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   toc::[]
   
  -A {prodname} connector works in the Kafka Connect framework to capture each row-level change in a database by generating a change event record. For each change event record, the {prodname} connector does the following: 
  -
  -. Applies configured transformations
  -. Serializes the record key and value into a binary form by using the configured link:https://kafka.apache.org/documentation/#connect_running[Kafka Connect converters]
  -. Writes the record to the correct Kafka topic
  -
  -You can specify converters for each individual {prodname} connector instance. Kafka Connect provides a JSON converter that serializes the record keys and values into JSON documents. The default behavior is that the JSON converter includes the record's message schema, which makes each record very verbose. The {link-prefix}:{link-tutorial}[{name-tutorial}] shows what the records look like when both payload and schemas are included. If you want records to be serialized with JSON, consider setting the following connector configuration properties to `false`: 
  +A {prodname} connector works in the Kafka Connect framework to capture each row-level change in a database by generating a change event record. 
  +For each change event record, the {prodname} connector completes the following actions: 
  +
  +. Applies configured transformations.
  +. Serializes the record key and value into a binary form by using the configured link:https://kafka.apache.org/documentation/#connect_running[Kafka Connect converters].
  +. Writes the record to the correct Kafka topic.
  +
  +You can specify converters for each individual {prodname} connector instance. 
  +Kafka Connect provides a JSON converter that serializes the record keys and values into JSON documents. 
  +The default behavior is that the JSON converter includes the record's message schema, which makes each record very verbose. 
  +The {link-prefix}:{link-tutorial}[{name-tutorial}] shows what the records look like when both payload and schemas are included. 
  +If you want records to be serialized with JSON, consider setting the following connector configuration properties to `false`: 
   
   * `key.converter.schemas.enable`
   * `value.converter.schemas.enable`
   
   Setting these properties to `false` excludes the verbose schema information from each record. 
   
  -Alternatively, you can serialize the record keys and values by using https://avro.apache.org/[Apache Avro]. The Avro binary format is compact and efficient. Avro schemas make it possible to ensure that each record has the correct structure. Avro's schema evolution mechanism enables schemas to evolve. This is essential for {prodname} connectors, which dynamically generate each record's schema to match the structure of the database table that was changed. Over time, change event records written to the same Kafka topic might have different versions of the same schema. Avro serialization makes it easier for change event record consumers to adapt to a changing record schema.
  +Alternatively, you can serialize the record keys and values by using https://avro.apache.org/[Apache Avro]. 
  +The Avro binary format is compact and efficient. 
  +Avro schemas make it possible to ensure that each record has the correct structure. 
  +Avro's schema evolution mechanism enables schemas to evolve. 
  +This is essential for {prodname} connectors, which dynamically generate each record's schema to match the structure of the database table that was changed. 
  +Over time, change event records written to the same Kafka topic might have different versions of the same schema. 
  +Avro serialization makes it easier for the consumers of change event records to adapt to a changing record schema.
   
   ifdef::community[]
   To use Apache Avro serialization, you must deploy a schema registry that manages Avro message schemas and their versions. 
  
positive.code: .. Extract the archive into the desired {prodname} connector directory.
  
  +
  To configure more than one type of {prodname} connector to use Avro serialization, extract the archive into the directory for each relevant connector type. While this duplicates the files, it removes the possibility of conflicting dependencies.
  
  . Create and publish a custom image for running {prodname} connectors that are configured to use the Avro converter:
  
  .. Create a new `Dockerfile` by using `{DockerKafkaConnect}` as the base image. In the following example, you would replace _my-plugins_ with the name of your plug-ins directory:
  +
  [subs=+macros]
  ----
  
negative.code: +
  * In the `install/cluster-operator/050-Deployment-strimzi-cluster-operator.yaml` file, edit the `STRIMZI_DEFAULT_KAFKA_CONNECT_IMAGE` variable to point to the new container image and reinstall the Cluster Operator. If you edit this file you will need to apply it to your OpenShift cluster.
  
  . Deploy each {prodname} connector that is configured to use the Avro converter. 
  For each {prodname} connector:  
  
  .. Create a {prodname} connector instance. The following `inventory-connector.yaml` file example creates a `KafkaConnector` custom resource that defines a MySQL connector instance that is configured to use the Avro converter:
  +
  