How to configure logging in Docker and centrally collect logs from containers?

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Proper organization of log collection and storage is an integral part of supporting applications in any modern information system. By default, Docker saves standard output and error streams of each container to local text files on the host machine's disk, which creates difficulties when scaling infrastructure and analyzing problems in a distributed environment.

To manage record output, a logging driver system is used, which allows redirecting the data stream from containers to various external storage and analysis systems. The choice of a specific driver is made at the global Docker daemon configuration level or individually for each launched service.

Popular integration drivers support sending data to centralized monitoring systems such as Elasticsearch, Fluentd, Graylog, or cloud-based metrics collection services. This allows aggregating information from hundreds of microservices into a single search interface, building charts, and setting up automated error alerts.

1. Choose a suitable centralized data collection system in accordance with the project's storage and analysis requirements.
2. Configure the logging driver parameters in the container or orchestrator configuration file, specifying the receiver address.
3. Limit the maximum size of local log files using special driver parameters to avoid filling up the host disk.
4. Ensure that the application inside the container correctly outputs text messages to standard output rather than trying to write them to local files.

Proper logging configuration saves the team from having to connect to each specific server to find the cause of a failure. A centralized approach ensures application transparency and accelerates the process of debugging incidents in a production environment.

How to configure logging in Docker and centrally collect logs from containers?

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