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Setting up logging for Elasticsearch to track errors and issues.

Setting up logging for Elasticsearch to track errors and issues.

Setting up logging for Elasticsearch to track errors and issues.


Setting up logging for Elasticsearch

Monitoring and diagnosing issues in your Elasticsearch cluster are essential for maintaining optimal performance. Leveraging Elasticsearch’s application logs provides valuable insights, and understanding the logging configuration is a key aspect of effective cluster management.


Logging Configuration: Log4j 2

Elasticsearch strongly recommends using the default Log4j 2 configuration. Log4j 2 is the logging tool of choice, configured through the log4j2.properties file. Elasticsearch exposes three crucial properties: ${sys:es.logs.base_path}, ${sys:es.logs.cluster_name}, and ${sys:es.logs.node_name}, allowing you to determine the log file’s location.

For example, if your log directory is /var/log/elasticsearch, and your cluster is named ‘production’, ${sys:es.logs.base_path} resolves to /var/log/elasticsearch, and ${sys:es.logs.base_path}${sys:file.separator}${sys:es.logs.cluster_name}.log resolves to /var/log/elasticsearch/production.log.


Server JSON Configuration

To configure the RollingFile appender, log to /var/log/elasticsearch/production_server.json, use JSON layout, and implement a time-based roll policy with logs rolling on a daily basis. Compression occurs with each log roll, activating a size-based roll policy after reaching 256 MB.Conditional deletion is in place, removing primary logs only when an abundance of compressed logs accumulates, surpassing the 2GB threshold.

[... Server JSON Configuration ...]

Old Style Pattern Configuration (Deprecated)

For the old style pattern, logs will be saved in .log files and archived in .log.gz files. Please be aware that this method is deprecated and will be phased out in upcoming versions.

[... Old Style Pattern Configuration ...]

Configuring Logging Levels

Each Java package in the Elasticsearch source code has a related logger, allowing you to control verbosity levels. Use the cluster update settings API to adjust log levels, with options ranging from OFF to TRACE. The default log level is INFO. Additional ways to change log levels include modifying elasticsearch.yml or log4j2.properties.


Deprecation Logging

Elasticsearch records deprecation messages when deprecated functionality is used, writing them to the log directory. These logs aid in updating applications before upgrading to a new major version. To manage deprecation log messages, set logger.deprecation.level to OFF in log4j2.properties, or dynamically change the logging level through the cluster settings API.

PUT /_cluster/settings
"persistent": {
"logger.org.elasticsearch.deprecation": "OFF"

Deprecation Logs Throttling

Deprecation logs are deduplicated based on a deprecated feature key and x-opaque-id to prevent overloading. Disable x-opaque-id in throttling by changing cluster.deprecation_indexing.x_opaque_id_used.enabled to false.


JSON Log Format

Elasticsearch now presents logs in a simplified JSON format, making parsing more straightforward. The ECSJsonLayout type, configured by appender.rolling.layout.type = ECSJsonLayout, requires a dataset attribute to distinguish log streams when parsing.

appender.rolling.layout.type = ECSJsonLayout
appender.rolling.layout.dataset = elasticsearch.server



In conclusion, setting up logging for Elasticsearch is a crucial aspect of maintaining a healthy cluster. Whether configuring log formats, adjusting levels, or managing deprecation logs, understanding and optimizing your logging strategy is essential for effective Elasticsearch administration.

For more detailed information, refer to the official Elasticsearch logging documentation. Additionally, consider seeking advice from a trusted Elasticsearch expert for personalized recommendations and insights tailored to your specific needs.

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