Question

What’s the best way to handle large log files generated by Docker containers?

This question seeks the various methods of controlling and managing the size of log files that Docker containers produce. This also seeks the avoidance of unnecessary logs to prevent overload in the disk space, optimizes storage for logs, and assures that log management will not degrade the performance of containers.

Answer 1

 In production, a Docker container generates a huge amount of log data. This would result in performance issues and quickly burn through storage. It provides several logging drivers - json-file (the default), syslog, fluentd, and journald.

Log Rotation: The log rotation should be done in such a way that not a single log file goes too large. Indicate max-size for example with "10m" - the size of the file and max-file for instance with "3" showing the number of files to hold in the daemon.json file.

External Logging Solutions: Commercial solutions like ELK stack (Elasticsearch, Logstash, Kibana), Splunk or other powerful tools can be used for indexing, search, and visualization of the log data.

Container:Aggregation: Log gathering from multiple containers can be done with Fluentd, Logstash, or Graylog. On the flip side, it gives control and central analysis of logs.

Optimize Log Levels: Append an optimum logging level to your application (e.g. INFO, ERROR, DEBUG) to avoid informational detail logging in a method that reduces volume. Avoid debugging in a verbosity of high in production environments for log manageability.

Monitoring and Alerts: Alerts should be set up to monitor specific log patterns or spikes in log volume. This helps detect unusual behavior early, allowing for proactive troubleshooting and resolution.