemas via URL and click > . If importing from file system, the Import XSD Files dialog is displayed. Click the Browse button to find the directory that contains the XSD file(s) you wish to import. To select all of the XSD files in the directory, click the checkbox to the folder in the left panel. To select individual XSD files, click the check boxes to the files you want in the right panel. Figure 9.60. Select XSD From File System If importing from URL, select the Import XML Schemas via URL option and click OK to display the final Add XML Schema URLs wizard page. Figure 9.61. Add XML Schema URLs Dialog Click the Add XML Schema URL button . Enter a valid schema URL. Click OK . Schema will be validated and resulting entry added to the list of XML Schema URLs. Figure 9.62. Add XSD Schema URLs The schema URL is now displayed in the XML Schema URLs list. Figure 9.63. Add XSD Schema URLs Click Finish . Note XSD files may have dependent files. This importer will determine these dependencies and import these as well if Add Dependent Schema Files is selected.	null	https://docs.redhat.com/en/documentation/red_hat_jboss_data_virtualization/6.4/html/user_guide_volume_1_teiid_designer/xsd_schema_file
Chapter 4. ConsoleLink [console.openshift.io/v1]	Chapter 4. ConsoleLink [console.openshift.io/v1] Description ConsoleLink is an extension for customizing OpenShift web console links. Compatibility level 2: Stable within a major release for a minimum of 9 months or 3 minor releases (whichever is longer). Type object Required spec 4.1. Specification Property Type Description apiVersion string APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#resources kind string Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds metadata ObjectMeta Standard object's metadata. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata spec object ConsoleLinkSpec is the desired console link configuration. 4.1.1. .spec Description ConsoleLinkSpec is the desired console link configuration. Type object Required href location text Property Type Description applicationMenu object applicationMenu holds information about section and icon used for the link in the application menu, and it is applicable only when location is set to ApplicationMenu. href string href is the absolute secure URL for the link (must use https) location string location determines which location in the console the link will be appended to (ApplicationMenu, HelpMenu, UserMenu, NamespaceDashboard). namespaceDashboard object namespaceDashboard holds information about namespaces in which the dashboard link should appear, and it is applicable only when location is set to NamespaceDashboard. If not specified, the link will appear in all namespaces. text string text is the display text for the link 4.1.2. .spec.applicationMenu Description applicationMenu holds information about section and icon used for the link in the application menu, and it is applicable only when location is set to ApplicationMenu. Type object Required section Property Type Description imageURL string imageUrl is the URL for the icon used in front of the link in the application menu. The URL must be an HTTPS URL or a Data URI. The image should be square and will be shown at 24x24 pixels. section string section is the section of the application menu in which the link should appear. This can be any text that will appear as a subheading in the application menu dropdown. A new section will be created if the text does not match text of an existing section. 4.1.3. .spec.namespaceDashboard Description namespaceDashboard holds information about namespaces in which the dashboard link should appear, and it is applicable only when location is set to NamespaceDashboard. If not specified, the link will appear in all namespaces. Type object Property Type Description namespaceSelector object namespaceSelector is used to select the Namespaces that should contain dashboard link by label. If the namespace labels match, dashboard link will be shown for the namespaces. namespaces array (string) namespaces is an array of namespace names in which the dashboard link should appear. 4.1.4. .spec.namespaceDashboard.namespaceSelector Description namespaceSelector is used to select the Namespaces that should contain dashboard link by label. If the namespace labels match, dashboard link will be shown for the namespaces. Type object Property Type Description matchExpressions array matchExpressions is a list of label selector requirements. The requirements are ANDed. matchExpressions[] object A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values. matchLabels object (string) matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions, whose key field is "key", the operator is "In", and the values array contains only "value". The requirements are ANDed. 4.1.5. .spec.namespaceDashboard.namespaceSelector.matchExpressions Description matchExpressions is a list of label selector requirements. The requirements are ANDed. Type array 4.1.6. .spec.namespaceDashboard.namespaceSelector.matchExpressions[] Description A label selector requirement is a selector that contains values, a key, and an operator that relates the key and values. Type object Required key operator Property Type Description key string key is the label key that the selector applies to. operator string operator represents a key's relationship to a set of values. Valid operators are In, NotIn, Exists and DoesNotExist. values array (string) values is an array of string values. If the operator is In or NotIn, the values array must be non-empty. If the operator is Exists or DoesNotExist, the values array must be empty. This array is replaced during a strategic merge patch. 4.2. API endpoints The following API endpoints are available: /apis/console.openshift.io/v1/consolelinks DELETE : delete collection of ConsoleLink GET : list objects of kind ConsoleLink POST : create a ConsoleLink /apis/console.openshift.io/v1/consolelinks/{name} DELETE : delete a ConsoleLink GET : read the specified ConsoleLink PATCH : partially update the specified ConsoleLink PUT : replace the specified ConsoleLink /apis/console.openshift.io/v1/consolelinks/{name}/status GET : read status of the specified ConsoleLink PATCH : partially update status of the specified ConsoleLink PUT : replace status of the specified ConsoleLink 4.2.1. /apis/console.openshift.io/v1/consolelinks HTTP method DELETE Description delete collection of ConsoleLink Table 4.1. HTTP responses HTTP code Reponse body 200 - OK Status schema 401 - Unauthorized Empty HTTP method GET Description list objects of kind ConsoleLink Table 4.2. HTTP responses HTTP code Reponse body 200 - OK ConsoleLinkList schema 401 - Unauthorized Empty HTTP method POST Description create a ConsoleLink Table 4.3. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 4.4. Body parameters Parameter Type Description body ConsoleLink schema Table 4.5. HTTP responses HTTP code Reponse body 200 - OK ConsoleLink schema 201 - Created ConsoleLink schema 202 - Accepted ConsoleLink schema 401 - Unauthorized Empty 4.2.2. /apis/console.openshift.io/v1/consolelinks/{name} Table 4.6. Global path parameters Parameter Type Description name string name of the ConsoleLink HTTP method DELETE Description delete a ConsoleLink Table 4.7. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed Table 4.8. HTTP responses HTTP code Reponse body 200 - OK Status schema 202 - Accepted Status schema 401 - Unauthorized Empty HTTP method GET Description read the specified ConsoleLink Table 4.9. HTTP responses HTTP code Reponse body 200 - OK ConsoleLink schema 401 - Unauthorized Empty HTTP method PATCH Description partially update the specified ConsoleLink Table 4.10. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 4.11. HTTP responses HTTP code Reponse body 200 - OK ConsoleLink schema 401 - Unauthorized Empty HTTP method PUT Description replace the specified ConsoleLink Table 4.12. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 4.13. Body parameters Parameter Type Description body ConsoleLink schema Table 4.14. HTTP responses HTTP code Reponse body 200 - OK ConsoleLink schema 201 - Created ConsoleLink schema 401 - Unauthorized Empty 4.2.3. /apis/console.openshift.io/v1/consolelinks/{name}/status Table 4.15. Global path parameters Parameter Type Description name string name of the ConsoleLink HTTP method GET Description read status of the specified ConsoleLink Table 4.16. HTTP responses HTTP code Reponse body 200 - OK ConsoleLink schema 401 - Unauthorized Empty HTTP method PATCH Description partially update status of the specified ConsoleLink Table 4.17. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 4.18. HTTP responses HTTP code Reponse body 200 - OK ConsoleLink schema 401 - Unauthorized Empty HTTP method PUT Description replace status of the specified ConsoleLink Table 4.19. Query parameters Parameter Type Description dryRun string When present, indicates that modifications should not be persisted. An invalid or unrecognized dryRun directive will result in an error response and no further processing of the request. Valid values are: - All: all dry run stages will be processed fieldValidation string fieldValidation instructs the server on how to handle objects in the request (POST/PUT/PATCH) containing unknown or duplicate fields. Valid values are: - Ignore: This will ignore any unknown fields that are silently dropped from the object, and will ignore all but the last duplicate field that the decoder encounters. This is the default behavior prior to v1.23. - Warn: This will send a warning via the standard warning response header for each unknown field that is dropped from the object, and for each duplicate field that is encountered. The request will still succeed if there are no other errors, and will only persist the last of any duplicate fields. This is the default in v1.23+ - Strict: This will fail the request with a BadRequest error if any unknown fields would be dropped from the object, or if any duplicate fields are present. The error returned from the server will contain all unknown and duplicate fields encountered. Table 4.20. Body parameters Parameter Type Description body ConsoleLink schema Table 4.21. HTTP responses HTTP code Reponse body 200 - OK ConsoleLink schema 201 - Created ConsoleLink schema 401 - Unauthorized Empty	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.18/html/console_apis/consolelink-console-openshift-io-v1
Chapter 20. Setting access control on the Directory Manager account	Chapter 20. Setting access control on the Directory Manager account Having an unconstrained administrative user makes sense from a maintenance perspective. The Directory Manager requires a high level of access in order to perform maintenance tasks and to respond to incidents. However, because of the power of the Directory Manager user, a certain level of access control can be advisable to prevent damages from attacks being performed as the administrative user. 20.1. About access controls on the Directory Manager account Directory Server applies regular access control instructions only to the directory tree. The privileges of the Directory Manager account are hard-coded, and you cannot use this account in bind rules. To limit access to the Directory Manager account, use the RootDN Access Control plug-in. This plug-in's features are different from standard access control instructions (ACI). For example, certain information, such as the target (the Directory Manager entry) and the allowed permissions (all of them) is implied. The purpose of the RootDN Access Control plug-in is to provide a level of security by limiting who can log in as Directory Manager based on their location or time, not to restrict what this user can do. For this reason, the settings of the plug-in only support: Time-based access controls, to allow or deny access on certain days and specific time ranges IP address rules, to allow or deny access from defined IP addresses, subnets, and domains Host access rules, to allow or deny access from specific hosts, domains, and subdomains There is only one access control rule you can set for the Directory Manager. It is in the plug-in entry, and it applies to the entire directory. Same as in regular ACIs, deny rules have a higher priority than allow rules. Important Ensure that the Directory Manager account has an appropriate level of access. This administrative user might need to perform maintenance operations in off-hours or to respond to failures. In this case, setting a too restrictive time or day rule can prevent the Directory Manager user from adequately manage the directory. 20.2. Configuring the RootDN access control plug-in using the command line By default, the RootDN Access Control plug-in is disabled. To limit permissions of the Directory Manager account, enable and configure the plug-in. Procedure Enable the RootDN Access Control plug-in: # dsconf -D " cn=Directory Manager " ldap://server.example.com plugin root-dn enable Set the bind rules. For example, to allow the Directory Manager account to only log in between 6am and 9pm from the host with IP address 192.0.2.1 , enter: # dsconf -D " cn=Directory Manager " ldap://server.example.com plugin root-dn set --open-time= 0600 --close-time= 2100 --allow-ip=" 192.0.2.1 " For the full list of parameters you can set and their descriptions, enter: # dsconf -D " cn=Directory Manager " ldap://server.example.com plugin root-dn set --help Restart the instance: # dsctl instance_name restart Verification Perform a query as cn=Directory Manager from a host that is not allowed or outside of the allowed time range: [[email protected]]USD ldapsearch -D " cn=Directory Manager " -W -H ldap://server.example.com -x -b " dc=example,dc=com " Enter LDAP Password: ldap_bind: Server is unwilling to perform (53) additional info: RootDN access control violation If Directory Server denies access, the plug-in works as expected. 20.3. Configuring the RootDN access control plug-in using the web console By default, the RootDN Access Control plug-in is disabled. To limit permissions of the Directory Manager account, enable and configure the plug-in. Prerequisites You are logged in to the instance in the web console. Procedure Navigate to Plugins RootDN Access Control . Enable the plug-in. Fill the fields according to your requirements. Click Save . Click Actions in the top right corner, and select Restart Instance . Verification Perform a query as cn=Directory Manager from a host that is not allowed or outside of the allowed time range: [[email protected]]USD ldapsearch -D " cn=Directory Manager " -W -H ldap://server.example.com -x -b " dc=example,dc=com " Enter LDAP Password: ldap_bind: Server is unwilling to perform (53) additional info: RootDN access control violation If Directory Server denies access, the plug-in works as expected.	[ "dsconf -D \" cn=Directory Manager \" ldap://server.example.com plugin root-dn enable", "dsconf -D \" cn=Directory Manager \" ldap://server.example.com plugin root-dn set --open-time= 0600 --close-time= 2100 --allow-ip=\" 192.0.2.1 \"", "dsconf -D \" cn=Directory Manager \" ldap://server.example.com plugin root-dn set --help", "dsctl instance_name restart", "[[email protected]]USD ldapsearch -D \" cn=Directory Manager \" -W -H ldap://server.example.com -x -b \" dc=example,dc=com \" Enter LDAP Password: ldap_bind: Server is unwilling to perform (53) additional info: RootDN access control violation", "[[email protected]]USD ldapsearch -D \" cn=Directory Manager \" -W -H ldap://server.example.com -x -b \" dc=example,dc=com \" Enter LDAP Password: ldap_bind: Server is unwilling to perform (53) additional info: RootDN access control violation" ]	https://docs.redhat.com/en/documentation/red_hat_directory_server/12/html/securing_red_hat_directory_server/assembly_setting-access-control-on-the-directory-manager-account_securing-rhds
4.6. iSCSI and DM Multipath overrides	4.6. iSCSI and DM Multipath overrides The recovery_tmo sysfs option controls the timeout for a particular iSCSI device. The following options globally override recovery_tmo values: The replacement_timeout configuration option globally overrides the recovery_tmo value for all iSCSI devices. For all iSCSI devices that are managed by DM Multipath, the fast_io_fail_tmo option in DM Multipath globally overrides the recovery_tmo value. The fast_io_fail_tmo option in DM Multipath also overrides the fast_io_fail_tmo option in Fibre Channel devices. The DM Multipath fast_io_fail_tmo option takes precedence over replacement_timeout . Red Hat does not recommend using replacement_timeout to override recovery_tmo in devices managed by DM Multipath because DM Multipath always resets recovery_tmo when the multipathd service reloads.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/7/html/dm_multipath/iscsi-and-dm-multipath-overrides
F.3. About JBoss Cache	F.3. About JBoss Cache Red Hat JBoss Cache is a tree-structured, clustered, transactional cache that can also be used in a standalone, non-clustered environment. It caches frequently accessed data in-memory to prevent data retrieval or calculation bottlenecks that occur while enterprise features such as Java Transactional API (JTA) compatibility, eviction and persistence are provided. JBoss Cache is the predecessor to Infinispan and Red Hat JBoss Data Grid. Report a bug	null	https://docs.redhat.com/en/documentation/red_hat_data_grid/6.6/html/administration_and_configuration_guide/jboss_cache
Providing feedback on Red Hat documentation	Providing feedback on Red Hat documentation We appreciate your input on our documentation. Do let us know how we can make it better. To give feedback: For simple comments on specific passages: Make sure you are viewing the documentation in the HTML format. In addition, ensure you see the Feedback button in the upper right corner of the document. Use your mouse cursor to highlight the part of text that you want to comment on. Click the Add Feedback pop-up that appears below the highlighted text. Follow the displayed instructions. For submitting more complex feedback, create a Bugzilla ticket: Go to the Bugzilla website. In the Component section, choose documentation . Fill in the Description field with your suggestion for improvement. Include a link to the relevant part(s) of documentation. Click Submit Bug .	null	https://docs.redhat.com/en/documentation/red_hat_openshift_data_foundation/4.9/html/deploying_openshift_data_foundation_using_microsoft_azure/providing-feedback-on-red-hat-documentation_azure
4.323. tftp	4.323. tftp 4.323.1. RHBA-2012:1436 - ftp bug fix update Updated ftp packages that fix three bugs are now available for Red Hat Enterprise Linux 6. The ftp packages provide the standard UNIX command line File Transfer Protocol (FTP) client. FTP is a widely used protocol for transferring files over the Internet, and for archiving files. Bug Fixes BZ# 871059 Previously, the command line width in the ftp client was limited to 200 characters. With this update, the maximum possible length of the FTP command line is extended to 4296 characters. BZ# 871071 Prior to this update, "append", "put", and "send" commands were causing system memory to leak. The memory holding the ftp command was not freed appropriately. With this update, the underlying source code has been improved to correctly free the system resources and the memory leaks are no longer present. BZ# 871546 Previously, if a macro longer than 200 characters was defined and then used after a connection, the ftp client crashed due to a buffer overflow. With this update, the underlying source code was updated and the buffer that holds memory for the macro name was extended. It now matches the length of the command line limit mentioned above. As a result, the ftp client no longer crashes when a macro with a long name is executed. All users of ftp are advised to upgrade to these updated packages, which fix these bugs. 4.323.2. RHBA-2011:1133 - tftp bug fix update Updated tftp packages that fix two bugs are now available for Red Hat Enterprise Linux 6. The Trivial File Transfer Protocol (TFTP) is normally used only for booting diskless workstations. The tftp package provides the user interface for TFTP, which allows users to transfer files to and from a remote machine. The tftp-server package provides the server for TFTP which allows users to transfer files to and from a remote machine. Bug Fixes BZ# 655830 When the small files were transferred and the "-v" option was enabled, the tftp client printed incorrect statistics about the transfer. This update fixes printing of the transfer statistics. BZ# 714240 The tftpd daemon did not correctly handle the utimeout option value. If a client specified a utimeout value within the permitted range, it caused the tftpd process to crash. This crash only affected the current tftp request. All users of tftp and tftp-server should upgrade to these updated packages, which fix these bugs.	null	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/6.2_technical_notes/tftp
Glossary	Glossary 1. A Access Layer The access layer is the interface through which applications submit queries (relational, XML, XQuery or procedural) to the virtual database via JDBC, ODBC or Web services. Admin API The Admin API package, org.teiid.adminapi , provides methods that allow developers to connect to and configure a Red Hat JBoss Data Virtualization instance at runtime from within other applications. Administration Tools The administration tools are a suite of tools made available for administrators to configure and monitor Red Hat JBoss Data Virtualization. AdminShell The AdminShell provides a script-based programming environment enabling users to access, monitor and control Red Hat JBoss Data Virtualization. AdminShell GUI The AdminShell GUI allows users to administer Red Hat JBoss Data Virtualization through the development and running of scripts in a graphical environment. It lets you write scripts using a GUI text editor featuring syntax highlighting. Apache CXF Apache CXF is an open source framework for developing service-oriented architectures (SOAs). CXF lets users build and develop services using frontend programming APIs, like JAX-WS and JAX-RS. These services can use a variety of protocols such as SOAP, XML/HTTP, RESTful HTTP, or CORBA and work over a variety of transports such as HTTP, JMS or JBI. For more information about CXF, refer to http://cxf.apache.org/docs/ 2. B 3. C Cluster A cluster is a group of loosely-connected computers that work together in such a way that they can be viewed as a single system. The components (or nodes) of a cluster are connected to each other through fast local area networks, each node running its own operating system. Clustering middleware orchestrates collaboration between the nodes, allowing users and applications to treat the cluster as a single processor. Clusters are effective for scalable enterprise applications, since performance is improved by adding more nodes as required. Furthermore, if at anytime one node fails, others can take on its load. Checksum Validation Checksum validation is used to ensure a downloaded file has not been corrupted. Checksum validation employs algorithms that compute a fixed-size datum (or checksum) from an arbitrary block of digital data. If two parties compute a checksum of a particular file using the same algorithm, the results will be identical. Therefore, when computing the checksum of a downloaded file using the same algorithm as the supplier, if the checksums match, the integrity of the file is confirmed. If there is a discrepancy, the file has been corrupted in the download process. Connector Development Kit The Connector Development Kit is a Java API that allows users to customize the connector architecture (translators and resource adapters) for specific integration scenarios. Connector Framework Red Hat JBoss Data Virtualization includes a set of translators and resource adapters that enable virtual databases to access their dependent physical data sources. In other words, they provide transparent connectivity between the query engine and the physical data sources. Collectively, this set of translators and adapters is known as the connector framework. You can develop your own custom translators and resource adapters for data sources that are not directly supported by Red Hat JBoss Data Virtualization. 4. D Dashboard The Dashboard builder allows you to connect to virtual databases through the DV JDBC driver to visualize the data for testing and Business Analytics. Data Federation Data Federation refers to the ability of Red Hat JBoss Data Virtualization to integrate multiple data sources so that a single query can return results from one or more data sources. Data Provider Data providers are entities that are configured to connect to a data source (a CSV file or database), collect the required data, and assign them the data type. You can think about them as database queries. The collected data can be then visualized in indicators on pages or exported in a variety of formats such as XLS or CSV. Data Role Data roles are sets of permissions used to control users' access to data. They include read-only and read-write access roles. Data Services Builder The Data Services Builder allows you to build Data Services through the browser. Data Source A data source is a repository for data. Query languages enable users to retrieve and manipulate data stored in these respositories. Database Tool The database tool is used to configure the database used by Red Hat JBoss Data Virtualization. The database in Red Hat JBoss Data Virtualization is required by three items: ModeShape, the Dashboard Builder and the command/audit logging functionality. If you are using Red Hat JBoss Data Virtualization in conjunction with Red Hat JBoss Fuse Service Works, BPEL, and SwitchYard/jBPM integration also make use of this functionality. Design Tools The design tools are available to assist users in setting up Red Hat JBoss Data Virtualization for their desired data integration solution. Distributed Caching Distributed caching extends the traditional concept of caching on single machines to allow caching across multiple servers. Using distributed cache, applications can treat the cache as a single entity, and cache can grow in size and transactional capacity by adding more servers. 5. E Execution Environment The Execution Environment is used to actualize the abstract structures from the underlying data, and expose them through standard APIs. The Data Virtualization query engine is a required part of the execution environment, to optimally federate data from multiple disparate sources. 6. F Failover Failover is automatic switching to a redundant or standby computer server, system, hardware component or network upon the failure or abnormal termination of the previously active application, server, system, hardware component or network. 7. G Governance Governance uses the hierarchical database for storing metadata related to Red Hat JBoss Data Virtualization. 8. H 9. I Interactive AdminShell The interactive AdminShell provides a command-line interface in which users can issue ad hoc script-based commands for simple administration of JBoss Data Virtualization. 10. J JBoss Operations Network JBoss Operations Network (JON) gives administrators a single point of access to view their systems. JON provides a means to develop and monitor a system's inventory. Every managed resource - from platforms to applications to services - is contained and organized in the inventory, no matter how complex the IT environment may be. JBoss Operations Network centralizes all of its operations in an installed server. The JON server communicates with locally installed JON agents. The agents interact directly with the platform and services to carry out local tasks such as monitoring. The types of resources that can be managed by JON and the operations that can be carried out are determined by the server and agent plug-ins which are loaded in JON. The relationships between servers, agents, plug-ins, and resources are what define JBoss Operations Network. 11. K 12. L Load Balancing Load balancing is a computer networking methodology to distribute workload across multiple computers or a computer cluster, network links, central processing units, disk drives, or other resources, to achieve optimal resource utilization, maximize throughput, minimize response time, and avoid overload. Using multiple components with load balancing, instead of a single component, also increases reliability through redundancy. 13. M Management Command Line Interface The Management Command Line Interface (CLI) is a command line administration tool for JBoss EAP 6. Use the Management CLI to start and stop servers, deploy and undeploy applications, configure system settings, and perform other administrative tasks. Operations can be performed in batch mode, allowing multiple tasks to be run as a group. Management Console The Management Console is a web-based administration tool for JBoss EAP 6. Use the Management Console to start and stop servers, deploy and undeploy applications, tune system settings, and make persistent modifications to the server configuration. The Management Console also has the ability to perform administrative tasks, with live notifications when any changes require the server instance to be restarted or reloaded. In a Managed Domain, server instances and server groups in the same domain can be centrally managed from the Management Console of the domain controller. Materialized Views JBoss Data Virtualization supports materialized views. Materialized views are just like other views, but their transformations are pre-computed and stored just like a regular table. When queries are issued against the views through the JBoss Data Virtualization Server, the cached results are used. This saves the cost of accessing all the underlying data sources and re-computing the view transformations each time a query is executed. Materialized views are appropriate when the underlying data does not change rapidly, or when it is acceptable to retrieve data that is "stale" within some period of time, or when it is preferred for end-user queries to access staged data rather than placing additional query load on operational sources. Maven Apache Maven is a distributed build automation tool used in Java application development to build and manage software projects. Maven uses configuration XML files called POM (Project Object Model) to define project properties and manage the build process. POM files describe the project's module and component dependencies, build order, and targets for the resulting project packaging and output. This ensures that projects are built in a correct and uniform manner. Maven uses repositories to store Java libraries, plug-ins, and other build artifacts. Repositories can be either local or remote. A local repository is a download of artifacts from a remote repository cached on a local machine. A remote repository is any other repository accessed using common protocols, such as http:// when located on an HTTP server or file:// when located on a file server. Modeling Environment The Modeling Environment is used to define abstraction layers. 14. N Non-interactive AdminShell The non-interactive AdminShell allows you to administer Red Hat JBoss Data Virtualization by executing previously developed scripts from the command-line. This mode is especially useful to automate testing and to perform repeated configuration/migration changes to a JBoss Data Virtualization instance. 15. O Open Database Connectivity Open Database Connectivity (ODBC) is a standard C programming language middleware API for accessing Database Management Systems (DBMSes). The designers of ODBC aimed to make it independent of database systems and operating systems; an application written using ODBC can be ported to other platforms, both on the client and server side, with few changes to the data access code. 16. P Pages Pages are units that live in a workspace and provide space (dashboard) for panels. By default, you can display a page by selecting it in the Page dropdown menu in the top panel. Every page is divided in two main parts: the lateral menu and the central part of the page. The parts are divided further (the exact division is visible when placing a new panel on a page). Note that the lateral menu allows you to insert panels only below each other, while in the central part of the page you can insert panels below each other as well as tab them. A page also has a customizable header part and logo area. 17. Q Query Engine When applications submit queries to a Virtual Database via the access layer, the query engine produces an optimized query plan to provide efficient access to the required physical data sources as determined by the SQL criteria and the mappings between source and view models in the VDB. This query plan dictates processing order to ensure physical data sources are accessed in the most efficient manner. 18. R Resource Adapters A resource adapter is a deployable Java EE component that provides communication between a Java EE application and an Enterprise Information System (EIS) using the Java Connector Architecture (JCA) specification. A resource adapter is often provided by EIS vendors to allow easy integration of their products with Java EE applications. An Enterprise Information System can be any other software system within an organization. Examples include Enterprise Resource Planning (ERP) systems, database systems, e-mail servers and proprietary messaging systems. A resource adapter is packaged in a Resource Adapter Archive (RAR) file which can be deployed to JBoss EAP 6. A RAR file may also be included in an Enterprise Archive (EAR) deployment. 19. S Server The server is positioned between business applications (consumers) and one or more data sources. An enterprise ready, scalable, manageable, runtime for the Query Engine that runs inside Red Hat JBoss EAP that provides additional security, fault-tolerance and administrative features. Service A Red Hat JBoss Data Virtualization service is positioned between business applications and one or more data sources, and co-ordinates the integration of those data sources for access by the business applications at runtime. Source Model Source Models represent the structure and characteristics of physical data sources and the source model must be associated with a translator and a resource adapter. 20. T Teiid Designer Teiid Designer is a plug-in for Red Hat JBoss Developer Studio, providing a graphical user interface to design and test virtual databases. The Teiid Designer produces Relational, XML and Web Service views. It is designed to resolve semantic differences, create virtual data structures at a physical or logical level and use declarative interfaces to integrate, aggregate, and transform the data from source to a target format for application compatability. Translator In Red Hat JBoss Data Virtualization, a translator provides an abstraction layer between the query engine and the physical data source. This layer converts query commands into source specific commands and executes them using a resource adapter. The translator also converts the result data that comes from the physical source into the form that the query engine requires. 21. U 22. V View Model View Models represent the structure and characteristics you want to expose to your consumers. These view models are used to define a layer of abstraction above the physical layer. This enables information to be presented to consumers as a business model rather than as a representation of how it is physically stored. The views are defined using transformations between models. The business views can be in a variety of forms: relational, XML or Web Services. Virtual Database A virtual database (VDB) is a container for components that integrate data from multiple disparate data sources, allowing applications to access and query the data as if it is in a single database and, therefore, using a single uniform API. A VDB is composed of various data models and configuration information that describes which data sources are to be integrated and how. In particular, source models are used to represent the structure and characteristics of the physical data sources, and view models represent the structure and characteristics of the integrated data exposed to applications. 23. W Workspace A workspace is a container for pages with panels or indicators. Every workspace uses a particular skin and envelope, which define the workspace's graphical properties. By default, the Showcase workspace is available. 24. X 25. Y 26. Z	null	https://docs.redhat.com/en/documentation/red_hat_jboss_data_virtualization/6.4/html/glossary_guide/glossary
Chapter 6. Working with nodes	Chapter 6. Working with nodes 6.1. Viewing and listing the nodes in your OpenShift Container Platform cluster You can list all the nodes in your cluster to obtain information such as status, age, memory usage, and details about the nodes. When you perform node management operations, the CLI interacts with node objects that are representations of actual node hosts. The master uses the information from node objects to validate nodes with health checks. 6.1.1. About listing all the nodes in a cluster You can get detailed information on the nodes in the cluster. The following command lists all nodes: USD oc get nodes The following example is a cluster with healthy nodes: USD oc get nodes Example output NAME STATUS ROLES AGE VERSION master.example.com Ready master 7h v1.29.4 node1.example.com Ready worker 7h v1.29.4 node2.example.com Ready worker 7h v1.29.4 The following example is a cluster with one unhealthy node: USD oc get nodes Example output NAME STATUS ROLES AGE VERSION master.example.com Ready master 7h v1.29.4 node1.example.com NotReady,SchedulingDisabled worker 7h v1.29.4 node2.example.com Ready worker 7h v1.29.4 The conditions that trigger a NotReady status are shown later in this section. The -o wide option provides additional information on nodes. USD oc get nodes -o wide Example output NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME master.example.com Ready master 171m v1.29.4 10.0.129.108 <none> Red Hat Enterprise Linux CoreOS 48.83.202103210901-0 (Ootpa) 4.18.0-240.15.1.el8_3.x86_64 cri-o://1.29.4-30.rhaos4.10.gitf2f339d.el8-dev node1.example.com Ready worker 72m v1.29.4 10.0.129.222 <none> Red Hat Enterprise Linux CoreOS 48.83.202103210901-0 (Ootpa) 4.18.0-240.15.1.el8_3.x86_64 cri-o://1.29.4-30.rhaos4.10.gitf2f339d.el8-dev node2.example.com Ready worker 164m v1.29.4 10.0.142.150 <none> Red Hat Enterprise Linux CoreOS 48.83.202103210901-0 (Ootpa) 4.18.0-240.15.1.el8_3.x86_64 cri-o://1.29.4-30.rhaos4.10.gitf2f339d.el8-dev The following command lists information about a single node: USD oc get node <node> For example: USD oc get node node1.example.com Example output NAME STATUS ROLES AGE VERSION node1.example.com Ready worker 7h v1.29.4 The following command provides more detailed information about a specific node, including the reason for the current condition: USD oc describe node <node> For example: USD oc describe node node1.example.com Note The following example contains some values that are specific to OpenShift Container Platform on AWS. Example output Name: node1.example.com 1 Roles: worker 2 Labels: kubernetes.io/os=linux kubernetes.io/hostname=ip-10-0-131-14 kubernetes.io/arch=amd64 3 node-role.kubernetes.io/worker= node.kubernetes.io/instance-type=m4.large node.openshift.io/os_id=rhcos node.openshift.io/os_version=4.5 region=east topology.kubernetes.io/region=us-east-1 topology.kubernetes.io/zone=us-east-1a Annotations: cluster.k8s.io/machine: openshift-machine-api/ahardin-worker-us-east-2a-q5dzc 4 machineconfiguration.openshift.io/currentConfig: worker-309c228e8b3a92e2235edd544c62fea8 machineconfiguration.openshift.io/desiredConfig: worker-309c228e8b3a92e2235edd544c62fea8 machineconfiguration.openshift.io/state: Done volumes.kubernetes.io/controller-managed-attach-detach: true CreationTimestamp: Wed, 13 Feb 2019 11:05:57 -0500 Taints: <none> 5 Unschedulable: false Conditions: 6 Type Status LastHeartbeatTime LastTransitionTime Reason Message ---- ------ ----------------- ------------------ ------ ------- OutOfDisk False Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:05:57 -0500 KubeletHasSufficientDisk kubelet has sufficient disk space available MemoryPressure False Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:05:57 -0500 KubeletHasSufficientMemory kubelet has sufficient memory available DiskPressure False Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:05:57 -0500 KubeletHasNoDiskPressure kubelet has no disk pressure PIDPressure False Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:05:57 -0500 KubeletHasSufficientPID kubelet has sufficient PID available Ready True Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:07:09 -0500 KubeletReady kubelet is posting ready status Addresses: 7 InternalIP: 10.0.140.16 InternalDNS: ip-10-0-140-16.us-east-2.compute.internal Hostname: ip-10-0-140-16.us-east-2.compute.internal Capacity: 8 attachable-volumes-aws-ebs: 39 cpu: 2 hugepages-1Gi: 0 hugepages-2Mi: 0 memory: 8172516Ki pods: 250 Allocatable: attachable-volumes-aws-ebs: 39 cpu: 1500m hugepages-1Gi: 0 hugepages-2Mi: 0 memory: 7558116Ki pods: 250 System Info: 9 Machine ID: 63787c9534c24fde9a0cde35c13f1f66 System UUID: EC22BF97-A006-4A58-6AF8-0A38DEEA122A Boot ID: f24ad37d-2594-46b4-8830-7f7555918325 Kernel Version: 3.10.0-957.5.1.el7.x86_64 OS Image: Red Hat Enterprise Linux CoreOS 410.8.20190520.0 (Ootpa) Operating System: linux Architecture: amd64 Container Runtime Version: cri-o://1.29.4-0.6.dev.rhaos4.3.git9ad059b.el8-rc2 Kubelet Version: v1.29.4 Kube-Proxy Version: v1.29.4 PodCIDR: 10.128.4.0/24 ProviderID: aws:///us-east-2a/i-04e87b31dc6b3e171 Non-terminated Pods: (12 in total) 10 Namespace Name CPU Requests CPU Limits Memory Requests Memory Limits --------- ---- ------------ ---------- --------------- ------------- openshift-cluster-node-tuning-operator tuned-hdl5q 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-dns dns-default-l69zr 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-image-registry node-ca-9hmcg 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-ingress router-default-76455c45c-c5ptv 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-machine-config-operator machine-config-daemon-cvqw9 20m (1%) 0 (0%) 50Mi (0%) 0 (0%) openshift-marketplace community-operators-f67fh 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-monitoring alertmanager-main-0 50m (3%) 50m (3%) 210Mi (2%) 10Mi (0%) openshift-monitoring node-exporter-l7q8d 10m (0%) 20m (1%) 20Mi (0%) 40Mi (0%) openshift-monitoring prometheus-adapter-75d769c874-hvb85 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-multus multus-kw8w5 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-sdn ovs-t4dsn 100m (6%) 0 (0%) 300Mi (4%) 0 (0%) openshift-sdn sdn-g79hg 100m (6%) 0 (0%) 200Mi (2%) 0 (0%) Allocated resources: (Total limits may be over 100 percent, i.e., overcommitted.) Resource Requests Limits -------- -------- ------ cpu 380m (25%) 270m (18%) memory 880Mi (11%) 250Mi (3%) attachable-volumes-aws-ebs 0 0 Events: 11 Type Reason Age From Message ---- ------ ---- ---- ------- Normal NodeHasSufficientPID 6d (x5 over 6d) kubelet, m01.example.com Node m01.example.com status is now: NodeHasSufficientPID Normal NodeAllocatableEnforced 6d kubelet, m01.example.com Updated Node Allocatable limit across pods Normal NodeHasSufficientMemory 6d (x6 over 6d) kubelet, m01.example.com Node m01.example.com status is now: NodeHasSufficientMemory Normal NodeHasNoDiskPressure 6d (x6 over 6d) kubelet, m01.example.com Node m01.example.com status is now: NodeHasNoDiskPressure Normal NodeHasSufficientDisk 6d (x6 over 6d) kubelet, m01.example.com Node m01.example.com status is now: NodeHasSufficientDisk Normal NodeHasSufficientPID 6d kubelet, m01.example.com Node m01.example.com status is now: NodeHasSufficientPID Normal Starting 6d kubelet, m01.example.com Starting kubelet. #... 1 The name of the node. 2 The role of the node, either master or worker . 3 The labels applied to the node. 4 The annotations applied to the node. 5 The taints applied to the node. 6 The node conditions and status. The conditions stanza lists the Ready , PIDPressure , MemoryPressure , DiskPressure and OutOfDisk status. These condition are described later in this section. 7 The IP address and hostname of the node. 8 The pod resources and allocatable resources. 9 Information about the node host. 10 The pods on the node. 11 The events reported by the node. Note The control plane label is not automatically added to newly created or updated master nodes. If you want to use the control plane label for your nodes, you can manually configure the label. For more information, see Understanding how to update labels on nodes in the Additional resources section. Among the information shown for nodes, the following node conditions appear in the output of the commands shown in this section: Table 6.1. Node Conditions Condition Description Ready If true , the node is healthy and ready to accept pods. If false , the node is not healthy and is not accepting pods. If unknown , the node controller has not received a heartbeat from the node for the node-monitor-grace-period (the default is 40 seconds). DiskPressure If true , the disk capacity is low. MemoryPressure If true , the node memory is low. PIDPressure If true , there are too many processes on the node. OutOfDisk If true , the node has insufficient free space on the node for adding new pods. NetworkUnavailable If true , the network for the node is not correctly configured. NotReady If true , one of the underlying components, such as the container runtime or network, is experiencing issues or is not yet configured. SchedulingDisabled Pods cannot be scheduled for placement on the node. Additional resources Understanding how to update labels on nodes 6.1.2. Listing pods on a node in your cluster You can list all the pods on a specific node. Procedure To list all or selected pods on selected nodes: USD oc get pod --selector=<nodeSelector> USD oc get pod --selector=kubernetes.io/os Or: USD oc get pod -l=<nodeSelector> USD oc get pod -l kubernetes.io/os=linux To list all pods on a specific node, including terminated pods: USD oc get pod --all-namespaces --field-selector=spec.nodeName=<nodename> 6.1.3. Viewing memory and CPU usage statistics on your nodes You can display usage statistics about nodes, which provide the runtime environments for containers. These usage statistics include CPU, memory, and storage consumption. Prerequisites You must have cluster-reader permission to view the usage statistics. Metrics must be installed to view the usage statistics. Procedure To view the usage statistics: USD oc adm top nodes Example output NAME CPU(cores) CPU% MEMORY(bytes) MEMORY% ip-10-0-12-143.ec2.compute.internal 1503m 100% 4533Mi 61% ip-10-0-132-16.ec2.compute.internal 76m 5% 1391Mi 18% ip-10-0-140-137.ec2.compute.internal 398m 26% 2473Mi 33% ip-10-0-142-44.ec2.compute.internal 656m 43% 6119Mi 82% ip-10-0-146-165.ec2.compute.internal 188m 12% 3367Mi 45% ip-10-0-19-62.ec2.compute.internal 896m 59% 5754Mi 77% ip-10-0-44-193.ec2.compute.internal 632m 42% 5349Mi 72% To view the usage statistics for nodes with labels: USD oc adm top node --selector='' You must choose the selector (label query) to filter on. Supports = , == , and != . 6.2. Working with nodes As an administrator, you can perform several tasks to make your clusters more efficient. 6.2.1. Understanding how to evacuate pods on nodes Evacuating pods allows you to migrate all or selected pods from a given node or nodes. You can only evacuate pods backed by a replication controller. The replication controller creates new pods on other nodes and removes the existing pods from the specified node(s). Bare pods, meaning those not backed by a replication controller, are unaffected by default. You can evacuate a subset of pods by specifying a pod-selector. Pod selectors are based on labels, so all the pods with the specified label will be evacuated. Procedure Mark the nodes unschedulable before performing the pod evacuation. Mark the node as unschedulable: USD oc adm cordon <node1> Example output node/<node1> cordoned Check that the node status is Ready,SchedulingDisabled : USD oc get node <node1> Example output NAME STATUS ROLES AGE VERSION <node1> Ready,SchedulingDisabled worker 1d v1.29.4 Evacuate the pods using one of the following methods: Evacuate all or selected pods on one or more nodes: USD oc adm drain <node1> <node2> [--pod-selector=<pod_selector>] Force the deletion of bare pods using the --force option. When set to true , deletion continues even if there are pods not managed by a replication controller, replica set, job, daemon set, or stateful set: USD oc adm drain <node1> <node2> --force=true Set a period of time in seconds for each pod to terminate gracefully, use --grace-period . If negative, the default value specified in the pod will be used: USD oc adm drain <node1> <node2> --grace-period=-1 Ignore pods managed by daemon sets using the --ignore-daemonsets flag set to true : USD oc adm drain <node1> <node2> --ignore-daemonsets=true Set the length of time to wait before giving up using the --timeout flag. A value of 0 sets an infinite length of time: USD oc adm drain <node1> <node2> --timeout=5s Delete pods even if there are pods using emptyDir volumes by setting the --delete-emptydir-data flag to true . Local data is deleted when the node is drained: USD oc adm drain <node1> <node2> --delete-emptydir-data=true List objects that will be migrated without actually performing the evacuation, using the --dry-run option set to true : USD oc adm drain <node1> <node2> --dry-run=true Instead of specifying specific node names (for example, <node1> <node2> ), you can use the --selector=<node_selector> option to evacuate pods on selected nodes. Mark the node as schedulable when done. USD oc adm uncordon <node1> 6.2.2. Understanding how to update labels on nodes You can update any label on a node. Node labels are not persisted after a node is deleted even if the node is backed up by a Machine. Note Any change to a MachineSet object is not applied to existing machines owned by the compute machine set. For example, labels edited or added to an existing MachineSet object are not propagated to existing machines and nodes associated with the compute machine set. The following command adds or updates labels on a node: USD oc label node <node> <key_1>=<value_1> ... <key_n>=<value_n> For example: USD oc label nodes webconsole-7f7f6 unhealthy=true Tip You can alternatively apply the following YAML to apply the label: kind: Node apiVersion: v1 metadata: name: webconsole-7f7f6 labels: unhealthy: 'true' #... The following command updates all pods in the namespace: USD oc label pods --all <key_1>=<value_1> For example: USD oc label pods --all status=unhealthy 6.2.3. Understanding how to mark nodes as unschedulable or schedulable By default, healthy nodes with a Ready status are marked as schedulable, which means that you can place new pods on the node. Manually marking a node as unschedulable blocks any new pods from being scheduled on the node. Existing pods on the node are not affected. The following command marks a node or nodes as unschedulable: Example output USD oc adm cordon <node> For example: USD oc adm cordon node1.example.com Example output node/node1.example.com cordoned NAME LABELS STATUS node1.example.com kubernetes.io/hostname=node1.example.com Ready,SchedulingDisabled The following command marks a currently unschedulable node or nodes as schedulable: USD oc adm uncordon <node1> Alternatively, instead of specifying specific node names (for example, <node> ), you can use the --selector=<node_selector> option to mark selected nodes as schedulable or unschedulable. 6.2.4. Handling errors in single-node OpenShift clusters when the node reboots without draining application pods In single-node OpenShift clusters and in OpenShift Container Platform clusters in general, a situation can arise where a node reboot occurs without first draining the node. This can occur where an application pod requesting devices fails with the UnexpectedAdmissionError error. Deployment , ReplicaSet , or DaemonSet errors are reported because the application pods that require those devices start before the pod serving those devices. You cannot control the order of pod restarts. While this behavior is to be expected, it can cause a pod to remain on the cluster even though it has failed to deploy successfully. The pod continues to report UnexpectedAdmissionError . This issue is mitigated by the fact that application pods are typically included in a Deployment , ReplicaSet , or DaemonSet . If a pod is in this error state, it is of little concern because another instance should be running. Belonging to a Deployment , ReplicaSet , or DaemonSet guarantees the successful creation and execution of subsequent pods and ensures the successful deployment of the application. There is ongoing work upstream to ensure that such pods are gracefully terminated. Until that work is resolved, run the following command for a single-node OpenShift cluster to remove the failed pods: USD oc delete pods --field-selector status.phase=Failed -n <POD_NAMESPACE> Note The option to drain the node is unavailable for single-node OpenShift clusters. Additional resources Understanding how to evacuate pods on nodes 6.2.5. Deleting nodes 6.2.5.1. Deleting nodes from a cluster To delete a node from the OpenShift Container Platform cluster, scale down the appropriate MachineSet object. Important When a cluster is integrated with a cloud provider, you must delete the corresponding machine to delete a node. Do not try to use the oc delete node command for this task. When you delete a node by using the CLI, the node object is deleted in Kubernetes, but the pods that exist on the node are not deleted. Any bare pods that are not backed by a replication controller become inaccessible to OpenShift Container Platform. Pods backed by replication controllers are rescheduled to other available nodes. You must delete local manifest pods. Note If you are running cluster on bare metal, you cannot delete a node by editing MachineSet objects. Compute machine sets are only available when a cluster is integrated with a cloud provider. Instead you must unschedule and drain the node before manually deleting it. Procedure View the compute machine sets that are in the cluster by running the following command: USD oc get machinesets -n openshift-machine-api The compute machine sets are listed in the form of <cluster-id>-worker-<aws-region-az> . Scale down the compute machine set by using one of the following methods: Specify the number of replicas to scale down to by running the following command: USD oc scale --replicas=2 machineset <machine-set-name> -n openshift-machine-api Edit the compute machine set custom resource by running the following command: USD oc edit machineset <machine-set-name> -n openshift-machine-api Example output apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: # ... name: <machine-set-name> namespace: openshift-machine-api # ... spec: replicas: 2 1 # ... 1 Specify the number of replicas to scale down to. Additional resources Manually scaling a compute machine set 6.2.5.2. Deleting nodes from a bare metal cluster When you delete a node using the CLI, the node object is deleted in Kubernetes, but the pods that exist on the node are not deleted. Any bare pods not backed by a replication controller become inaccessible to OpenShift Container Platform. Pods backed by replication controllers are rescheduled to other available nodes. You must delete local manifest pods. Procedure Delete a node from an OpenShift Container Platform cluster running on bare metal by completing the following steps: Mark the node as unschedulable: USD oc adm cordon <node_name> Drain all pods on the node: USD oc adm drain <node_name> --force=true This step might fail if the node is offline or unresponsive. Even if the node does not respond, it might still be running a workload that writes to shared storage. To avoid data corruption, power down the physical hardware before you proceed. Delete the node from the cluster: USD oc delete node <node_name> Although the node object is now deleted from the cluster, it can still rejoin the cluster after reboot or if the kubelet service is restarted. To permanently delete the node and all its data, you must decommission the node . If you powered down the physical hardware, turn it back on so that the node can rejoin the cluster. 6.3. Managing nodes OpenShift Container Platform uses a KubeletConfig custom resource (CR) to manage the configuration of nodes. By creating an instance of a KubeletConfig object, a managed machine config is created to override setting on the node. Note Logging in to remote machines for the purpose of changing their configuration is not supported. 6.3.1. Modifying nodes To make configuration changes to a cluster, or machine pool, you must create a custom resource definition (CRD), or kubeletConfig object. OpenShift Container Platform uses the Machine Config Controller to watch for changes introduced through the CRD to apply the changes to the cluster. Note Because the fields in a kubeletConfig object are passed directly to the kubelet from upstream Kubernetes, the validation of those fields is handled directly by the kubelet itself. Please refer to the relevant Kubernetes documentation for the valid values for these fields. Invalid values in the kubeletConfig object can render cluster nodes unusable. Procedure Obtain the label associated with the static CRD, Machine Config Pool, for the type of node you want to configure. Perform one of the following steps: Check current labels of the desired machine config pool. For example: USD oc get machineconfigpool --show-labels Example output NAME CONFIG UPDATED UPDATING DEGRADED LABELS master rendered-master-e05b81f5ca4db1d249a1bf32f9ec24fd True False False operator.machineconfiguration.openshift.io/required-for-upgrade= worker rendered-worker-f50e78e1bc06d8e82327763145bfcf62 True False False Add a custom label to the desired machine config pool. For example: USD oc label machineconfigpool worker custom-kubelet=enabled Create a kubeletconfig custom resource (CR) for your configuration change. For example: Sample configuration for a custom-config CR apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: custom-config 1 spec: machineConfigPoolSelector: matchLabels: custom-kubelet: enabled 2 kubeletConfig: 3 podsPerCore: 10 maxPods: 250 systemReserved: cpu: 2000m memory: 1Gi #... 1 Assign a name to CR. 2 Specify the label to apply the configuration change, this is the label you added to the machine config pool. 3 Specify the new value(s) you want to change. Create the CR object. USD oc create -f <file-name> For example: USD oc create -f master-kube-config.yaml Most Kubelet Configuration options can be set by the user. The following options are not allowed to be overwritten: CgroupDriver ClusterDNS ClusterDomain StaticPodPath Note If a single node contains more than 50 images, pod scheduling might be imbalanced across nodes. This is because the list of images on a node is shortened to 50 by default. You can disable the image limit by editing the KubeletConfig object and setting the value of nodeStatusMaxImages to -1 . 6.3.2. Updating boot images The Machine Config Operator (MCO) uses a boot image to bring up a Red Hat Enterprise Linux CoreOS (RHCOS) node. By default, OpenShift Container Platform does not manage the boot image. This means that the boot image in your cluster is not updated along with your cluster. For example, if your cluster was originally created with OpenShift Container Platform 4.12, the boot image that the cluster uses to create nodes is the same 4.12 version, even if your cluster is at a later version. If the cluster is later upgraded to 4.13 or later, new nodes continue to scale with the same 4.12 image. This process could cause the following issues: Extra time to start up nodes Certificate expiration issues Version skew issues To avoid these issues, you can configure your cluster to update the boot image whenever you update your cluster. By modifying the MachineConfiguration object, you can enable this feature. Currently, the ability to update the boot image is available for only Google Cloud Platform (GCP) clusters and is not supported for Cluster CAPI Operator managed clusters. Important The updating boot image feature is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . To view the current boot image used in your cluster, examine a machine set: Example machine set with the boot image reference apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: ci-ln-hmy310k-72292-5f87z-worker-a namespace: openshift-machine-api spec: # ... template: # ... spec: # ... providerSpec: # ... value: disks: - autoDelete: true boot: true image: projects/rhcos-cloud/global/images/rhcos-412-85-202203181601-0-gcp-x86-64 1 # ... 1 This boot image is the same as the originally-installed OpenShift Container Platform version, in this example OpenShift Container Platform 4.12, regardless of the current version of the cluster. The way that the boot image is represented in the machine set depends on the platform, as the structure of the providerSpec field differs from platform to platform. If you configure your cluster to update your boot images, the boot image referenced in your machine sets matches the current version of the cluster. Prerequisites You have enabled the TechPreviewNoUpgrade feature set by using the feature gates. For more information, see "Enabling features using feature gates" in the "Additional resources" section. Procedure Edit the MachineConfiguration object, named cluster , to enable the updating of boot images by running the following command: USD oc edit MachineConfiguration cluster Optional: Configure the boot image update feature for all the machine sets: apiVersion: operator.openshift.io/v1 kind: MachineConfiguration metadata: name: cluster namespace: openshift-machine-config-operator spec: # ... managedBootImages: 1 machineManagers: - resource: machinesets apiGroup: machine.openshift.io selection: mode: All 2 1 Activates the boot image update feature. 2 Specifies that all the machine sets in the cluster are to be updated. Optional: Configure the boot image update feature for specific machine sets: apiVersion: operator.openshift.io/v1 kind: MachineConfiguration metadata: name: cluster namespace: openshift-machine-config-operator spec: # ... managedBootImages: 1 machineManagers: - resource: machinesets apiGroup: machine.openshift.io selection: mode: Partial partial: machineResourceSelector: matchLabels: update-boot-image: "true" 2 1 Activates the boot image update feature. 2 Specifies that any machine set with this label is to be updated. Tip If an appropriate label is not present on the machine set, add a key/value pair by running a command similar to following: Verification Get the boot image version by running the following command: USD oc get machinesets <machineset_name> -n openshift-machine-api -o yaml Example machine set with the boot image reference apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: labels: machine.openshift.io/cluster-api-cluster: ci-ln-77hmkpt-72292-d4pxp update-boot-image: "true" name: ci-ln-77hmkpt-72292-d4pxp-worker-a namespace: openshift-machine-api spec: # ... template: # ... spec: # ... providerSpec: # ... value: disks: - autoDelete: true boot: true image: projects/rhcos-cloud/global/images/rhcos-416-92-202402201450-0-gcp-x86-64 1 # ... 1 This boot image is the same as the current OpenShift Container Platform version. Additional resources Enabling features using feature gates 6.3.2.1. Disabling updated boot images To disable the updated boot image feature, edit the MachineConfiguration object to remove the managedBootImages stanza. If you disable this feature after some nodes have been created with the new boot image version, any existing nodes retain their current boot image. Turning off this feature does not rollback the nodes or machine sets to the originally-installed boot image. The machine sets retain the boot image version that was present when the feature was enabled and is not updated again when the cluster is upgraded to a new OpenShift Container Platform version in the future. Procedure Disable updated boot images by editing the MachineConfiguration object: USD oc edit MachineConfiguration cluster Remove the managedBootImages stanza: apiVersion: operator.openshift.io/v1 kind: MachineConfiguration metadata: name: cluster namespace: openshift-machine-config-operator spec: # ... managedBootImages: 1 machineManagers: - resource: machinesets apiGroup: machine.openshift.io selection: mode: All 1 Remove the entire stanza to disable updated boot images. 6.3.3. Configuring control plane nodes as schedulable You can configure control plane nodes to be schedulable, meaning that new pods are allowed for placement on the master nodes. By default, control plane nodes are not schedulable. You can set the masters to be schedulable, but must retain the worker nodes. Note You can deploy OpenShift Container Platform with no worker nodes on a bare metal cluster. In this case, the control plane nodes are marked schedulable by default. You can allow or disallow control plane nodes to be schedulable by configuring the mastersSchedulable field. Important When you configure control plane nodes from the default unschedulable to schedulable, additional subscriptions are required. This is because control plane nodes then become worker nodes. Procedure Edit the schedulers.config.openshift.io resource. USD oc edit schedulers.config.openshift.io cluster Configure the mastersSchedulable field. apiVersion: config.openshift.io/v1 kind: Scheduler metadata: creationTimestamp: "2019-09-10T03:04:05Z" generation: 1 name: cluster resourceVersion: "433" selfLink: /apis/config.openshift.io/v1/schedulers/cluster uid: a636d30a-d377-11e9-88d4-0a60097bee62 spec: mastersSchedulable: false 1 status: {} #... 1 Set to true to allow control plane nodes to be schedulable, or false to disallow control plane nodes to be schedulable. Save the file to apply the changes. 6.3.4. Setting SELinux booleans OpenShift Container Platform allows you to enable and disable an SELinux boolean on a Red Hat Enterprise Linux CoreOS (RHCOS) node. The following procedure explains how to modify SELinux booleans on nodes using the Machine Config Operator (MCO). This procedure uses container_manage_cgroup as the example boolean. You can modify this value to whichever boolean you need. Prerequisites You have installed the OpenShift CLI (oc). Procedure Create a new YAML file with a MachineConfig object, displayed in the following example: apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: worker name: 99-worker-setsebool spec: config: ignition: version: 3.2.0 systemd: units: - contents: \| [Unit] Description=Set SELinux booleans Before=kubelet.service [Service] Type=oneshot ExecStart=/sbin/setsebool container_manage_cgroup=on RemainAfterExit=true [Install] WantedBy=multi-user.target graphical.target enabled: true name: setsebool.service #... Create the new MachineConfig object by running the following command: USD oc create -f 99-worker-setsebool.yaml Note Applying any changes to the MachineConfig object causes all affected nodes to gracefully reboot after the change is applied. 6.3.5. Adding kernel arguments to nodes In some special cases, you might want to add kernel arguments to a set of nodes in your cluster. This should only be done with caution and clear understanding of the implications of the arguments you set. Warning Improper use of kernel arguments can result in your systems becoming unbootable. Examples of kernel arguments you could set include: nosmt : Disables symmetric multithreading (SMT) in the kernel. Multithreading allows multiple logical threads for each CPU. You could consider nosmt in multi-tenant environments to reduce risks from potential cross-thread attacks. By disabling SMT, you essentially choose security over performance. systemd.unified_cgroup_hierarchy : Enables Linux control group version 2 (cgroup v2). cgroup v2 is the version of the kernel control group and offers multiple improvements. Important cgroup v1 is a deprecated feature. Deprecated functionality is still included in OpenShift Container Platform and continues to be supported; however, it will be removed in a future release of this product and is not recommended for new deployments. For the most recent list of major functionality that has been deprecated or removed within OpenShift Container Platform, refer to the Deprecated and removed features section of the OpenShift Container Platform release notes. enforcing=0 : Configures Security Enhanced Linux (SELinux) to run in permissive mode. In permissive mode, the system acts as if SELinux is enforcing the loaded security policy, including labeling objects and emitting access denial entries in the logs, but it does not actually deny any operations. While not supported for production systems, permissive mode can be helpful for debugging. Warning Disabling SELinux on RHCOS in production is not supported. Once SELinux has been disabled on a node, it must be re-provisioned before re-inclusion in a production cluster. See Kernel.org kernel parameters for a list and descriptions of kernel arguments. In the following procedure, you create a MachineConfig object that identifies: A set of machines to which you want to add the kernel argument. In this case, machines with a worker role. Kernel arguments that are appended to the end of the existing kernel arguments. A label that indicates where in the list of machine configs the change is applied. Prerequisites Have administrative privilege to a working OpenShift Container Platform cluster. Procedure List existing MachineConfig objects for your OpenShift Container Platform cluster to determine how to label your machine config: USD oc get MachineConfig Example output NAME GENERATEDBYCONTROLLER IGNITIONVERSION AGE 00-master 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 00-worker 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-ssh 3.2.0 40m 99-worker-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-worker-ssh 3.2.0 40m rendered-master-23e785de7587df95a4b517e0647e5ab7 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m rendered-worker-5d596d9293ca3ea80c896a1191735bb1 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m Create a MachineConfig object file that identifies the kernel argument (for example, 05-worker-kernelarg-selinuxpermissive.yaml ) apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: worker 1 name: 05-worker-kernelarg-selinuxpermissive 2 spec: kernelArguments: - enforcing=0 3 1 Applies the new kernel argument only to worker nodes. 2 Named to identify where it fits among the machine configs (05) and what it does (adds a kernel argument to configure SELinux permissive mode). 3 Identifies the exact kernel argument as enforcing=0 . Create the new machine config: USD oc create -f 05-worker-kernelarg-selinuxpermissive.yaml Check the machine configs to see that the new one was added: USD oc get MachineConfig Example output NAME GENERATEDBYCONTROLLER IGNITIONVERSION AGE 00-master 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 00-worker 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 05-worker-kernelarg-selinuxpermissive 3.2.0 105s 99-master-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-ssh 3.2.0 40m 99-worker-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-worker-ssh 3.2.0 40m rendered-master-23e785de7587df95a4b517e0647e5ab7 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m rendered-worker-5d596d9293ca3ea80c896a1191735bb1 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m Check the nodes: USD oc get nodes Example output NAME STATUS ROLES AGE VERSION ip-10-0-136-161.ec2.internal Ready worker 28m v1.29.4 ip-10-0-136-243.ec2.internal Ready master 34m v1.29.4 ip-10-0-141-105.ec2.internal Ready,SchedulingDisabled worker 28m v1.29.4 ip-10-0-142-249.ec2.internal Ready master 34m v1.29.4 ip-10-0-153-11.ec2.internal Ready worker 28m v1.29.4 ip-10-0-153-150.ec2.internal Ready master 34m v1.29.4 You can see that scheduling on each worker node is disabled as the change is being applied. Check that the kernel argument worked by going to one of the worker nodes and listing the kernel command line arguments (in /proc/cmdline on the host): USD oc debug node/ip-10-0-141-105.ec2.internal Example output Starting pod/ip-10-0-141-105ec2internal-debug ... To use host binaries, run `chroot /host` sh-4.2# cat /host/proc/cmdline BOOT_IMAGE=/ostree/rhcos-... console=tty0 console=ttyS0,115200n8 rootflags=defaults,prjquota rw root=UUID=fd0... ostree=/ostree/boot.0/rhcos/16... coreos.oem.id=qemu coreos.oem.id=ec2 ignition.platform.id=ec2 enforcing=0 sh-4.2# exit You should see the enforcing=0 argument added to the other kernel arguments. 6.3.6. Enabling swap memory use on nodes Important Enabling swap memory use on nodes is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . Note Enabling swap memory is only available for container-native virtualization (CNV) users or use cases. Warning Enabling swap memory can negatively impact workload performance and out-of-resource handling. Do not enable swap memory on control plane nodes. To enable swap memory, create a kubeletconfig custom resource (CR) to set the swapbehavior parameter. You can set limited or unlimited swap memory: Limited: Use the LimitedSwap value to limit how much swap memory workloads can use. Any workloads on the node that are not managed by OpenShift Container Platform can still use swap memory. The LimitedSwap behavior depends on whether the node is running with Linux control groups version 1 (cgroups v1) or version 2 (cgroup v2) : cgroup v1: OpenShift Container Platform workloads can use any combination of memory and swap, up to the pod's memory limit, if set. cgroup v2: OpenShift Container Platform workloads cannot use swap memory. Unlimited: Use the UnlimitedSwap value to allow workloads to use as much swap memory as they request, up to the system limit. Because the kubelet will not start in the presence of swap memory without this configuration, you must enable swap memory in OpenShift Container Platform before enabling swap memory on the nodes. If there is no swap memory present on a node, enabling swap memory in OpenShift Container Platform has no effect. Prerequisites You have a running OpenShift Container Platform cluster that uses version 4.10 or later. You are logged in to the cluster as a user with administrative privileges. You have enabled the TechPreviewNoUpgrade feature set on the cluster (see Nodes Working with clusters Enabling features using feature gates ). Note Enabling the TechPreviewNoUpgrade feature set cannot be undone and prevents minor version updates. These feature sets are not recommended on production clusters. If cgroup v2 is enabled on a node, you must enable swap accounting on the node, by setting the swapaccount=1 kernel argument. Procedure Apply a custom label to the machine config pool where you want to allow swap memory. USD oc label machineconfigpool worker kubelet-swap=enabled Create a custom resource (CR) to enable and configure swap settings. apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: swap-config spec: machineConfigPoolSelector: matchLabels: kubelet-swap: enabled kubeletConfig: failSwapOn: false 1 memorySwap: swapBehavior: LimitedSwap 2 #... 1 Set to false to enable swap memory use on the associated nodes. Set to true to disable swap memory use. 2 Specify the swap memory behavior. If unspecified, the default is LimitedSwap . Enable swap memory on the machines. 6.3.7. Migrating control plane nodes from one RHOSP host to another manually If control plane machine sets are not enabled on your cluster, you can run a script that moves a control plane node from one Red Hat OpenStack Platform (RHOSP) node to another. Note Control plane machine sets are not enabled on clusters that run on user-provisioned infrastructure. For information about control plane machine sets, see "Managing control plane machines with control plane machine sets". Prerequisites The environment variable OS_CLOUD refers to a clouds entry that has administrative credentials in a clouds.yaml file. The environment variable KUBECONFIG refers to a configuration that contains administrative OpenShift Container Platform credentials. Procedure From a command line, run the following script: #!/usr/bin/env bash set -Eeuo pipefail if [ USD# -lt 1 ]; then echo "Usage: 'USD0 node_name'" exit 64 fi # Check for admin OpenStack credentials openstack server list --all-projects >/dev/null \|\| { >&2 echo "The script needs OpenStack admin credentials. Exiting"; exit 77; } # Check for admin OpenShift credentials oc adm top node >/dev/null \|\| { >&2 echo "The script needs OpenShift admin credentials. Exiting"; exit 77; } set -x declare -r node_name="USD1" declare server_id server_id="USD(openstack server list --all-projects -f value -c ID -c Name \| grep "USDnode_name" \| cut -d' ' -f1)" readonly server_id # Drain the node oc adm cordon "USDnode_name" oc adm drain "USDnode_name" --delete-emptydir-data --ignore-daemonsets --force # Power off the server oc debug "node/USD{node_name}" -- chroot /host shutdown -h 1 # Verify the server is shut off until openstack server show "USDserver_id" -f value -c status \| grep -q 'SHUTOFF'; do sleep 5; done # Migrate the node openstack server migrate --wait "USDserver_id" # Resize the VM openstack server resize confirm "USDserver_id" # Wait for the resize confirm to finish until openstack server show "USDserver_id" -f value -c status \| grep -q 'SHUTOFF'; do sleep 5; done # Restart the VM openstack server start "USDserver_id" # Wait for the node to show up as Ready: until oc get node "USDnode_name" \| grep -q "^USD{node_name}[[:space:]]\+Ready"; do sleep 5; done # Uncordon the node oc adm uncordon "USDnode_name" # Wait for cluster operators to stabilize until oc get co -o go-template='statuses: {{ range .items }}{{ range .status.conditions }}{{ if eq .type "Degraded" }}{{ if ne .status "False" }}DEGRADED{{ end }}{{ else if eq .type "Progressing"}}{{ if ne .status "False" }}PROGRESSING{{ end }}{{ else if eq .type "Available"}}{{ if ne .status "True" }}NOTAVAILABLE{{ end }}{{ end }}{{ end }}{{ end }}' \| grep -qv '\(DEGRADED\\|PROGRESSING\\|NOTAVAILABLE\)'; do sleep 5; done If the script completes, the control plane machine is migrated to a new RHOSP node. Additional resources Managing control plane machines with control plane machine sets 6.4. Managing the maximum number of pods per node In OpenShift Container Platform, you can configure the number of pods that can run on a node based on the number of processor cores on the node, a hard limit or both. If you use both options, the lower of the two limits the number of pods on a node. When both options are in use, the lower of the two values limits the number of pods on a node. Exceeding these values can result in: Increased CPU utilization. Slow pod scheduling. Potential out-of-memory scenarios, depending on the amount of memory in the node. Exhausting the pool of IP addresses. Resource overcommitting, leading to poor user application performance. Important In Kubernetes, a pod that is holding a single container actually uses two containers. The second container is used to set up networking prior to the actual container starting. Therefore, a system running 10 pods will actually have 20 containers running. Note Disk IOPS throttling from the cloud provider might have an impact on CRI-O and kubelet. They might get overloaded when there are large number of I/O intensive pods running on the nodes. It is recommended that you monitor the disk I/O on the nodes and use volumes with sufficient throughput for the workload. The podsPerCore parameter sets the number of pods the node can run based on the number of processor cores on the node. For example, if podsPerCore is set to 10 on a node with 4 processor cores, the maximum number of pods allowed on the node will be 40 . kubeletConfig: podsPerCore: 10 Setting podsPerCore to 0 disables this limit. The default is 0 . The value of the podsPerCore parameter cannot exceed the value of the maxPods parameter. The maxPods parameter sets the number of pods the node can run to a fixed value, regardless of the properties of the node. kubeletConfig: maxPods: 250 6.4.1. Configuring the maximum number of pods per node Two parameters control the maximum number of pods that can be scheduled to a node: podsPerCore and maxPods . If you use both options, the lower of the two limits the number of pods on a node. For example, if podsPerCore is set to 10 on a node with 4 processor cores, the maximum number of pods allowed on the node will be 40. Prerequisites Obtain the label associated with the static MachineConfigPool CRD for the type of node you want to configure by entering the following command: USD oc edit machineconfigpool <name> For example: USD oc edit machineconfigpool worker Example output apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: "2022-11-16T15:34:25Z" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: "" 1 name: worker #... 1 The label appears under Labels. Tip If the label is not present, add a key/value pair such as: Procedure Create a custom resource (CR) for your configuration change. Sample configuration for a max-pods CR apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: set-max-pods 1 spec: machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 2 kubeletConfig: podsPerCore: 10 3 maxPods: 250 4 #... 1 Assign a name to CR. 2 Specify the label from the machine config pool. 3 Specify the number of pods the node can run based on the number of processor cores on the node. 4 Specify the number of pods the node can run to a fixed value, regardless of the properties of the node. Note Setting podsPerCore to 0 disables this limit. In the above example, the default value for podsPerCore is 10 and the default value for maxPods is 250 . This means that unless the node has 25 cores or more, by default, podsPerCore will be the limiting factor. Run the following command to create the CR: USD oc create -f <file_name>.yaml Verification List the MachineConfigPool CRDs to see if the change is applied. The UPDATING column reports True if the change is picked up by the Machine Config Controller: USD oc get machineconfigpools Example output NAME CONFIG UPDATED UPDATING DEGRADED master master-9cc2c72f205e103bb534 False False False worker worker-8cecd1236b33ee3f8a5e False True False Once the change is complete, the UPDATED column reports True . USD oc get machineconfigpools Example output NAME CONFIG UPDATED UPDATING DEGRADED master master-9cc2c72f205e103bb534 False True False worker worker-8cecd1236b33ee3f8a5e True False False 6.5. Using the Node Tuning Operator Learn about the Node Tuning Operator and how you can use it to manage node-level tuning by orchestrating the tuned daemon. Purpose The Node Tuning Operator helps you manage node-level tuning by orchestrating the TuneD daemon and achieves low latency performance by using the Performance Profile controller. The majority of high-performance applications require some level of kernel tuning. The Node Tuning Operator provides a unified management interface to users of node-level sysctls and more flexibility to add custom tuning specified by user needs. The Operator manages the containerized TuneD daemon for OpenShift Container Platform as a Kubernetes daemon set. It ensures the custom tuning specification is passed to all containerized TuneD daemons running in the cluster in the format that the daemons understand. The daemons run on all nodes in the cluster, one per node. Node-level settings applied by the containerized TuneD daemon are rolled back on an event that triggers a profile change or when the containerized TuneD daemon is terminated gracefully by receiving and handling a termination signal. The Node Tuning Operator uses the Performance Profile controller to implement automatic tuning to achieve low latency performance for OpenShift Container Platform applications. The cluster administrator configures a performance profile to define node-level settings such as the following: Updating the kernel to kernel-rt. Choosing CPUs for housekeeping. Choosing CPUs for running workloads. The Node Tuning Operator is part of a standard OpenShift Container Platform installation in version 4.1 and later. Note In earlier versions of OpenShift Container Platform, the Performance Addon Operator was used to implement automatic tuning to achieve low latency performance for OpenShift applications. In OpenShift Container Platform 4.11 and later, this functionality is part of the Node Tuning Operator. 6.5.1. Accessing an example Node Tuning Operator specification Use this process to access an example Node Tuning Operator specification. Procedure Run the following command to access an example Node Tuning Operator specification: oc get tuned.tuned.openshift.io/default -o yaml -n openshift-cluster-node-tuning-operator The default CR is meant for delivering standard node-level tuning for the OpenShift Container Platform platform and it can only be modified to set the Operator Management state. Any other custom changes to the default CR will be overwritten by the Operator. For custom tuning, create your own Tuned CRs. Newly created CRs will be combined with the default CR and custom tuning applied to OpenShift Container Platform nodes based on node or pod labels and profile priorities. Warning While in certain situations the support for pod labels can be a convenient way of automatically delivering required tuning, this practice is discouraged and strongly advised against, especially in large-scale clusters. The default Tuned CR ships without pod label matching. If a custom profile is created with pod label matching, then the functionality will be enabled at that time. The pod label functionality will be deprecated in future versions of the Node Tuning Operator. 6.5.2. Custom tuning specification The custom resource (CR) for the Operator has two major sections. The first section, profile: , is a list of TuneD profiles and their names. The second, recommend: , defines the profile selection logic. Multiple custom tuning specifications can co-exist as multiple CRs in the Operator's namespace. The existence of new CRs or the deletion of old CRs is detected by the Operator. All existing custom tuning specifications are merged and appropriate objects for the containerized TuneD daemons are updated. Management state The Operator Management state is set by adjusting the default Tuned CR. By default, the Operator is in the Managed state and the spec.managementState field is not present in the default Tuned CR. Valid values for the Operator Management state are as follows: Managed: the Operator will update its operands as configuration resources are updated Unmanaged: the Operator will ignore changes to the configuration resources Removed: the Operator will remove its operands and resources the Operator provisioned Profile data The profile: section lists TuneD profiles and their names. profile: - name: tuned_profile_1 data: \| # TuneD profile specification [main] summary=Description of tuned_profile_1 profile [sysctl] net.ipv4.ip_forward=1 # ... other sysctl's or other TuneD daemon plugins supported by the containerized TuneD # ... - name: tuned_profile_n data: \| # TuneD profile specification [main] summary=Description of tuned_profile_n profile # tuned_profile_n profile settings Recommended profiles The profile: selection logic is defined by the recommend: section of the CR. The recommend: section is a list of items to recommend the profiles based on a selection criteria. recommend: <recommend-item-1> # ... <recommend-item-n> The individual items of the list: - machineConfigLabels: 1 <mcLabels> 2 match: 3 <match> 4 priority: <priority> 5 profile: <tuned_profile_name> 6 operand: 7 debug: <bool> 8 tunedConfig: reapply_sysctl: <bool> 9 1 Optional. 2 A dictionary of key/value MachineConfig labels. The keys must be unique. 3 If omitted, profile match is assumed unless a profile with a higher priority matches first or machineConfigLabels is set. 4 An optional list. 5 Profile ordering priority. Lower numbers mean higher priority ( 0 is the highest priority). 6 A TuneD profile to apply on a match. For example tuned_profile_1 . 7 Optional operand configuration. 8 Turn debugging on or off for the TuneD daemon. Options are true for on or false for off. The default is false . 9 Turn reapply_sysctl functionality on or off for the TuneD daemon. Options are true for on and false for off. <match> is an optional list recursively defined as follows: - label: <label_name> 1 value: <label_value> 2 type: <label_type> 3 <match> 4 1 Node or pod label name. 2 Optional node or pod label value. If omitted, the presence of <label_name> is enough to match. 3 Optional object type ( node or pod ). If omitted, node is assumed. 4 An optional <match> list. If <match> is not omitted, all nested <match> sections must also evaluate to true . Otherwise, false is assumed and the profile with the respective <match> section will not be applied or recommended. Therefore, the nesting (child <match> sections) works as logical AND operator. Conversely, if any item of the <match> list matches, the entire <match> list evaluates to true . Therefore, the list acts as logical OR operator. If machineConfigLabels is defined, machine config pool based matching is turned on for the given recommend: list item. <mcLabels> specifies the labels for a machine config. The machine config is created automatically to apply host settings, such as kernel boot parameters, for the profile <tuned_profile_name> . This involves finding all machine config pools with machine config selector matching <mcLabels> and setting the profile <tuned_profile_name> on all nodes that are assigned the found machine config pools. To target nodes that have both master and worker roles, you must use the master role. The list items match and machineConfigLabels are connected by the logical OR operator. The match item is evaluated first in a short-circuit manner. Therefore, if it evaluates to true , the machineConfigLabels item is not considered. Important When using machine config pool based matching, it is advised to group nodes with the same hardware configuration into the same machine config pool. Not following this practice might result in TuneD operands calculating conflicting kernel parameters for two or more nodes sharing the same machine config pool. Example: Node or pod label based matching - match: - label: tuned.openshift.io/elasticsearch match: - label: node-role.kubernetes.io/master - label: node-role.kubernetes.io/infra type: pod priority: 10 profile: openshift-control-plane-es - match: - label: node-role.kubernetes.io/master - label: node-role.kubernetes.io/infra priority: 20 profile: openshift-control-plane - priority: 30 profile: openshift-node The CR above is translated for the containerized TuneD daemon into its recommend.conf file based on the profile priorities. The profile with the highest priority ( 10 ) is openshift-control-plane-es and, therefore, it is considered first. The containerized TuneD daemon running on a given node looks to see if there is a pod running on the same node with the tuned.openshift.io/elasticsearch label set. If not, the entire <match> section evaluates as false . If there is such a pod with the label, in order for the <match> section to evaluate to true , the node label also needs to be node-role.kubernetes.io/master or node-role.kubernetes.io/infra . If the labels for the profile with priority 10 matched, openshift-control-plane-es profile is applied and no other profile is considered. If the node/pod label combination did not match, the second highest priority profile ( openshift-control-plane ) is considered. This profile is applied if the containerized TuneD pod runs on a node with labels node-role.kubernetes.io/master or node-role.kubernetes.io/infra . Finally, the profile openshift-node has the lowest priority of 30 . It lacks the <match> section and, therefore, will always match. It acts as a profile catch-all to set openshift-node profile, if no other profile with higher priority matches on a given node. Example: Machine config pool based matching apiVersion: tuned.openshift.io/v1 kind: Tuned metadata: name: openshift-node-custom namespace: openshift-cluster-node-tuning-operator spec: profile: - data: \| [main] summary=Custom OpenShift node profile with an additional kernel parameter include=openshift-node [bootloader] cmdline_openshift_node_custom=+skew_tick=1 name: openshift-node-custom recommend: - machineConfigLabels: machineconfiguration.openshift.io/role: "worker-custom" priority: 20 profile: openshift-node-custom To minimize node reboots, label the target nodes with a label the machine config pool's node selector will match, then create the Tuned CR above and finally create the custom machine config pool itself. Cloud provider-specific TuneD profiles With this functionality, all Cloud provider-specific nodes can conveniently be assigned a TuneD profile specifically tailored to a given Cloud provider on a OpenShift Container Platform cluster. This can be accomplished without adding additional node labels or grouping nodes into machine config pools. This functionality takes advantage of spec.providerID node object values in the form of <cloud-provider>://<cloud-provider-specific-id> and writes the file /var/lib/ocp-tuned/provider with the value <cloud-provider> in NTO operand containers. The content of this file is then used by TuneD to load provider-<cloud-provider> profile if such profile exists. The openshift profile that both openshift-control-plane and openshift-node profiles inherit settings from is now updated to use this functionality through the use of conditional profile loading. Neither NTO nor TuneD currently include any Cloud provider-specific profiles. However, it is possible to create a custom profile provider-<cloud-provider> that will be applied to all Cloud provider-specific cluster nodes. Example GCE Cloud provider profile apiVersion: tuned.openshift.io/v1 kind: Tuned metadata: name: provider-gce namespace: openshift-cluster-node-tuning-operator spec: profile: - data: \| [main] summary=GCE Cloud provider-specific profile # Your tuning for GCE Cloud provider goes here. name: provider-gce Note Due to profile inheritance, any setting specified in the provider-<cloud-provider> profile will be overwritten by the openshift profile and its child profiles. 6.5.3. Default profiles set on a cluster The following are the default profiles set on a cluster. apiVersion: tuned.openshift.io/v1 kind: Tuned metadata: name: default namespace: openshift-cluster-node-tuning-operator spec: profile: - data: \| [main] summary=Optimize systems running OpenShift (provider specific parent profile) include=-provider-USD{f:exec:cat:/var/lib/ocp-tuned/provider},openshift name: openshift recommend: - profile: openshift-control-plane priority: 30 match: - label: node-role.kubernetes.io/master - label: node-role.kubernetes.io/infra - profile: openshift-node priority: 40 Starting with OpenShift Container Platform 4.9, all OpenShift TuneD profiles are shipped with the TuneD package. You can use the oc exec command to view the contents of these profiles: USD oc exec USDtuned_pod -n openshift-cluster-node-tuning-operator -- find /usr/lib/tuned/openshift{,-control-plane,-node} -name tuned.conf -exec grep -H ^ {} \; 6.5.4. Supported TuneD daemon plugins Excluding the [main] section, the following TuneD plugins are supported when using custom profiles defined in the profile: section of the Tuned CR: audio cpu disk eeepc_she modules mounts net scheduler scsi_host selinux sysctl sysfs usb video vm bootloader There is some dynamic tuning functionality provided by some of these plugins that is not supported. The following TuneD plugins are currently not supported: script systemd Note The TuneD bootloader plugin only supports Red Hat Enterprise Linux CoreOS (RHCOS) worker nodes. Additional resources Available TuneD Plugins Getting Started with TuneD 6.6. Remediating, fencing, and maintaining nodes When node-level failures occur, such as the kernel hangs or network interface controllers (NICs) fail, the work required from the cluster does not decrease, and workloads from affected nodes need to be restarted somewhere. Failures affecting these workloads risk data loss, corruption, or both. It is important to isolate the node, known as fencing , before initiating recovery of the workload, known as remediation , and recovery of the node. For more information on remediation, fencing, and maintaining nodes, see the Workload Availability for Red Hat OpenShift documentation. 6.7. Understanding node rebooting To reboot a node without causing an outage for applications running on the platform, it is important to first evacuate the pods. For pods that are made highly available by the routing tier, nothing else needs to be done. For other pods needing storage, typically databases, it is critical to ensure that they can remain in operation with one pod temporarily going offline. While implementing resiliency for stateful pods is different for each application, in all cases it is important to configure the scheduler to use node anti-affinity to ensure that the pods are properly spread across available nodes. Another challenge is how to handle nodes that are running critical infrastructure such as the router or the registry. The same node evacuation process applies, though it is important to understand certain edge cases. 6.7.1. About rebooting nodes running critical infrastructure When rebooting nodes that host critical OpenShift Container Platform infrastructure components, such as router pods, registry pods, and monitoring pods, ensure that there are at least three nodes available to run these components. The following scenario demonstrates how service interruptions can occur with applications running on OpenShift Container Platform when only two nodes are available: Node A is marked unschedulable and all pods are evacuated. The registry pod running on that node is now redeployed on node B. Node B is now running both registry pods. Node B is now marked unschedulable and is evacuated. The service exposing the two pod endpoints on node B loses all endpoints, for a brief period of time, until they are redeployed to node A. When using three nodes for infrastructure components, this process does not result in a service disruption. However, due to pod scheduling, the last node that is evacuated and brought back into rotation does not have a registry pod. One of the other nodes has two registry pods. To schedule the third registry pod on the last node, use pod anti-affinity to prevent the scheduler from locating two registry pods on the same node. Additional information For more information on pod anti-affinity, see Placing pods relative to other pods using affinity and anti-affinity rules . 6.7.2. Rebooting a node using pod anti-affinity Pod anti-affinity is slightly different than node anti-affinity. Node anti-affinity can be violated if there are no other suitable locations to deploy a pod. Pod anti-affinity can be set to either required or preferred. With this in place, if only two infrastructure nodes are available and one is rebooted, the container image registry pod is prevented from running on the other node. oc get pods reports the pod as unready until a suitable node is available. Once a node is available and all pods are back in ready state, the node can be restarted. Procedure To reboot a node using pod anti-affinity: Edit the node specification to configure pod anti-affinity: apiVersion: v1 kind: Pod metadata: name: with-pod-antiaffinity spec: affinity: podAntiAffinity: 1 preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 100 3 podAffinityTerm: labelSelector: matchExpressions: - key: registry 4 operator: In 5 values: - default topologyKey: kubernetes.io/hostname #... 1 Stanza to configure pod anti-affinity. 2 Defines a preferred rule. 3 Specifies a weight for a preferred rule. The node with the highest weight is preferred. 4 Description of the pod label that determines when the anti-affinity rule applies. Specify a key and value for the label. 5 The operator represents the relationship between the label on the existing pod and the set of values in the matchExpression parameters in the specification for the new pod. Can be In , NotIn , Exists , or DoesNotExist . This example assumes the container image registry pod has a label of registry=default . Pod anti-affinity can use any Kubernetes match expression. Enable the MatchInterPodAffinity scheduler predicate in the scheduling policy file. Perform a graceful restart of the node. 6.7.3. Understanding how to reboot nodes running routers In most cases, a pod running an OpenShift Container Platform router exposes a host port. The PodFitsPorts scheduler predicate ensures that no router pods using the same port can run on the same node, and pod anti-affinity is achieved. If the routers are relying on IP failover for high availability, there is nothing else that is needed. For router pods relying on an external service such as AWS Elastic Load Balancing for high availability, it is that service's responsibility to react to router pod restarts. In rare cases, a router pod may not have a host port configured. In those cases, it is important to follow the recommended restart process for infrastructure nodes. 6.7.4. Rebooting a node gracefully Before rebooting a node, it is recommended to backup etcd data to avoid any data loss on the node. Note For single-node OpenShift clusters that require users to perform the oc login command rather than having the certificates in kubeconfig file to manage the cluster, the oc adm commands might not be available after cordoning and draining the node. This is because the openshift-oauth-apiserver pod is not running due to the cordon. You can use SSH to access the nodes as indicated in the following procedure. In a single-node OpenShift cluster, pods cannot be rescheduled when cordoning and draining. However, doing so gives the pods, especially your workload pods, time to properly stop and release associated resources. Procedure To perform a graceful restart of a node: Mark the node as unschedulable: USD oc adm cordon <node1> Drain the node to remove all the running pods: USD oc adm drain <node1> --ignore-daemonsets --delete-emptydir-data --force You might receive errors that pods associated with custom pod disruption budgets (PDB) cannot be evicted. Example error error when evicting pods/"rails-postgresql-example-1-72v2w" -n "rails" (will retry after 5s): Cannot evict pod as it would violate the pod's disruption budget. In this case, run the drain command again, adding the disable-eviction flag, which bypasses the PDB checks: USD oc adm drain <node1> --ignore-daemonsets --delete-emptydir-data --force --disable-eviction Access the node in debug mode: USD oc debug node/<node1> Change your root directory to /host : USD chroot /host Restart the node: USD systemctl reboot In a moment, the node enters the NotReady state. Note With some single-node OpenShift clusters, the oc commands might not be available after you cordon and drain the node because the openshift-oauth-apiserver pod is not running. You can use SSH to connect to the node and perform the reboot. USD ssh core@<master-node>.<cluster_name>.<base_domain> USD sudo systemctl reboot After the reboot is complete, mark the node as schedulable by running the following command: USD oc adm uncordon <node1> Note With some single-node OpenShift clusters, the oc commands might not be available after you cordon and drain the node because the openshift-oauth-apiserver pod is not running. You can use SSH to connect to the node and uncordon it. USD ssh core@<target_node> USD sudo oc adm uncordon <node> --kubeconfig /etc/kubernetes/static-pod-resources/kube-apiserver-certs/secrets/node-kubeconfigs/localhost.kubeconfig Verify that the node is ready: USD oc get node <node1> Example output NAME STATUS ROLES AGE VERSION <node1> Ready worker 6d22h v1.18.3+b0068a8 Additional information For information on etcd data backup, see Backing up etcd data . 6.8. Freeing node resources using garbage collection As an administrator, you can use OpenShift Container Platform to ensure that your nodes are running efficiently by freeing up resources through garbage collection. The OpenShift Container Platform node performs two types of garbage collection: Container garbage collection: Removes terminated containers. Image garbage collection: Removes images not referenced by any running pods. 6.8.1. Understanding how terminated containers are removed through garbage collection Container garbage collection removes terminated containers by using eviction thresholds. When eviction thresholds are set for garbage collection, the node tries to keep any container for any pod accessible from the API. If the pod has been deleted, the containers will be as well. Containers are preserved as long the pod is not deleted and the eviction threshold is not reached. If the node is under disk pressure, it will remove containers and their logs will no longer be accessible using oc logs . eviction-soft - A soft eviction threshold pairs an eviction threshold with a required administrator-specified grace period. eviction-hard - A hard eviction threshold has no grace period, and if observed, OpenShift Container Platform takes immediate action. The following table lists the eviction thresholds: Table 6.2. Variables for configuring container garbage collection Node condition Eviction signal Description MemoryPressure memory.available The available memory on the node. DiskPressure nodefs.available nodefs.inodesFree imagefs.available imagefs.inodesFree The available disk space or inodes on the node root file system, nodefs , or image file system, imagefs . Note For evictionHard you must specify all of these parameters. If you do not specify all parameters, only the specified parameters are applied and the garbage collection will not function properly. If a node is oscillating above and below a soft eviction threshold, but not exceeding its associated grace period, the corresponding node would constantly oscillate between true and false . As a consequence, the scheduler could make poor scheduling decisions. To protect against this oscillation, use the evictionpressure-transition-period flag to control how long OpenShift Container Platform must wait before transitioning out of a pressure condition. OpenShift Container Platform will not set an eviction threshold as being met for the specified pressure condition for the period specified before toggling the condition back to false. Note Setting the evictionPressureTransitionPeriod parameter to 0 configures the default value of 5 minutes. You cannot set an eviction pressure transition period to zero seconds. 6.8.2. Understanding how images are removed through garbage collection Image garbage collection removes images that are not referenced by any running pods. OpenShift Container Platform determines which images to remove from a node based on the disk usage that is reported by cAdvisor . The policy for image garbage collection is based on two conditions: The percent of disk usage (expressed as an integer) which triggers image garbage collection. The default is 85 . The percent of disk usage (expressed as an integer) to which image garbage collection attempts to free. Default is 80 . For image garbage collection, you can modify any of the following variables using a custom resource. Table 6.3. Variables for configuring image garbage collection Setting Description imageMinimumGCAge The minimum age for an unused image before the image is removed by garbage collection. The default is 2m . imageGCHighThresholdPercent The percent of disk usage, expressed as an integer, which triggers image garbage collection. The default is 85 . This value must be greater than the imageGCLowThresholdPercent value. imageGCLowThresholdPercent The percent of disk usage, expressed as an integer, to which image garbage collection attempts to free. The default is 80 . This value must be less than the imageGCHighThresholdPercent value. Two lists of images are retrieved in each garbage collector run: A list of images currently running in at least one pod. A list of images available on a host. As new containers are run, new images appear. All images are marked with a time stamp. If the image is running (the first list above) or is newly detected (the second list above), it is marked with the current time. The remaining images are already marked from the spins. All images are then sorted by the time stamp. Once the collection starts, the oldest images get deleted first until the stopping criterion is met. 6.8.3. Configuring garbage collection for containers and images As an administrator, you can configure how OpenShift Container Platform performs garbage collection by creating a kubeletConfig object for each machine config pool. Note OpenShift Container Platform supports only one kubeletConfig object for each machine config pool. You can configure any combination of the following: Soft eviction for containers Hard eviction for containers Eviction for images Container garbage collection removes terminated containers. Image garbage collection removes images that are not referenced by any running pods. Prerequisites Obtain the label associated with the static MachineConfigPool CRD for the type of node you want to configure by entering the following command: USD oc edit machineconfigpool <name> For example: USD oc edit machineconfigpool worker Example output apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: "2022-11-16T15:34:25Z" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: "" 1 name: worker #... 1 The label appears under Labels. Tip If the label is not present, add a key/value pair such as: Procedure Create a custom resource (CR) for your configuration change. Important If there is one file system, or if /var/lib/kubelet and /var/lib/containers/ are in the same file system, the settings with the highest values trigger evictions, as those are met first. The file system triggers the eviction. Sample configuration for a container garbage collection CR apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: worker-kubeconfig 1 spec: machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 2 kubeletConfig: evictionSoft: 3 memory.available: "500Mi" 4 nodefs.available: "10%" nodefs.inodesFree: "5%" imagefs.available: "15%" imagefs.inodesFree: "10%" evictionSoftGracePeriod: 5 memory.available: "1m30s" nodefs.available: "1m30s" nodefs.inodesFree: "1m30s" imagefs.available: "1m30s" imagefs.inodesFree: "1m30s" evictionHard: 6 memory.available: "200Mi" nodefs.available: "5%" nodefs.inodesFree: "4%" imagefs.available: "10%" imagefs.inodesFree: "5%" evictionPressureTransitionPeriod: 3m 7 imageMinimumGCAge: 5m 8 imageGCHighThresholdPercent: 80 9 imageGCLowThresholdPercent: 75 10 #... 1 Name for the object. 2 Specify the label from the machine config pool. 3 For container garbage collection: Type of eviction: evictionSoft or evictionHard . 4 For container garbage collection: Eviction thresholds based on a specific eviction trigger signal. 5 For container garbage collection: Grace periods for the soft eviction. This parameter does not apply to eviction-hard . 6 For container garbage collection: Eviction thresholds based on a specific eviction trigger signal. For evictionHard you must specify all of these parameters. If you do not specify all parameters, only the specified parameters are applied and the garbage collection will not function properly. 7 For container garbage collection: The duration to wait before transitioning out of an eviction pressure condition. Setting the evictionPressureTransitionPeriod parameter to 0 configures the default value of 5 minutes. 8 For image garbage collection: The minimum age for an unused image before the image is removed by garbage collection. 9 For image garbage collection: Image garbage collection is triggered at the specified percent of disk usage (expressed as an integer). This value must be greater than the imageGCLowThresholdPercent value. 10 For image garbage collection: Image garbage collection attempts to free resources to the specified percent of disk usage (expressed as an integer). This value must be less than the imageGCHighThresholdPercent value. Run the following command to create the CR: USD oc create -f <file_name>.yaml For example: USD oc create -f gc-container.yaml Example output kubeletconfig.machineconfiguration.openshift.io/gc-container created Verification Verify that garbage collection is active by entering the following command. The Machine Config Pool you specified in the custom resource appears with UPDATING as 'true` until the change is fully implemented: USD oc get machineconfigpool Example output NAME CONFIG UPDATED UPDATING master rendered-master-546383f80705bd5aeaba93 True False worker rendered-worker-b4c51bb33ccaae6fc4a6a5 False True 6.9. Allocating resources for nodes in an OpenShift Container Platform cluster To provide more reliable scheduling and minimize node resource overcommitment, reserve a portion of the CPU and memory resources for use by the underlying node components, such as kubelet and kube-proxy , and the remaining system components, such as sshd and NetworkManager . By specifying the resources to reserve, you provide the scheduler with more information about the remaining CPU and memory resources that a node has available for use by pods. You can allow OpenShift Container Platform to automatically determine the optimal system-reserved CPU and memory resources for your nodes or you can manually determine and set the best resources for your nodes. Important To manually set resource values, you must use a kubelet config CR. You cannot use a machine config CR. 6.9.1. Understanding how to allocate resources for nodes CPU and memory resources reserved for node components in OpenShift Container Platform are based on two node settings: Setting Description kube-reserved This setting is not used with OpenShift Container Platform. Add the CPU and memory resources that you planned to reserve to the system-reserved setting. system-reserved This setting identifies the resources to reserve for the node components and system components, such as CRI-O and Kubelet. The default settings depend on the OpenShift Container Platform and Machine Config Operator versions. Confirm the default systemReserved parameter on the machine-config-operator repository. If a flag is not set, the defaults are used. If none of the flags are set, the allocated resource is set to the node's capacity as it was before the introduction of allocatable resources. Note Any CPUs specifically reserved using the reservedSystemCPUs parameter are not available for allocation using kube-reserved or system-reserved . 6.9.1.1. How OpenShift Container Platform computes allocated resources An allocated amount of a resource is computed based on the following formula: Note The withholding of Hard-Eviction-Thresholds from Allocatable improves system reliability because the value for Allocatable is enforced for pods at the node level. If Allocatable is negative, it is set to 0 . Each node reports the system resources that are used by the container runtime and kubelet. To simplify configuring the system-reserved parameter, view the resource use for the node by using the node summary API. The node summary is available at /api/v1/nodes/<node>/proxy/stats/summary . 6.9.1.2. How nodes enforce resource constraints The node is able to limit the total amount of resources that pods can consume based on the configured allocatable value. This feature significantly improves the reliability of the node by preventing pods from using CPU and memory resources that are needed by system services such as the container runtime and node agent. To improve node reliability, administrators should reserve resources based on a target for resource use. The node enforces resource constraints by using a new cgroup hierarchy that enforces quality of service. All pods are launched in a dedicated cgroup hierarchy that is separate from system daemons. Administrators should treat system daemons similar to pods that have a guaranteed quality of service. System daemons can burst within their bounding control groups and this behavior must be managed as part of cluster deployments. Reserve CPU and memory resources for system daemons by specifying the amount of CPU and memory resources in system-reserved . Enforcing system-reserved limits can prevent critical system services from receiving CPU and memory resources. As a result, a critical system service can be ended by the out-of-memory killer. The recommendation is to enforce system-reserved only if you have profiled the nodes exhaustively to determine precise estimates and you are confident that critical system services can recover if any process in that group is ended by the out-of-memory killer. 6.9.1.3. Understanding Eviction Thresholds If a node is under memory pressure, it can impact the entire node and all pods running on the node. For example, a system daemon that uses more than its reserved amount of memory can trigger an out-of-memory event. To avoid or reduce the probability of system out-of-memory events, the node provides out-of-resource handling. You can reserve some memory using the --eviction-hard flag. The node attempts to evict pods whenever memory availability on the node drops below the absolute value or percentage. If system daemons do not exist on a node, pods are limited to the memory capacity - eviction-hard . For this reason, resources set aside as a buffer for eviction before reaching out of memory conditions are not available for pods. The following is an example to illustrate the impact of node allocatable for memory: Node capacity is 32Gi --system-reserved is 3Gi --eviction-hard is set to 100Mi . For this node, the effective node allocatable value is 28.9Gi . If the node and system components use all their reservation, the memory available for pods is 28.9Gi , and kubelet evicts pods when it exceeds this threshold. If you enforce node allocatable, 28.9Gi , with top-level cgroups, then pods can never exceed 28.9Gi . Evictions are not performed unless system daemons consume more than 3.1Gi of memory. If system daemons do not use up all their reservation, with the above example, pods would face memcg OOM kills from their bounding cgroup before node evictions kick in. To better enforce QoS under this situation, the node applies the hard eviction thresholds to the top-level cgroup for all pods to be Node Allocatable + Eviction Hard Thresholds . If system daemons do not use up all their reservation, the node will evict pods whenever they consume more than 28.9Gi of memory. If eviction does not occur in time, a pod will be OOM killed if pods consume 29Gi of memory. 6.9.1.4. How the scheduler determines resource availability The scheduler uses the value of node.Status.Allocatable instead of node.Status.Capacity to decide if a node will become a candidate for pod scheduling. By default, the node will report its machine capacity as fully schedulable by the cluster. 6.9.2. Automatically allocating resources for nodes OpenShift Container Platform can automatically determine the optimal system-reserved CPU and memory resources for nodes associated with a specific machine config pool and update the nodes with those values when the nodes start. By default, the system-reserved CPU is 500m and system-reserved memory is 1Gi . To automatically determine and allocate the system-reserved resources on nodes, create a KubeletConfig custom resource (CR) to set the autoSizingReserved: true parameter. A script on each node calculates the optimal values for the respective reserved resources based on the installed CPU and memory capacity on each node. The script takes into account that increased capacity requires a corresponding increase in the reserved resources. Automatically determining the optimal system-reserved settings ensures that your cluster is running efficiently and prevents node failure due to resource starvation of system components, such as CRI-O and kubelet, without your needing to manually calculate and update the values. This feature is disabled by default. Prerequisites Obtain the label associated with the static MachineConfigPool object for the type of node you want to configure by entering the following command: USD oc edit machineconfigpool <name> For example: USD oc edit machineconfigpool worker Example output apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: "2022-11-16T15:34:25Z" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: "" 1 name: worker #... 1 The label appears under Labels . Tip If an appropriate label is not present, add a key/value pair such as: Procedure Create a custom resource (CR) for your configuration change: Sample configuration for a resource allocation CR apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: dynamic-node 1 spec: autoSizingReserved: true 2 machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 3 #... 1 Assign a name to CR. 2 Add the autoSizingReserved parameter set to true to allow OpenShift Container Platform to automatically determine and allocate the system-reserved resources on the nodes associated with the specified label. To disable automatic allocation on those nodes, set this parameter to false . 3 Specify the label from the machine config pool that you configured in the "Prerequisites" section. You can choose any desired labels for the machine config pool, such as custom-kubelet: small-pods , or the default label, pools.operator.machineconfiguration.openshift.io/worker: "" . The example enables automatic resource allocation on all worker nodes. OpenShift Container Platform drains the nodes, applies the kubelet config, and restarts the nodes. Create the CR by entering the following command: USD oc create -f <file_name>.yaml Verification Log in to a node you configured by entering the following command: USD oc debug node/<node_name> Set /host as the root directory within the debug shell: # chroot /host View the /etc/node-sizing.env file: Example output SYSTEM_RESERVED_MEMORY=3Gi SYSTEM_RESERVED_CPU=0.08 The kubelet uses the system-reserved values in the /etc/node-sizing.env file. In the example, the worker nodes are allocated 0.08 CPU and 3 Gi of memory. It can take several minutes for the optimal values to appear. 6.9.3. Manually allocating resources for nodes OpenShift Container Platform supports the CPU and memory resource types for allocation. The ephemeral-resource resource type is also supported. For the cpu type, you specify the resource quantity in units of cores, such as 200m , 0.5 , or 1 . For memory and ephemeral-storage , you specify the resource quantity in units of bytes, such as 200Ki , 50Mi , or 5Gi . By default, the system-reserved CPU is 500m and system-reserved memory is 1Gi . As an administrator, you can set these values by using a kubelet config custom resource (CR) through a set of <resource_type>=<resource_quantity> pairs (e.g., cpu=200m,memory=512Mi ). Important You must use a kubelet config CR to manually set resource values. You cannot use a machine config CR. For details on the recommended system-reserved values, refer to the recommended system-reserved values . Prerequisites Obtain the label associated with the static MachineConfigPool CRD for the type of node you want to configure by entering the following command: USD oc edit machineconfigpool <name> For example: USD oc edit machineconfigpool worker Example output apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: "2022-11-16T15:34:25Z" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: "" 1 name: worker #... 1 The label appears under Labels. Tip If the label is not present, add a key/value pair such as: Procedure Create a custom resource (CR) for your configuration change. Sample configuration for a resource allocation CR apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: set-allocatable 1 spec: machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 2 kubeletConfig: systemReserved: 3 cpu: 1000m memory: 1Gi #... 1 Assign a name to CR. 2 Specify the label from the machine config pool. 3 Specify the resources to reserve for the node components and system components. Run the following command to create the CR: USD oc create -f <file_name>.yaml 6.10. Allocating specific CPUs for nodes in a cluster When using the static CPU Manager policy , you can reserve specific CPUs for use by specific nodes in your cluster. For example, on a system with 24 CPUs, you could reserve CPUs numbered 0 - 3 for the control plane allowing the compute nodes to use CPUs 4 - 23. 6.10.1. Reserving CPUs for nodes To explicitly define a list of CPUs that are reserved for specific nodes, create a KubeletConfig custom resource (CR) to define the reservedSystemCPUs parameter. This list supersedes the CPUs that might be reserved using the systemReserved parameter. Procedure Obtain the label associated with the machine config pool (MCP) for the type of node you want to configure: USD oc describe machineconfigpool <name> For example: USD oc describe machineconfigpool worker Example output Name: worker Namespace: Labels: machineconfiguration.openshift.io/mco-built-in= pools.operator.machineconfiguration.openshift.io/worker= 1 Annotations: <none> API Version: machineconfiguration.openshift.io/v1 Kind: MachineConfigPool #... 1 Get the MCP label. Create a YAML file for the KubeletConfig CR: apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: set-reserved-cpus 1 spec: kubeletConfig: reservedSystemCPUs: "0,1,2,3" 2 machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 3 #... 1 Specify a name for the CR. 2 Specify the core IDs of the CPUs you want to reserve for the nodes associated with the MCP. 3 Specify the label from the MCP. Create the CR object: USD oc create -f <file_name>.yaml Additional resources For more information on the systemReserved parameter, see Allocating resources for nodes in an OpenShift Container Platform cluster . 6.11. Enabling TLS security profiles for the kubelet You can use a TLS (Transport Layer Security) security profile to define which TLS ciphers are required by the kubelet when it is acting as an HTTP server. The kubelet uses its HTTP/GRPC server to communicate with the Kubernetes API server, which sends commands to pods, gathers logs, and run exec commands on pods through the kubelet. A TLS security profile defines the TLS ciphers that the Kubernetes API server must use when connecting with the kubelet to protect communication between the kubelet and the Kubernetes API server. Note By default, when the kubelet acts as a client with the Kubernetes API server, it automatically negotiates the TLS parameters with the API server. 6.11.1. Understanding TLS security profiles You can use a TLS (Transport Layer Security) security profile to define which TLS ciphers are required by various OpenShift Container Platform components. The OpenShift Container Platform TLS security profiles are based on Mozilla recommended configurations . You can specify one of the following TLS security profiles for each component: Table 6.4. TLS security profiles Profile Description Old This profile is intended for use with legacy clients or libraries. The profile is based on the Old backward compatibility recommended configuration. The Old profile requires a minimum TLS version of 1.0. Note For the Ingress Controller, the minimum TLS version is converted from 1.0 to 1.1. Intermediate This profile is the recommended configuration for the majority of clients. It is the default TLS security profile for the Ingress Controller, kubelet, and control plane. The profile is based on the Intermediate compatibility recommended configuration. The Intermediate profile requires a minimum TLS version of 1.2. Modern This profile is intended for use with modern clients that have no need for backwards compatibility. This profile is based on the Modern compatibility recommended configuration. The Modern profile requires a minimum TLS version of 1.3. Custom This profile allows you to define the TLS version and ciphers to use. Warning Use caution when using a Custom profile, because invalid configurations can cause problems. Note When using one of the predefined profile types, the effective profile configuration is subject to change between releases. For example, given a specification to use the Intermediate profile deployed on release X.Y.Z, an upgrade to release X.Y.Z+1 might cause a new profile configuration to be applied, resulting in a rollout. 6.11.2. Configuring the TLS security profile for the kubelet To configure a TLS security profile for the kubelet when it is acting as an HTTP server, create a KubeletConfig custom resource (CR) to specify a predefined or custom TLS security profile for specific nodes. If a TLS security profile is not configured, the default TLS security profile is Intermediate . Sample KubeletConfig CR that configures the Old TLS security profile on worker nodes apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig # ... spec: tlsSecurityProfile: old: {} type: Old machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" # ... You can see the ciphers and the minimum TLS version of the configured TLS security profile in the kubelet.conf file on a configured node. Prerequisites You are logged in to OpenShift Container Platform as a user with the cluster-admin role. Procedure Create a KubeletConfig CR to configure the TLS security profile: Sample KubeletConfig CR for a Custom profile apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: set-kubelet-tls-security-profile spec: tlsSecurityProfile: type: Custom 1 custom: 2 ciphers: 3 - ECDHE-ECDSA-CHACHA20-POLY1305 - ECDHE-RSA-CHACHA20-POLY1305 - ECDHE-RSA-AES128-GCM-SHA256 - ECDHE-ECDSA-AES128-GCM-SHA256 minTLSVersion: VersionTLS11 machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 4 #... 1 Specify the TLS security profile type ( Old , Intermediate , or Custom ). The default is Intermediate . 2 Specify the appropriate field for the selected type: old: {} intermediate: {} custom: 3 For the custom type, specify a list of TLS ciphers and minimum accepted TLS version. 4 Optional: Specify the machine config pool label for the nodes you want to apply the TLS security profile. Create the KubeletConfig object: USD oc create -f <filename> Depending on the number of worker nodes in the cluster, wait for the configured nodes to be rebooted one by one. Verification To verify that the profile is set, perform the following steps after the nodes are in the Ready state: Start a debug session for a configured node: USD oc debug node/<node_name> Set /host as the root directory within the debug shell: sh-4.4# chroot /host View the kubelet.conf file: sh-4.4# cat /etc/kubernetes/kubelet.conf Example output "kind": "KubeletConfiguration", "apiVersion": "kubelet.config.k8s.io/v1beta1", #... "tlsCipherSuites": [ "TLS_ECDHE_ECDSA_WITH_AES_128_GCM_SHA256", "TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256", "TLS_ECDHE_ECDSA_WITH_AES_256_GCM_SHA384", "TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384", "TLS_ECDHE_ECDSA_WITH_CHACHA20_POLY1305_SHA256", "TLS_ECDHE_RSA_WITH_CHACHA20_POLY1305_SHA256" ], "tlsMinVersion": "VersionTLS12", #... 6.12. Creating infrastructure nodes Important You can use the advanced machine management and scaling capabilities only in clusters where the Machine API is operational. Clusters with user-provisioned infrastructure require additional validation and configuration to use the Machine API. Clusters with the infrastructure platform type none cannot use the Machine API. This limitation applies even if the compute machines that are attached to the cluster are installed on a platform that supports the feature. This parameter cannot be changed after installation. To view the platform type for your cluster, run the following command: USD oc get infrastructure cluster -o jsonpath='{.status.platform}' You can use infrastructure machine sets to create machines that host only infrastructure components, such as the default router, the integrated container image registry, and the components for cluster metrics and monitoring. These infrastructure machines are not counted toward the total number of subscriptions that are required to run the environment. In a production deployment, it is recommended that you deploy at least three machine sets to hold infrastructure components. Both OpenShift Logging and Red Hat OpenShift Service Mesh deploy Elasticsearch, which requires three instances to be installed on different nodes. Each of these nodes can be deployed to different availability zones for high availability. This configuration requires three different machine sets, one for each availability zone. In global Azure regions that do not have multiple availability zones, you can use availability sets to ensure high availability. Note After adding the NoSchedule taint on the infrastructure node, existing DNS pods running on that node are marked as misscheduled . You must either delete or add toleration on misscheduled DNS pods . 6.12.1. OpenShift Container Platform infrastructure components Each self-managed Red Hat OpenShift subscription includes entitlements for OpenShift Container Platform and other OpenShift-related components. These entitlements are included for running OpenShift Container Platform control plane and infrastructure workloads and do not need to be accounted for during sizing. To qualify as an infrastructure node and use the included entitlement, only components that are supporting the cluster, and not part of an end-user application, can run on those instances. Examples include the following components: Kubernetes and OpenShift Container Platform control plane services The default router The integrated container image registry The HAProxy-based Ingress Controller The cluster metrics collection, or monitoring service, including components for monitoring user-defined projects Cluster aggregated logging Red Hat Quay Red Hat OpenShift Data Foundation Red Hat Advanced Cluster Management for Kubernetes Red Hat Advanced Cluster Security for Kubernetes Red Hat OpenShift GitOps Red Hat OpenShift Pipelines Red Hat OpenShift Service Mesh Any node that runs any other container, pod, or component is a worker node that your subscription must cover. For information about infrastructure nodes and which components can run on infrastructure nodes, see the "Red Hat OpenShift control plane and infrastructure nodes" section in the OpenShift sizing and subscription guide for enterprise Kubernetes document. To create an infrastructure node, you can use a machine set , label the node , or use a machine config pool . 6.12.1.1. Creating an infrastructure node Important See Creating infrastructure machine sets for installer-provisioned infrastructure environments or for any cluster where the control plane nodes are managed by the machine API. Requirements of the cluster dictate that infrastructure, also called infra nodes, be provisioned. The installer only provides provisions for control plane and worker nodes. Worker nodes can be designated as infrastructure nodes or application, also called app , nodes through labeling. Procedure Add a label to the worker node that you want to act as application node: USD oc label node <node-name> node-role.kubernetes.io/app="" Add a label to the worker nodes that you want to act as infrastructure nodes: USD oc label node <node-name> node-role.kubernetes.io/infra="" Check to see if applicable nodes now have the infra role and app roles: USD oc get nodes Create a default cluster-wide node selector. The default node selector is applied to pods created in all namespaces. This creates an intersection with any existing node selectors on a pod, which additionally constrains the pod's selector. Important If the default node selector key conflicts with the key of a pod's label, then the default node selector is not applied. However, do not set a default node selector that might cause a pod to become unschedulable. For example, setting the default node selector to a specific node role, such as node-role.kubernetes.io/infra="" , when a pod's label is set to a different node role, such as node-role.kubernetes.io/master="" , can cause the pod to become unschedulable. For this reason, use caution when setting the default node selector to specific node roles. You can alternatively use a project node selector to avoid cluster-wide node selector key conflicts. Edit the Scheduler object: USD oc edit scheduler cluster Add the defaultNodeSelector field with the appropriate node selector: apiVersion: config.openshift.io/v1 kind: Scheduler metadata: name: cluster spec: defaultNodeSelector: node-role.kubernetes.io/infra="" 1 # ... 1 This example node selector deploys pods on infrastructure nodes by default. Save the file to apply the changes. You can now move infrastructure resources to the newly labeled infra nodes. Additional resources Moving resources to infrastructure machine sets	[ "oc get nodes", "oc get nodes", "NAME STATUS ROLES AGE VERSION master.example.com Ready master 7h v1.29.4 node1.example.com Ready worker 7h v1.29.4 node2.example.com Ready worker 7h v1.29.4", "oc get nodes", "NAME STATUS ROLES AGE VERSION master.example.com Ready master 7h v1.29.4 node1.example.com NotReady,SchedulingDisabled worker 7h v1.29.4 node2.example.com Ready worker 7h v1.29.4", "oc get nodes -o wide", "NAME STATUS ROLES AGE VERSION INTERNAL-IP EXTERNAL-IP OS-IMAGE KERNEL-VERSION CONTAINER-RUNTIME master.example.com Ready master 171m v1.29.4 10.0.129.108 <none> Red Hat Enterprise Linux CoreOS 48.83.202103210901-0 (Ootpa) 4.18.0-240.15.1.el8_3.x86_64 cri-o://1.29.4-30.rhaos4.10.gitf2f339d.el8-dev node1.example.com Ready worker 72m v1.29.4 10.0.129.222 <none> Red Hat Enterprise Linux CoreOS 48.83.202103210901-0 (Ootpa) 4.18.0-240.15.1.el8_3.x86_64 cri-o://1.29.4-30.rhaos4.10.gitf2f339d.el8-dev node2.example.com Ready worker 164m v1.29.4 10.0.142.150 <none> Red Hat Enterprise Linux CoreOS 48.83.202103210901-0 (Ootpa) 4.18.0-240.15.1.el8_3.x86_64 cri-o://1.29.4-30.rhaos4.10.gitf2f339d.el8-dev", "oc get node <node>", "oc get node node1.example.com", "NAME STATUS ROLES AGE VERSION node1.example.com Ready worker 7h v1.29.4", "oc describe node <node>", "oc describe node node1.example.com", "Name: node1.example.com 1 Roles: worker 2 Labels: kubernetes.io/os=linux kubernetes.io/hostname=ip-10-0-131-14 kubernetes.io/arch=amd64 3 node-role.kubernetes.io/worker= node.kubernetes.io/instance-type=m4.large node.openshift.io/os_id=rhcos node.openshift.io/os_version=4.5 region=east topology.kubernetes.io/region=us-east-1 topology.kubernetes.io/zone=us-east-1a Annotations: cluster.k8s.io/machine: openshift-machine-api/ahardin-worker-us-east-2a-q5dzc 4 machineconfiguration.openshift.io/currentConfig: worker-309c228e8b3a92e2235edd544c62fea8 machineconfiguration.openshift.io/desiredConfig: worker-309c228e8b3a92e2235edd544c62fea8 machineconfiguration.openshift.io/state: Done volumes.kubernetes.io/controller-managed-attach-detach: true CreationTimestamp: Wed, 13 Feb 2019 11:05:57 -0500 Taints: <none> 5 Unschedulable: false Conditions: 6 Type Status LastHeartbeatTime LastTransitionTime Reason Message ---- ------ ----------------- ------------------ ------ ------- OutOfDisk False Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:05:57 -0500 KubeletHasSufficientDisk kubelet has sufficient disk space available MemoryPressure False Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:05:57 -0500 KubeletHasSufficientMemory kubelet has sufficient memory available DiskPressure False Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:05:57 -0500 KubeletHasNoDiskPressure kubelet has no disk pressure PIDPressure False Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:05:57 -0500 KubeletHasSufficientPID kubelet has sufficient PID available Ready True Wed, 13 Feb 2019 15:09:42 -0500 Wed, 13 Feb 2019 11:07:09 -0500 KubeletReady kubelet is posting ready status Addresses: 7 InternalIP: 10.0.140.16 InternalDNS: ip-10-0-140-16.us-east-2.compute.internal Hostname: ip-10-0-140-16.us-east-2.compute.internal Capacity: 8 attachable-volumes-aws-ebs: 39 cpu: 2 hugepages-1Gi: 0 hugepages-2Mi: 0 memory: 8172516Ki pods: 250 Allocatable: attachable-volumes-aws-ebs: 39 cpu: 1500m hugepages-1Gi: 0 hugepages-2Mi: 0 memory: 7558116Ki pods: 250 System Info: 9 Machine ID: 63787c9534c24fde9a0cde35c13f1f66 System UUID: EC22BF97-A006-4A58-6AF8-0A38DEEA122A Boot ID: f24ad37d-2594-46b4-8830-7f7555918325 Kernel Version: 3.10.0-957.5.1.el7.x86_64 OS Image: Red Hat Enterprise Linux CoreOS 410.8.20190520.0 (Ootpa) Operating System: linux Architecture: amd64 Container Runtime Version: cri-o://1.29.4-0.6.dev.rhaos4.3.git9ad059b.el8-rc2 Kubelet Version: v1.29.4 Kube-Proxy Version: v1.29.4 PodCIDR: 10.128.4.0/24 ProviderID: aws:///us-east-2a/i-04e87b31dc6b3e171 Non-terminated Pods: (12 in total) 10 Namespace Name CPU Requests CPU Limits Memory Requests Memory Limits --------- ---- ------------ ---------- --------------- ------------- openshift-cluster-node-tuning-operator tuned-hdl5q 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-dns dns-default-l69zr 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-image-registry node-ca-9hmcg 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-ingress router-default-76455c45c-c5ptv 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-machine-config-operator machine-config-daemon-cvqw9 20m (1%) 0 (0%) 50Mi (0%) 0 (0%) openshift-marketplace community-operators-f67fh 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-monitoring alertmanager-main-0 50m (3%) 50m (3%) 210Mi (2%) 10Mi (0%) openshift-monitoring node-exporter-l7q8d 10m (0%) 20m (1%) 20Mi (0%) 40Mi (0%) openshift-monitoring prometheus-adapter-75d769c874-hvb85 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-multus multus-kw8w5 0 (0%) 0 (0%) 0 (0%) 0 (0%) openshift-sdn ovs-t4dsn 100m (6%) 0 (0%) 300Mi (4%) 0 (0%) openshift-sdn sdn-g79hg 100m (6%) 0 (0%) 200Mi (2%) 0 (0%) Allocated resources: (Total limits may be over 100 percent, i.e., overcommitted.) Resource Requests Limits -------- -------- ------ cpu 380m (25%) 270m (18%) memory 880Mi (11%) 250Mi (3%) attachable-volumes-aws-ebs 0 0 Events: 11 Type Reason Age From Message ---- ------ ---- ---- ------- Normal NodeHasSufficientPID 6d (x5 over 6d) kubelet, m01.example.com Node m01.example.com status is now: NodeHasSufficientPID Normal NodeAllocatableEnforced 6d kubelet, m01.example.com Updated Node Allocatable limit across pods Normal NodeHasSufficientMemory 6d (x6 over 6d) kubelet, m01.example.com Node m01.example.com status is now: NodeHasSufficientMemory Normal NodeHasNoDiskPressure 6d (x6 over 6d) kubelet, m01.example.com Node m01.example.com status is now: NodeHasNoDiskPressure Normal NodeHasSufficientDisk 6d (x6 over 6d) kubelet, m01.example.com Node m01.example.com status is now: NodeHasSufficientDisk Normal NodeHasSufficientPID 6d kubelet, m01.example.com Node m01.example.com status is now: NodeHasSufficientPID Normal Starting 6d kubelet, m01.example.com Starting kubelet. #", "oc get pod --selector=<nodeSelector>", "oc get pod --selector=kubernetes.io/os", "oc get pod -l=<nodeSelector>", "oc get pod -l kubernetes.io/os=linux", "oc get pod --all-namespaces --field-selector=spec.nodeName=<nodename>", "oc adm top nodes", "NAME CPU(cores) CPU% MEMORY(bytes) MEMORY% ip-10-0-12-143.ec2.compute.internal 1503m 100% 4533Mi 61% ip-10-0-132-16.ec2.compute.internal 76m 5% 1391Mi 18% ip-10-0-140-137.ec2.compute.internal 398m 26% 2473Mi 33% ip-10-0-142-44.ec2.compute.internal 656m 43% 6119Mi 82% ip-10-0-146-165.ec2.compute.internal 188m 12% 3367Mi 45% ip-10-0-19-62.ec2.compute.internal 896m 59% 5754Mi 77% ip-10-0-44-193.ec2.compute.internal 632m 42% 5349Mi 72%", "oc adm top node --selector=''", "oc adm cordon <node1>", "node/<node1> cordoned", "oc get node <node1>", "NAME STATUS ROLES AGE VERSION <node1> Ready,SchedulingDisabled worker 1d v1.29.4", "oc adm drain <node1> <node2> [--pod-selector=<pod_selector>]", "oc adm drain <node1> <node2> --force=true", "oc adm drain <node1> <node2> --grace-period=-1", "oc adm drain <node1> <node2> --ignore-daemonsets=true", "oc adm drain <node1> <node2> --timeout=5s", "oc adm drain <node1> <node2> --delete-emptydir-data=true", "oc adm drain <node1> <node2> --dry-run=true", "oc adm uncordon <node1>", "oc label node <node> <key_1>=<value_1> ... <key_n>=<value_n>", "oc label nodes webconsole-7f7f6 unhealthy=true", "kind: Node apiVersion: v1 metadata: name: webconsole-7f7f6 labels: unhealthy: 'true' #", "oc label pods --all <key_1>=<value_1>", "oc label pods --all status=unhealthy", "oc adm cordon <node>", "oc adm cordon node1.example.com", "node/node1.example.com cordoned NAME LABELS STATUS node1.example.com kubernetes.io/hostname=node1.example.com Ready,SchedulingDisabled", "oc adm uncordon <node1>", "oc delete pods --field-selector status.phase=Failed -n <POD_NAMESPACE>", "oc get machinesets -n openshift-machine-api", "oc scale --replicas=2 machineset <machine-set-name> -n openshift-machine-api", "oc edit machineset <machine-set-name> -n openshift-machine-api", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: # name: <machine-set-name> namespace: openshift-machine-api # spec: replicas: 2 1 #", "oc adm cordon <node_name>", "oc adm drain <node_name> --force=true", "oc delete node <node_name>", "oc get machineconfigpool --show-labels", "NAME CONFIG UPDATED UPDATING DEGRADED LABELS master rendered-master-e05b81f5ca4db1d249a1bf32f9ec24fd True False False operator.machineconfiguration.openshift.io/required-for-upgrade= worker rendered-worker-f50e78e1bc06d8e82327763145bfcf62 True False False", "oc label machineconfigpool worker custom-kubelet=enabled", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: custom-config 1 spec: machineConfigPoolSelector: matchLabels: custom-kubelet: enabled 2 kubeletConfig: 3 podsPerCore: 10 maxPods: 250 systemReserved: cpu: 2000m memory: 1Gi #", "oc create -f <file-name>", "oc create -f master-kube-config.yaml", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: name: ci-ln-hmy310k-72292-5f87z-worker-a namespace: openshift-machine-api spec: template: spec: providerSpec: value: disks: - autoDelete: true boot: true image: projects/rhcos-cloud/global/images/rhcos-412-85-202203181601-0-gcp-x86-64 1", "oc edit MachineConfiguration cluster", "apiVersion: operator.openshift.io/v1 kind: MachineConfiguration metadata: name: cluster namespace: openshift-machine-config-operator spec: managedBootImages: 1 machineManagers: - resource: machinesets apiGroup: machine.openshift.io selection: mode: All 2", "apiVersion: operator.openshift.io/v1 kind: MachineConfiguration metadata: name: cluster namespace: openshift-machine-config-operator spec: managedBootImages: 1 machineManagers: - resource: machinesets apiGroup: machine.openshift.io selection: mode: Partial partial: machineResourceSelector: matchLabels: update-boot-image: \"true\" 2", "oc label machineset.machine ci-ln-hmy310k-72292-5f87z-worker-a update-boot-image=true -n openshift-machine-api", "oc get machinesets <machineset_name> -n openshift-machine-api -o yaml", "apiVersion: machine.openshift.io/v1beta1 kind: MachineSet metadata: labels: machine.openshift.io/cluster-api-cluster: ci-ln-77hmkpt-72292-d4pxp update-boot-image: \"true\" name: ci-ln-77hmkpt-72292-d4pxp-worker-a namespace: openshift-machine-api spec: template: spec: providerSpec: value: disks: - autoDelete: true boot: true image: projects/rhcos-cloud/global/images/rhcos-416-92-202402201450-0-gcp-x86-64 1", "oc edit MachineConfiguration cluster", "apiVersion: operator.openshift.io/v1 kind: MachineConfiguration metadata: name: cluster namespace: openshift-machine-config-operator spec: managedBootImages: 1 machineManagers: - resource: machinesets apiGroup: machine.openshift.io selection: mode: All", "oc edit schedulers.config.openshift.io cluster", "apiVersion: config.openshift.io/v1 kind: Scheduler metadata: creationTimestamp: \"2019-09-10T03:04:05Z\" generation: 1 name: cluster resourceVersion: \"433\" selfLink: /apis/config.openshift.io/v1/schedulers/cluster uid: a636d30a-d377-11e9-88d4-0a60097bee62 spec: mastersSchedulable: false 1 status: {} #", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: worker name: 99-worker-setsebool spec: config: ignition: version: 3.2.0 systemd: units: - contents: \| [Unit] Description=Set SELinux booleans Before=kubelet.service [Service] Type=oneshot ExecStart=/sbin/setsebool container_manage_cgroup=on RemainAfterExit=true [Install] WantedBy=multi-user.target graphical.target enabled: true name: setsebool.service #", "oc create -f 99-worker-setsebool.yaml", "oc get MachineConfig", "NAME GENERATEDBYCONTROLLER IGNITIONVERSION AGE 00-master 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 00-worker 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-ssh 3.2.0 40m 99-worker-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-worker-ssh 3.2.0 40m rendered-master-23e785de7587df95a4b517e0647e5ab7 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m rendered-worker-5d596d9293ca3ea80c896a1191735bb1 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfig metadata: labels: machineconfiguration.openshift.io/role: worker 1 name: 05-worker-kernelarg-selinuxpermissive 2 spec: kernelArguments: - enforcing=0 3", "oc create -f 05-worker-kernelarg-selinuxpermissive.yaml", "oc get MachineConfig", "NAME GENERATEDBYCONTROLLER IGNITIONVERSION AGE 00-master 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 00-worker 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-master-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-container-runtime 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 01-worker-kubelet 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 05-worker-kernelarg-selinuxpermissive 3.2.0 105s 99-master-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-master-ssh 3.2.0 40m 99-worker-generated-registries 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m 99-worker-ssh 3.2.0 40m rendered-master-23e785de7587df95a4b517e0647e5ab7 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m rendered-worker-5d596d9293ca3ea80c896a1191735bb1 52dd3ba6a9a527fc3ab42afac8d12b693534c8c9 3.2.0 33m", "oc get nodes", "NAME STATUS ROLES AGE VERSION ip-10-0-136-161.ec2.internal Ready worker 28m v1.29.4 ip-10-0-136-243.ec2.internal Ready master 34m v1.29.4 ip-10-0-141-105.ec2.internal Ready,SchedulingDisabled worker 28m v1.29.4 ip-10-0-142-249.ec2.internal Ready master 34m v1.29.4 ip-10-0-153-11.ec2.internal Ready worker 28m v1.29.4 ip-10-0-153-150.ec2.internal Ready master 34m v1.29.4", "oc debug node/ip-10-0-141-105.ec2.internal", "Starting pod/ip-10-0-141-105ec2internal-debug To use host binaries, run `chroot /host` sh-4.2# cat /host/proc/cmdline BOOT_IMAGE=/ostree/rhcos-... console=tty0 console=ttyS0,115200n8 rootflags=defaults,prjquota rw root=UUID=fd0... ostree=/ostree/boot.0/rhcos/16 coreos.oem.id=qemu coreos.oem.id=ec2 ignition.platform.id=ec2 enforcing=0 sh-4.2# exit", "oc label machineconfigpool worker kubelet-swap=enabled", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: swap-config spec: machineConfigPoolSelector: matchLabels: kubelet-swap: enabled kubeletConfig: failSwapOn: false 1 memorySwap: swapBehavior: LimitedSwap 2 #", "#!/usr/bin/env bash set -Eeuo pipefail if [ USD# -lt 1 ]; then echo \"Usage: 'USD0 node_name'\" exit 64 fi Check for admin OpenStack credentials openstack server list --all-projects >/dev/null \|\| { >&2 echo \"The script needs OpenStack admin credentials. Exiting\"; exit 77; } Check for admin OpenShift credentials adm top node >/dev/null \|\| { >&2 echo \"The script needs OpenShift admin credentials. Exiting\"; exit 77; } set -x declare -r node_name=\"USD1\" declare server_id server_id=\"USD(openstack server list --all-projects -f value -c ID -c Name \| grep \"USDnode_name\" \| cut -d' ' -f1)\" readonly server_id Drain the node adm cordon \"USDnode_name\" adm drain \"USDnode_name\" --delete-emptydir-data --ignore-daemonsets --force Power off the server debug \"node/USD{node_name}\" -- chroot /host shutdown -h 1 Verify the server is shut off until openstack server show \"USDserver_id\" -f value -c status \| grep -q 'SHUTOFF'; do sleep 5; done Migrate the node openstack server migrate --wait \"USDserver_id\" Resize the VM openstack server resize confirm \"USDserver_id\" Wait for the resize confirm to finish until openstack server show \"USDserver_id\" -f value -c status \| grep -q 'SHUTOFF'; do sleep 5; done Restart the VM openstack server start \"USDserver_id\" Wait for the node to show up as Ready: until oc get node \"USDnode_name\" \| grep -q \"^USD{node_name}[[:space:]]\\+Ready\"; do sleep 5; done Uncordon the node adm uncordon \"USDnode_name\" Wait for cluster operators to stabilize until oc get co -o go-template='statuses: {{ range .items }}{{ range .status.conditions }}{{ if eq .type \"Degraded\" }}{{ if ne .status \"False\" }}DEGRADED{{ end }}{{ else if eq .type \"Progressing\"}}{{ if ne .status \"False\" }}PROGRESSING{{ end }}{{ else if eq .type \"Available\"}}{{ if ne .status \"True\" }}NOTAVAILABLE{{ end }}{{ end }}{{ end }}{{ end }}' \| grep -qv '\\(DEGRADED\\\|PROGRESSING\\\|NOTAVAILABLE\\)'; do sleep 5; done", "kubeletConfig: podsPerCore: 10", "kubeletConfig: maxPods: 250", "oc edit machineconfigpool <name>", "oc edit machineconfigpool worker", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: \"2022-11-16T15:34:25Z\" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 1 name: worker #", "oc label machineconfigpool worker custom-kubelet=small-pods", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: set-max-pods 1 spec: machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 2 kubeletConfig: podsPerCore: 10 3 maxPods: 250 4 #", "oc create -f <file_name>.yaml", "oc get machineconfigpools", "NAME CONFIG UPDATED UPDATING DEGRADED master master-9cc2c72f205e103bb534 False False False worker worker-8cecd1236b33ee3f8a5e False True False", "oc get machineconfigpools", "NAME CONFIG UPDATED UPDATING DEGRADED master master-9cc2c72f205e103bb534 False True False worker worker-8cecd1236b33ee3f8a5e True False False", "get tuned.tuned.openshift.io/default -o yaml -n openshift-cluster-node-tuning-operator", "profile: - name: tuned_profile_1 data: \| # TuneD profile specification [main] summary=Description of tuned_profile_1 profile [sysctl] net.ipv4.ip_forward=1 # ... other sysctl's or other TuneD daemon plugins supported by the containerized TuneD - name: tuned_profile_n data: \| # TuneD profile specification [main] summary=Description of tuned_profile_n profile # tuned_profile_n profile settings", "recommend: <recommend-item-1> <recommend-item-n>", "- machineConfigLabels: 1 <mcLabels> 2 match: 3 <match> 4 priority: <priority> 5 profile: <tuned_profile_name> 6 operand: 7 debug: <bool> 8 tunedConfig: reapply_sysctl: <bool> 9", "- label: <label_name> 1 value: <label_value> 2 type: <label_type> 3 <match> 4", "- match: - label: tuned.openshift.io/elasticsearch match: - label: node-role.kubernetes.io/master - label: node-role.kubernetes.io/infra type: pod priority: 10 profile: openshift-control-plane-es - match: - label: node-role.kubernetes.io/master - label: node-role.kubernetes.io/infra priority: 20 profile: openshift-control-plane - priority: 30 profile: openshift-node", "apiVersion: tuned.openshift.io/v1 kind: Tuned metadata: name: openshift-node-custom namespace: openshift-cluster-node-tuning-operator spec: profile: - data: \| [main] summary=Custom OpenShift node profile with an additional kernel parameter include=openshift-node [bootloader] cmdline_openshift_node_custom=+skew_tick=1 name: openshift-node-custom recommend: - machineConfigLabels: machineconfiguration.openshift.io/role: \"worker-custom\" priority: 20 profile: openshift-node-custom", "apiVersion: tuned.openshift.io/v1 kind: Tuned metadata: name: provider-gce namespace: openshift-cluster-node-tuning-operator spec: profile: - data: \| [main] summary=GCE Cloud provider-specific profile # Your tuning for GCE Cloud provider goes here. name: provider-gce", "apiVersion: tuned.openshift.io/v1 kind: Tuned metadata: name: default namespace: openshift-cluster-node-tuning-operator spec: profile: - data: \| [main] summary=Optimize systems running OpenShift (provider specific parent profile) include=-provider-USD{f:exec:cat:/var/lib/ocp-tuned/provider},openshift name: openshift recommend: - profile: openshift-control-plane priority: 30 match: - label: node-role.kubernetes.io/master - label: node-role.kubernetes.io/infra - profile: openshift-node priority: 40", "oc exec USDtuned_pod -n openshift-cluster-node-tuning-operator -- find /usr/lib/tuned/openshift{,-control-plane,-node} -name tuned.conf -exec grep -H ^ {} \\;", "apiVersion: v1 kind: Pod metadata: name: with-pod-antiaffinity spec: affinity: podAntiAffinity: 1 preferredDuringSchedulingIgnoredDuringExecution: 2 - weight: 100 3 podAffinityTerm: labelSelector: matchExpressions: - key: registry 4 operator: In 5 values: - default topologyKey: kubernetes.io/hostname #", "oc adm cordon <node1>", "oc adm drain <node1> --ignore-daemonsets --delete-emptydir-data --force", "error when evicting pods/\"rails-postgresql-example-1-72v2w\" -n \"rails\" (will retry after 5s): Cannot evict pod as it would violate the pod's disruption budget.", "oc adm drain <node1> --ignore-daemonsets --delete-emptydir-data --force --disable-eviction", "oc debug node/<node1>", "chroot /host", "systemctl reboot", "ssh core@<master-node>.<cluster_name>.<base_domain>", "sudo systemctl reboot", "oc adm uncordon <node1>", "ssh core@<target_node>", "sudo oc adm uncordon <node> --kubeconfig /etc/kubernetes/static-pod-resources/kube-apiserver-certs/secrets/node-kubeconfigs/localhost.kubeconfig", "oc get node <node1>", "NAME STATUS ROLES AGE VERSION <node1> Ready worker 6d22h v1.18.3+b0068a8", "oc edit machineconfigpool <name>", "oc edit machineconfigpool worker", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: \"2022-11-16T15:34:25Z\" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 1 name: worker #", "oc label machineconfigpool worker custom-kubelet=small-pods", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: worker-kubeconfig 1 spec: machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 2 kubeletConfig: evictionSoft: 3 memory.available: \"500Mi\" 4 nodefs.available: \"10%\" nodefs.inodesFree: \"5%\" imagefs.available: \"15%\" imagefs.inodesFree: \"10%\" evictionSoftGracePeriod: 5 memory.available: \"1m30s\" nodefs.available: \"1m30s\" nodefs.inodesFree: \"1m30s\" imagefs.available: \"1m30s\" imagefs.inodesFree: \"1m30s\" evictionHard: 6 memory.available: \"200Mi\" nodefs.available: \"5%\" nodefs.inodesFree: \"4%\" imagefs.available: \"10%\" imagefs.inodesFree: \"5%\" evictionPressureTransitionPeriod: 3m 7 imageMinimumGCAge: 5m 8 imageGCHighThresholdPercent: 80 9 imageGCLowThresholdPercent: 75 10 #", "oc create -f <file_name>.yaml", "oc create -f gc-container.yaml", "kubeletconfig.machineconfiguration.openshift.io/gc-container created", "oc get machineconfigpool", "NAME CONFIG UPDATED UPDATING master rendered-master-546383f80705bd5aeaba93 True False worker rendered-worker-b4c51bb33ccaae6fc4a6a5 False True", "[Allocatable] = [Node Capacity] - [system-reserved] - [Hard-Eviction-Thresholds]", "oc edit machineconfigpool <name>", "oc edit machineconfigpool worker", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: \"2022-11-16T15:34:25Z\" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 1 name: worker #", "oc label machineconfigpool worker custom-kubelet=small-pods", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: dynamic-node 1 spec: autoSizingReserved: true 2 machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 3 #", "oc create -f <file_name>.yaml", "oc debug node/<node_name>", "chroot /host", "SYSTEM_RESERVED_MEMORY=3Gi SYSTEM_RESERVED_CPU=0.08", "oc edit machineconfigpool <name>", "oc edit machineconfigpool worker", "apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: creationTimestamp: \"2022-11-16T15:34:25Z\" generation: 4 labels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 1 name: worker #", "oc label machineconfigpool worker custom-kubelet=small-pods", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: set-allocatable 1 spec: machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 2 kubeletConfig: systemReserved: 3 cpu: 1000m memory: 1Gi #", "oc create -f <file_name>.yaml", "oc describe machineconfigpool <name>", "oc describe machineconfigpool worker", "Name: worker Namespace: Labels: machineconfiguration.openshift.io/mco-built-in= pools.operator.machineconfiguration.openshift.io/worker= 1 Annotations: <none> API Version: machineconfiguration.openshift.io/v1 Kind: MachineConfigPool #", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: set-reserved-cpus 1 spec: kubeletConfig: reservedSystemCPUs: \"0,1,2,3\" 2 machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 3 #", "oc create -f <file_name>.yaml", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig spec: tlsSecurityProfile: old: {} type: Old machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: \"\"", "apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: set-kubelet-tls-security-profile spec: tlsSecurityProfile: type: Custom 1 custom: 2 ciphers: 3 - ECDHE-ECDSA-CHACHA20-POLY1305 - ECDHE-RSA-CHACHA20-POLY1305 - ECDHE-RSA-AES128-GCM-SHA256 - ECDHE-ECDSA-AES128-GCM-SHA256 minTLSVersion: VersionTLS11 machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: \"\" 4 #", "oc create -f <filename>", "oc debug node/<node_name>", "sh-4.4# chroot /host", "sh-4.4# cat /etc/kubernetes/kubelet.conf", "\"kind\": \"KubeletConfiguration\", \"apiVersion\": \"kubelet.config.k8s.io/v1beta1\", # \"tlsCipherSuites\": [ \"TLS_ECDHE_ECDSA_WITH_AES_128_GCM_SHA256\", \"TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256\", \"TLS_ECDHE_ECDSA_WITH_AES_256_GCM_SHA384\", \"TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384\", \"TLS_ECDHE_ECDSA_WITH_CHACHA20_POLY1305_SHA256\", \"TLS_ECDHE_RSA_WITH_CHACHA20_POLY1305_SHA256\" ], \"tlsMinVersion\": \"VersionTLS12\", #", "oc get infrastructure cluster -o jsonpath='{.status.platform}'", "oc label node <node-name> node-role.kubernetes.io/app=\"\"", "oc label node <node-name> node-role.kubernetes.io/infra=\"\"", "oc get nodes", "oc edit scheduler cluster", "apiVersion: config.openshift.io/v1 kind: Scheduler metadata: name: cluster spec: defaultNodeSelector: node-role.kubernetes.io/infra=\"\" 1" ]	https://docs.redhat.com/en/documentation/openshift_container_platform/4.16/html/nodes/working-with-nodes
6.6. Resource Operations	6.6. Resource Operations To ensure that resources remain healthy, you can add a monitoring operation to a resource's definition. If you do not specify a monitoring operation for a resource, by default the pcs command will create a monitoring operation, with an interval that is determined by the resource agent. If the resource agent does not provide a default monitoring interval, the pcs command will create a monitoring operation with an interval of 60 seconds. Table 6.4, "Properties of an Operation" summarizes the properties of a resource monitoring operation. Table 6.4. Properties of an Operation Field Description id Unique name for the action. The system assigns this when you configure an operation. name The action to perform. Common values: monitor , start , stop interval If set to a nonzero value, a recurring operation is created that repeats at this frequency, in seconds. A nonzero value makes sense only when the action name is set to monitor . A recurring monitor action will be executed immediately after a resource start completes, and subsequent monitor actions are scheduled starting at the time the monitor action completed. For example, if a monitor action with interval=20s is executed at 01:00:00, the monitor action does not occur at 01:00:20, but at 20 seconds after the first monitor action completes. If set to zero, which is the default value, this parameter allows you to provide values to be used for operations created by the cluster. For example, if the interval is set to zero, the name of the operation is set to start , and the timeout value is set to 40, then Pacemaker will use a timeout of 40 seconds when starting this resource. A monitor operation with a zero interval allows you to set the timeout / on-fail / enabled values for the probes that Pacemaker does at startup to get the current status of all resources when the defaults are not desirable. timeout If the operation does not complete in the amount of time set by this parameter, abort the operation and consider it failed. The default value is the value of timeout if set with the pcs resource op defaults command, or 20 seconds if it is not set. If you find that your system includes a resource that requires more time than the system allows to perform an operation (such as start , stop , or monitor ), investigate the cause and if the lengthy execution time is expected you can increase this value. The timeout value is not a delay of any kind, nor does the cluster wait the entire timeout period if the operation returns before the timeout period has completed. on-fail The action to take if this action ever fails. Allowed values: * ignore - Pretend the resource did not fail * block - Do not perform any further operations on the resource * stop - Stop the resource and do not start it elsewhere * restart - Stop the resource and start it again (possibly on a different node) * fence - STONITH the node on which the resource failed * standby - Move all resources away from the node on which the resource failed The default for the stop operation is fence when STONITH is enabled and block otherwise. All other operations default to restart . enabled If false , the operation is treated as if it does not exist. Allowed values: true , false 6.6.1. Configuring Resource Operations You can configure monitoring operations when you create a resource, using the following command. For example, the following command creates an IPaddr2 resource with a monitoring operation. The new resource is called VirtualIP with an IP address of 192.168.0.99 and a netmask of 24 on eth2 . A monitoring operation will be performed every 30 seconds. Alternately, you can add a monitoring operation to an existing resource with the following command. Use the following command to delete a configured resource operation. Note You must specify the exact operation properties to properly remove an existing operation. To change the values of a monitoring option, you can update the resource. For example, you can create a VirtualIP with the following command. By default, this command creates these operations. To change the stop timeout operation, execute the following command. Note When you update a resource's operation with the pcs resource update command, any options you do not specifically call out are reset to their default values. 6.6.2. Configuring Global Resource Operation Defaults You can use the following command to set global default values for monitoring operations. For example, the following command sets a global default of a timeout value of 240 seconds for all monitoring operations. To display the currently configured default values for monitoring operations, do not specify any options when you execute the pcs resource op defaults command. For example, following command displays the default monitoring operation values for a cluster which has been configured with a timeout value of 240 seconds. Note that a cluster resource will use the global default only when the option is not specified in the cluster resource definition. By default, resource agents define the timeout option for all operations. For the global operation timeout value to be honored, you must create the cluster resource without the timeout option explicitly or you must remove the timeout option by updating the cluster resource, as in the following command. For example, after setting a global default of a timeout value of 240 seconds for all monitoring operations and updating the cluster resource VirtualIP to remove the timeout value for the monitor operation, the resource VirtualIP will then have timeout values for start , stop , and monitor operations of 20s, 40s and 240s, respectively. The global default value for timeout operations is applied here only on the monitor operation, where the default timeout option was removed by the command.	[ "pcs resource create resource_id standard:provider:type\|type [ resource_options ] [op operation_action operation_options [ operation_type operation_options ]...]", "pcs resource create VirtualIP ocf:heartbeat:IPaddr2 ip=192.168.0.99 cidr_netmask=24 nic=eth2 op monitor interval=30s", "pcs resource op add resource_id operation_action [ operation_properties ]", "pcs resource op remove resource_id operation_name operation_properties", "pcs resource create VirtualIP ocf:heartbeat:IPaddr2 ip=192.168.0.99 cidr_netmask=24 nic=eth2", "Operations: start interval=0s timeout=20s (VirtualIP-start-timeout-20s) stop interval=0s timeout=20s (VirtualIP-stop-timeout-20s) monitor interval=10s timeout=20s (VirtualIP-monitor-interval-10s)", "pcs resource update VirtualIP op stop interval=0s timeout=40s pcs resource show VirtualIP Resource: VirtualIP (class=ocf provider=heartbeat type=IPaddr2) Attributes: ip=192.168.0.99 cidr_netmask=24 nic=eth2 Operations: start interval=0s timeout=20s (VirtualIP-start-timeout-20s) monitor interval=10s timeout=20s (VirtualIP-monitor-interval-10s) stop interval=0s timeout=40s (VirtualIP-name-stop-interval-0s-timeout-40s)", "pcs resource op defaults [ options ]", "pcs resource op defaults timeout=240s", "pcs resource op defaults timeout: 240s", "pcs resource update VirtualIP op monitor interval=10s", "pcs resource show VirtualIP Resource: VirtualIP (class=ocf provider=heartbeat type=IPaddr2) Attributes: ip=192.168.0.99 cidr_netmask=24 nic=eth2 Operations: start interval=0s timeout=20s (VirtualIP-start-timeout-20s) monitor interval=10s (VirtualIP-monitor-interval-10s) stop interval=0s timeout=40s (VirtualIP-name-stop-interval-0s-timeout-40s)" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/high_availability_add-on_reference/s1-resourceoperate-haar
function::stp_pid	function::stp_pid Name function::stp_pid - The process id of the stapio process Synopsis Arguments None Description This function returns the process id of the stapio process that launched this script. There could be other SystemTap scripts and stapio processes running on the system.	[ "stp_pid:long()" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/systemtap_tapset_reference/api-stp-pid
17.3. Network Address Translation	17.3. Network Address Translation By default, virtual network switches operate in NAT mode. They use IP masquerading rather than Source-NAT (SNAT) or Destination-NAT (DNAT). IP masquerading enables connected guests to use the host physical machine IP address for communication to any external network. By default, computers that are placed externally to the host physical machine cannot communicate to the guests inside when the virtual network switch is operating in NAT mode, as shown in the following diagram: Figure 17.3. Virtual network switch using NAT with two guests Warning Virtual network switches use NAT configured by iptables rules. Editing these rules while the switch is running is not recommended, as incorrect rules may result in the switch being unable to communicate. If the switch is not running, you can set the public IP range for forward mode NAT in order to create a port masquerading range by running:	[ "iptables -j SNAT --to-source [start]-[end]" ]	https://docs.redhat.com/en/documentation/Red_Hat_Enterprise_Linux/7/html/virtualization_deployment_and_administration_guide/sect-Virtual_Networking-Network_Address_Translation
Chapter 78. KafkaClientAuthenticationOAuth schema reference	Chapter 78. KafkaClientAuthenticationOAuth schema reference Used in: KafkaBridgeSpec , KafkaConnectSpec , KafkaMirrorMaker2ClusterSpec , KafkaMirrorMakerConsumerSpec , KafkaMirrorMakerProducerSpec Full list of KafkaClientAuthenticationOAuth schema properties To configure OAuth client authentication, set the type property to oauth . OAuth authentication can be configured using one of the following options: Client ID and secret Client ID and refresh token Access token Username and password TLS Client ID and secret You can configure the address of your authorization server in the tokenEndpointUri property together with the client ID and client secret used in authentication. The OAuth client will connect to the OAuth server, authenticate using the client ID and secret and get an access token which it will use to authenticate with the Kafka broker. In the clientSecret property, specify a link to a Secret containing the client secret. An example of OAuth client authentication using client ID and client secret authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token clientId: my-client-id clientSecret: secretName: my-client-oauth-secret key: client-secret Optionally, scope and audience can be specified if needed. Client ID and refresh token You can configure the address of your OAuth server in the tokenEndpointUri property together with the OAuth client ID and refresh token. The OAuth client will connect to the OAuth server, authenticate using the client ID and refresh token and get an access token which it will use to authenticate with the Kafka broker. In the refreshToken property, specify a link to a Secret containing the refresh token. An example of OAuth client authentication using client ID and refresh token authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token clientId: my-client-id refreshToken: secretName: my-refresh-token-secret key: refresh-token Access token You can configure the access token used for authentication with the Kafka broker directly. In this case, you do not specify the tokenEndpointUri . In the accessToken property, specify a link to a Secret containing the access token. An example of OAuth client authentication using only an access token authentication: type: oauth accessToken: secretName: my-access-token-secret key: access-token Username and password OAuth username and password configuration uses the OAuth Resource Owner Password Grant mechanism. The mechanism is deprecated, and is only supported to enable integration in environments where client credentials (ID and secret) cannot be used. You might need to use user accounts if your access management system does not support another approach or user accounts are required for authentication. A typical approach is to create a special user account in your authorization server that represents your client application. You then give the account a long randomly generated password and a very limited set of permissions. For example, the account can only connect to your Kafka cluster, but is not allowed to use any other services or login to the user interface. Consider using a refresh token mechanism first. You can configure the address of your authorization server in the tokenEndpointUri property together with the client ID, username and the password used in authentication. The OAuth client will connect to the OAuth server, authenticate using the username, the password, the client ID, and optionally even the client secret to obtain an access token which it will use to authenticate with the Kafka broker. In the passwordSecret property, specify a link to a Secret containing the password. Normally, you also have to configure a clientId using a public OAuth client. If you are using a confidential OAuth client, you also have to configure a clientSecret . An example of OAuth client authentication using username and a password with a public client authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token username: my-username passwordSecret: secretName: my-password-secret-name password: my-password-field-name clientId: my-public-client-id An example of OAuth client authentication using a username and a password with a confidential client authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token username: my-username passwordSecret: secretName: my-password-secret-name password: my-password-field-name clientId: my-confidential-client-id clientSecret: secretName: my-confidential-client-oauth-secret key: client-secret Optionally, scope and audience can be specified if needed. TLS Accessing the OAuth server using the HTTPS protocol does not require any additional configuration as long as the TLS certificates used by it are signed by a trusted certification authority and its hostname is listed in the certificate. If your OAuth server is using certificates which are self-signed or are signed by a certification authority which is not trusted, you can configure a list of trusted certificates in the custom resource. The tlsTrustedCertificates property contains a list of secrets with key names under which the certificates are stored. The certificates must be stored in X509 format. An example of TLS certificates provided authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token clientId: my-client-id refreshToken: secretName: my-refresh-token-secret key: refresh-token tlsTrustedCertificates: - secretName: oauth-server-ca certificate: tls.crt The OAuth client will by default verify that the hostname of your OAuth server matches either the certificate subject or one of the alternative DNS names. If it is not required, you can disable the hostname verification. An example of disabled TLS hostname verification authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token clientId: my-client-id refreshToken: secretName: my-refresh-token-secret key: refresh-token disableTlsHostnameVerification: true 78.1. KafkaClientAuthenticationOAuth schema properties The type property is a discriminator that distinguishes use of the KafkaClientAuthenticationOAuth type from KafkaClientAuthenticationTls , KafkaClientAuthenticationScramSha256 , KafkaClientAuthenticationScramSha512 , KafkaClientAuthenticationPlain . It must have the value oauth for the type KafkaClientAuthenticationOAuth . Property Property type Description accessToken GenericSecretSource Link to OpenShift Secret containing the access token which was obtained from the authorization server. accessTokenIsJwt boolean Configure whether access token should be treated as JWT. This should be set to false if the authorization server returns opaque tokens. Defaults to true . audience string OAuth audience to use when authenticating against the authorization server. Some authorization servers require the audience to be explicitly set. The possible values depend on how the authorization server is configured. By default, audience is not specified when performing the token endpoint request. clientId string OAuth Client ID which the Kafka client can use to authenticate against the OAuth server and use the token endpoint URI. clientSecret GenericSecretSource Link to OpenShift Secret containing the OAuth client secret which the Kafka client can use to authenticate against the OAuth server and use the token endpoint URI. connectTimeoutSeconds integer The connect timeout in seconds when connecting to authorization server. If not set, the effective connect timeout is 60 seconds. disableTlsHostnameVerification boolean Enable or disable TLS hostname verification. Default value is false . enableMetrics boolean Enable or disable OAuth metrics. Default value is false . httpRetries integer The maximum number of retries to attempt if an initial HTTP request fails. If not set, the default is to not attempt any retries. httpRetryPauseMs integer The pause to take before retrying a failed HTTP request. If not set, the default is to not pause at all but to immediately repeat a request. includeAcceptHeader boolean Whether the Accept header should be set in requests to the authorization servers. The default value is true . maxTokenExpirySeconds integer Set or limit time-to-live of the access tokens to the specified number of seconds. This should be set if the authorization server returns opaque tokens. passwordSecret PasswordSecretSource Reference to the Secret which holds the password. readTimeoutSeconds integer The read timeout in seconds when connecting to authorization server. If not set, the effective read timeout is 60 seconds. refreshToken GenericSecretSource Link to OpenShift Secret containing the refresh token which can be used to obtain access token from the authorization server. scope string OAuth scope to use when authenticating against the authorization server. Some authorization servers require this to be set. The possible values depend on how authorization server is configured. By default scope is not specified when doing the token endpoint request. tlsTrustedCertificates CertSecretSource array Trusted certificates for TLS connection to the OAuth server. tokenEndpointUri string Authorization server token endpoint URI. type string Must be oauth . username string Username used for the authentication.	[ "authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token clientId: my-client-id clientSecret: secretName: my-client-oauth-secret key: client-secret", "authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token clientId: my-client-id refreshToken: secretName: my-refresh-token-secret key: refresh-token", "authentication: type: oauth accessToken: secretName: my-access-token-secret key: access-token", "authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token username: my-username passwordSecret: secretName: my-password-secret-name password: my-password-field-name clientId: my-public-client-id", "authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token username: my-username passwordSecret: secretName: my-password-secret-name password: my-password-field-name clientId: my-confidential-client-id clientSecret: secretName: my-confidential-client-oauth-secret key: client-secret", "authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token clientId: my-client-id refreshToken: secretName: my-refresh-token-secret key: refresh-token tlsTrustedCertificates: - secretName: oauth-server-ca certificate: tls.crt", "authentication: type: oauth tokenEndpointUri: https://sso.myproject.svc:8443/auth/realms/internal/protocol/openid-connect/token clientId: my-client-id refreshToken: secretName: my-refresh-token-secret key: refresh-token disableTlsHostnameVerification: true" ]	https://docs.redhat.com/en/documentation/red_hat_streams_for_apache_kafka/2.7/html/streams_for_apache_kafka_api_reference/type-KafkaClientAuthenticationOAuth-reference
Chapter 9. Changes in 3scale	Chapter 9. Changes in 3scale Note In 3scale 2.14, support for deploying databases within the cluster as part of the standard 3scale deployment was deprecated. In 3scale 2.16, Red Hat supports only self-deployed databases, whether within the cluster or external to it. This section lists current and future 3scale changes. Deprecated features 3scale support for OpenTracing is now deprecated in favor of OpenTelemetry. In the upcoming version, 3scale 2.16, OpenTracing will no longer be available. 3scale Toolbox Command Line Tool is deprecated and we will no longer incorporate further enhancements. The recommended way for provisioning and automation needs, is the 3scale Application Capabilities operator. OpenShift APIs for Data Protection is now the standard and recommended backup and restore mechanism in 3scale. The old backup and restore procedures are deprecated and will be removed from future versions documentation. 3scale no longer supports slaves for Redis configurations. If slaves are enabled on internal Redis configurations, the operator will override and disable them.	null	https://docs.redhat.com/en/documentation/red_hat_3scale_api_management/2.15/html/release_notes_for_red_hat_3scale_api_management_2.15_on-premises/changes_in_3scale
Chapter 10. Upgrading	Chapter 10. Upgrading The upgrade of the OpenShift sandboxed containers components consists of the following steps: Upgrade OpenShift Container Platform to update the Kata runtime and its dependencies. Upgrade the OpenShift sandboxed containers Operator to update the Operator subscription. You can upgrade OpenShift Container Platform before or after the OpenShift sandboxed containers Operator upgrade, with the one exception noted below. Always apply the KataConfig patch immediately after upgrading the OpenShift sandboxed containers Operator. 10.1. Upgrading resources Red Hat Enterprise Linux CoreOS (RHCOS) extensions deploy the OpenShift sandboxed containers resources onto the cluster. The RHCOS extension sandboxed containers contains the required components to run OpenShift sandboxed containers, such as the Kata containers runtime, the hypervisor QEMU, and other dependencies. You upgrade the extension by upgrading the cluster to a new release of OpenShift Container Platform. For more information about upgrading OpenShift Container Platform, see Updating Clusters . 10.2. Upgrading the Operator Use Operator Lifecycle Manager (OLM) to upgrade the OpenShift sandboxed containers Operator either manually or automatically. Selecting between manual or automatic upgrade during the initial deployment determines the future upgrade mode. For manual upgrades, the OpenShift Container Platform web console shows the available updates that the cluster administrator can install. For more information about upgrading the OpenShift sandboxed containers Operator in Operator Lifecycle Manager (OLM), see Updating installed Operators . 10.3. Updating the pod VM image For AWS, Azure, and IBM deployments, you must update the pod VM image. Upgrading the OpenShift sandboxed containers Operator when the enablePeerpods: paramter is true will not update the existing pod VM image automatically. To update the pod VM image after an upgrade you must delete and re-create the KataConfig CR. Note You can also check the peer pod config map for AWS and Azure deployments to ensure that the image ID is empty before re-creating the KataConfig CR. 10.3.1. Deleting the KataConfig custom resource You can delete the KataConfig custom resource (CR) by using the command line. Prerequisites You have installed the OpenShift CLI ( oc ). You have access to the cluster as a user with the cluster-admin role. Procedure Delete the KataConfig CR by running the following command: USD oc delete kataconfig example-kataconfig Verify that the custom resource was deleted by running the following command: USD oc get kataconfig example-kataconfig Example output No example-kataconfig instances exist 10.3.2. Ensure peer pods CM image ID is empty When you delete the KataConfig CR, it should delete the peer pods CM image ID. For AWS and Azure deployments, check to ensure that the peer pods CM image ID is empty. Procedure Obtain the config map you created for the peer pods: USD oc get cm -n openshift-sandboxed-containers-operator peer-pods-cm -o jsonpath="{.data.AZURE_IMAGE_ID}" Use PODVM_AMI_ID for AWS. Use AZURE_IMAGE_ID for Azure. Check the status stanza of the YAML file. If the PODVM_AMI_ID parameter for AWS or the AZURE_IMAGE_ID parameter for Azure contains a value, set the value to "". If you have set the value to "", patch the peer pods config map: USD oc patch configmap peer-pods-cm -n openshift-sandboxed-containers-operator -p '{"data":{"AZURE_IMAGE_ID":""}}' Use PODVM_AMI_ID for AWS. Use AZURE_IMAGE_ID for Azure. 10.3.3. Creating the KataConfig custom resource You must create the KataConfig custom resource (CR) to install kata-remote as a runtime class on your worker nodes. Creating the KataConfig CR triggers the OpenShift sandboxed containers Operator to do the following: Create a RuntimeClass CR named kata-remote with a default configuration. This enables users to configure workloads to use kata-remote as the runtime by referencing the CR in the RuntimeClassName field. This CR also specifies the resource overhead for the runtime. OpenShift sandboxed containers installs kata-remote as a secondary, optional runtime on the cluster and not as the primary runtime. Important Creating the KataConfig CR automatically reboots the worker nodes. The reboot can take from 10 to more than 60 minutes. Factors that impede reboot time are as follows: A larger OpenShift Container Platform deployment with a greater number of worker nodes. Activation of the BIOS and Diagnostics utility. Deployment on a hard disk drive rather than an SSD. Deployment on physical nodes such as bare metal, rather than on virtual nodes. A slow CPU and network. Prerequisites You have access to the cluster as a user with the cluster-admin role. Procedure Create an example-kataconfig.yaml manifest file according to the following example: apiVersion: kataconfiguration.openshift.io/v1 kind: KataConfig metadata: name: example-kataconfig spec: enablePeerPods: true logLevel: info # kataConfigPoolSelector: # matchLabels: # <label_key>: '<label_value>' 1 Create the KataConfig CR by running the following command: USD oc apply -f example-kataconfig.yaml The new KataConfig CR is created and installs kata-remote as a runtime class on the worker nodes. Wait for the kata-remote installation to complete and the worker nodes to reboot before verifying the installation. Monitor the installation progress by running the following command: USD watch "oc describe kataconfig \| sed -n /^Status:/,/^Events/p" When the status of all workers under kataNodes is installed and the condition InProgress is False without specifying a reason, the kata-remote is installed on the cluster. Verify the daemon set by running the following command: USD oc get -n openshift-sandboxed-containers-operator ds/peerpodconfig-ctrl-caa-daemon Verify the runtime classes by running the following command: USD oc get runtimeclass Example output NAME HANDLER AGE kata kata 152m kata-remote kata-remote 152m	[ "oc delete kataconfig example-kataconfig", "oc get kataconfig example-kataconfig", "No example-kataconfig instances exist", "oc get cm -n openshift-sandboxed-containers-operator peer-pods-cm -o jsonpath=\"{.data.AZURE_IMAGE_ID}\"", "oc patch configmap peer-pods-cm -n openshift-sandboxed-containers-operator -p '{\"data\":{\"AZURE_IMAGE_ID\":\"\"}}'", "apiVersion: kataconfiguration.openshift.io/v1 kind: KataConfig metadata: name: example-kataconfig spec: enablePeerPods: true logLevel: info kataConfigPoolSelector: matchLabels: <label_key>: '<label_value>' 1", "oc apply -f example-kataconfig.yaml", "watch \"oc describe kataconfig \| sed -n /^Status:/,/^Events/p\"", "oc get -n openshift-sandboxed-containers-operator ds/peerpodconfig-ctrl-caa-daemon", "oc get runtimeclass", "NAME HANDLER AGE kata kata 152m kata-remote kata-remote 152m" ]	https://docs.redhat.com/en/documentation/openshift_sandboxed_containers/1.8/html/user_guide/upgrading
CLI tools	CLI tools OpenShift Container Platform 4.13 Learning how to use the command-line tools for OpenShift Container Platform Red Hat OpenShift Documentation Team	null	https://docs.redhat.com/en/documentation/openshift_container_platform/4.13/html/cli_tools/index
14.22.7. Getting Information about a Virtual Network	14.22.7. Getting Information about a Virtual Network This command returns basic information about the network object. To get the network information, run:	[ "virsh net-info network" ]	https://docs.redhat.com/en/documentation/red_hat_enterprise_linux/6/html/virtualization_administration_guide/sub-sect-virtual_networking_commands-getting_information_about_a_virtual_network