Mastering Kubernetes Logging Architecture: What You Need to Know

In the world of Kubernetes, effective logging architecture is not just a nice-to-have; it’s essential for observability and troubleshooting. Cluster-level logging architectures require a separate backend to store, analyze, and query logs, ensuring that you can access and interpret your application’s behavior in real time. Without a solid logging strategy, you risk losing critical insights into your applications, leading to prolonged downtime and frustrating debugging sessions.

Kubernetes captures logs from each container in a running Pod, with the kubelet handling the output generated to stdout and stderr streams. By default, if a container restarts, the kubelet retains one terminated container along with its logs. You can configure parameters like containerLogMaxSize, which sets the maximum size for each log file to 10Mi, and containerLogMaxFiles, which limits the number of files per container to 5. The kubelet also manages log rotation and makes logs available via the Kubernetes API. For example, you can retrieve logs using commands like kubectl logs counter or access previous logs with kubectl logs --previous.

In production, be cautious with the default log directory at /var/log/pods, as many processes may rely on this path. Changing it can lead to unexpected issues. Additionally, if your logs reside on a separate filesystem from /var, the kubelet won't track its usage, which could result in filling up that filesystem. Remember, Kubernetes does not manage log rotation for cluster components deployed to shared volumes, so you need to implement your own rotation strategy. Always keep your Kubernetes version in mind; for instance, version 1.36 allows direct access to log streams via the Pod API, enhancing your logging capabilities.