Basic Container Logging

Logging is a critical part of any application lifecycle, providing insights into application behavior, identifying issues, and tracking performance. In containerized environments, logging works slightly differently compared to traditional applications due to the ephemeral nature of containers. This article will cover the basics of container logging, common practices, and how to set up simple logging for containerized applications.

Why Container Logging is Important

Containers bundle applications with their dependencies into isolated units. While this isolation aids deployment and scalability, it complicates logging. Since containers are transient and may shut down unexpectedly, collecting and retaining logs is essential for debugging and monitoring.

Without proper logging:

• It becomes difficult to troubleshoot issues after a container stops running.
• Valuable insights into container performance, errors, and application behavior may be lost.
• Ensuring compliance and tracking for auditing purposes is hindered.

How Logging Works in Containers

Containers typically follow the "log to stdout and stderr" principle. This means that logs generated within a containerized application are directed to the container's standard output (stdout) and standard error (stderr) streams. These logs are then collected by the container runtime or orchestration platform and are available for review even after the container terminates.

Key Concepts:

• stdout (Standard Output): Regular logs, such as status updates, operational messages, or results from normal operations.
• stderr (Standard Error): Error logs, including warnings, exceptions, or any failure points within the application.

For most container runtimes (like Docker), these streams are captured and stored locally on the host machine, typically as JSON files. However, relying solely on local storage is not scalable in production environments where centralized log aggregation is necessary.

Basic Logging with Docker

In a Docker-based environment, containers use the default logging driver, which captures stdout and stderr. The default Docker logging driver, json-file, stores logs as JSON objects on the host filesystem.

Example: Viewing Logs in Docker

To view logs from a running or stopped container, you can use the docker logs command:

docker logs <container_id>

This command displays the logs captured from the container's stdout and stderr. You can also tail the logs or filter them by timestamps.

• Tail logs in real-time:

  docker logs -f <container_id>

• Show logs since a specific time:

  docker logs --since "2023-09-15T00:00:00" <container_id>

Challenges of Container Logging

While logging to stdout and stderr works in many cases, it has several limitations:

• Limited log retention: Logs stored locally may be lost if the container is deleted, or the host system restarts.
• Scaling issues: For large-scale deployments, local storage quickly becomes unmanageable.
• No aggregation: Logs are isolated per container, making it difficult to analyze logs from multiple containers.

Best Practices for Container Logging

Use Centralized logging

Rely on a centralized logging solution to collect logs from all containers in your environment. This ensures logs are retained and accessible even if containers are deleted. Popular logging tools include:

• ELK Stack (Elasticsearch, Logstash, Kibana)
• Fluentd
• Promtail and Loki (for Grafana integration)

Structured logging

Emit logs in a structured format like JSON, which makes it easier to parse and analyze log data.

Log Rotationlogging

Ensure log rotation is configured to prevent logs from consuming excessive disk space. Many logging drivers allow you to set log size limits and rotation policies.

Logging Driverslogging

Use appropriate logging drivers or plugins depending on your infrastructure. For example, Docker supports logging drivers like json-file, syslog, journald, and third-party solutions like gelf for integration with Graylog or awslogs for AWS CloudWatch integration.

Security Considerationslogging

Ensure logs do not contain sensitive information, such as credentials or personal data. Use encryption and access control to safeguard log data.