anchor.diff:  2016-11-23T16:04:01.49-0800 [RTR/0]      OUT www.example.com - [24/11/2016:00:04:01.227 +0000] "GET / HTTP/1.1" 200 0 109 "-" "curl/7.43.0" 10.0.2.150:4070 10.0.48.66:60815 x_forwarded_for:"198.51.100.120" x_forwarded_proto:"http" vcap_request_id:87f9d899-c7a4-46cd-7b76-4ec35ce9921b response_time:0.263000966 app_id:8e5d6451-b369-4423-bce8-3a7a9e479dbb app_index:0 x_b3_traceid:"2d5610bf5e0f7241" x_b3_spanid:"2d5610bf5e0f7241" x_b3_parentspanid:"-"
   </pre>
   
  -For more information about Zipkin tracing, see the [Zipkin Tracking in HTTP Headers](../../concepts/http-routing.html#zipkin-headers) topic.
  +For more information about Zipkin tracing, see [Zipkin Tracking in HTTP Headers](../../concepts/http-routing.html#zipkin-headers).
   
   ### <a id='lgr'></a>LGR ###
   
  
positive.code: See [Third-Party Log Management Services](../services/log-management.html).
  
  Cloud Foundry gathers and stores logs in a best-effort manner.
  If a client is unable to consume log lines quickly enough, the Loggregator
  buffer may need to overwrite some lines before the client has consumed them.
  A syslog drain or a CLI tail can usually keep up with the flow of app
  logs.
  
negative.code:     ...
  </pre>
  
  ### <a id='log-ordering'></a> Log Ordering
  
  Ensuring log ordering in drains can be an important consideration for both operators and developers. 
  
  * Diego uses a nanosecond-based timestamp that can be ingested properly by Splunk. For more information, see [TIME_FORMAT and subseconds](https://answers.splunk.com/answers/1946/time-format-and-subseconds.html) in the Splunk documentation.
  * The Elastic Stack can ingest the nanosecond timestamps but only supports millisecond precision, so timestamps are truncated. For more information, see the [Date datatype](https://www.elastic.co/guide/en/elasticsearch/reference/current/date.html) in the Elasticsearch documentation and the [Date type has not enough precision for the logging use case](https://github.com/elastic/elasticsearch/issues/10005) GitHub issue.
  
  If you are developing a client that displays a stream of Cloud Foundry logs to users, you can order the logs to improve the debugging experience for your user. The following are general tips for ordering logs:
  
  * For CLIs, batch the logs and display the logs you have in that timeframe, sorted by timestamp.
  * For web clients, use dynamic HTML to insert older logs into the sorting as they appear. This creates complete, ordered logs.
  * Java app developers may want to convert stack traces into a single log entity. To simplify log ordering for Java apps, use the [multi-line Java message workaround](https://github.com/cloudfoundry/loggregator-release/blob/develop/docs/java-multi-line-work-around.md) to convert your multi-line stack traces into a single log entity.
  <br><br>By modifying the Java log output, you can force your app to reformat stack trace messages, replacing newline characters with a token. Set your log parsing code to replace that token with newline characters again to display the logs properly in Kibana.
  