Analyze and use Structured log data

Some choices are: AWS CloudWatch, Datadog, Dynatrace, Elastic, or Splunk. Your observability platform contains several tools for indexing logs and displaying them in human-readable dashboards.

Some choices are: AWS CloudWatch Agent, Datadog Agent, Dynatrace OneAgent, Filebeat or Logstash (Elastic Stack), or Splunk Universal Forwarder or Splunk HTTP Event Collector (HEC).

• If your company has an observability subject matter expert (SME), consult them to determine what architecture to use to index your logs. You may want to ingest logs in multiple environments, each with unique requirements.

• If your company doesn't have an observability SME, contact Liquibase Support for assistance.

• Note: Configuration of an external tool may not be entirely covered by your Liquibase support plan.

Some choices are: AWS CloudWatch Logs Insights, Datadog Logs Processing Pipeline, Dynatrace Log Management and Analytics, Elasticsearch or Logstash, or Splunk Indexer. Consult your observability SME for guidance.

You must query the logs you have ingested and indexed and send this data to your dashboard to represent it visually. The Liquibase Observability-Dashboards repository on GitHub contains several sample dashboards for common metrics. For a list of keys (endpoints) you can include in your queries, see Structured Logging Keys.

Ensure that your logging jobs run automatically after every Liquibase operation in your pipeline. Using your indexed logs, write queries that automatically notify you of problematic behavior. You can also use Liquibase Operation Reports to receive information about common Liquibase operations.