Understanding Logging in Kubernetes - From Containers to Nodes

Logging is an essential component of monitoring and maintaining applications, particularly in a complex environment like Kubernetes. Logs provide valuable insights into how an application behaves, identifying errors, performance issues, and security threats. However, logging in Kubernetes is challenging due to the dynamic and distributed nature of the platform. This blog post will explain where logs originate within Kubernetes, the importance of log collectors, and compare popular logging solutions such as Fluentd, Fluent Bit, and AWS CloudWatch Container Insights.

Where Do Logs Come From in Kubernetes?

In Kubernetes, logs are generated at various layers, including:

• Containers: Each container in a Kubernetes pod generates its own logs. These logs are written to the container’s standard output (stdout) and standard error (stderr). The container runtime (such as Docker or containerd) manages these logs.

• Pods: Since a pod can have multiple containers, it aggregates logs from all its containers. However, Kubernetes does not automatically store or forward pod logs. They are ephemeral and typically vanish when a pod is terminated or restarted.

• Nodes: Each Kubernetes node has a logging agent that collects logs from all the pods running on the node. These logs are stored locally on the node, but like pod logs, they are temporary and could be lost if the node fails or is replaced.

Why Not Just Use AWS CloudWatch for EKS?

AWS CloudWatch is a powerful tool for monitoring and logging in AWS environments, including Elastic Kubernetes Service (EKS). While it may seem convenient to use CloudWatch for EKS logging, it has limitations when managing the full spectrum of log collection and processing needs.

Limitations of AWS CloudWatch for Kubernetes Logging:

• Lack of Flexibility: CloudWatch works well for simple, centralized logging, but it may not offer the flexibility needed to manage complex Kubernetes environments. It doesn’t support advanced log parsing, enrichment, or filtering natively, which are often required in real-world applications.

• Cost Management: CloudWatch pricing is based on the volume of logs ingested and stored. In a Kubernetes environment where log volumes can grow exponentially, this can lead to unexpectedly high costs without offering enough control over data retention and processing.

• Multi-cluster Aggregation: Kubernetes often runs across multiple clusters. CloudWatch isn’t designed to natively support cross-cluster log aggregation, which can make it challenging to get a unified view of your logs.

Given these challenges, many teams opt for specialized log collectors to gain better control over their logging infrastructure.

The Need for a Log Collector

A log collector is a tool designed to aggregate, process, and forward logs from different parts of the Kubernetes infrastructure. Instead of relying solely on CloudWatch, a log collector allows you to:

• Process Logs Efficiently: Filter and transform logs in real time, only forwarding the necessary information to CloudWatch or other logging backends.

• Enhance Log Enrichment: Enrich logs with additional metadata like pod labels, namespace, or node name, making it easier to analyze and search through logs.

• Optimize Cost: Reduce the volume of logs sent to CloudWatch by filtering irrelevant logs, thus minimizing cost.

• Centralized Aggregation: Collect logs from multiple clusters, enabling better observability across environments.

Comparison of Popular Log Collectors: Fluentd, Fluent Bit, and AWS CloudWatch Container Insights

There are several tools available for collecting and managing logs in Kubernetes, including Fluentd, Fluent Bit, and AWS CloudWatch Container Insights. Each tool has its own advantages and trade-offs.

Fluentd

• Overview: Fluentd is a full-fledged, open-source data collector designed to unify log data. It offers a wide range of plugins to integrate with various systems like Elasticsearch, S3, and CloudWatch.

• Pros:

  • Highly customizable with over 500 plugins.

  • Supports advanced log processing, filtering, and transformation.

  • Works well in large, complex environments with heavy log processing needs.

• Cons:

  • Heavier in terms of resource consumption due to its more extensive feature set.

  • Requires more configuration and tuning, which can be complex.

• Use Case: Best suited for large-scale Kubernetes clusters where complex log management and advanced processing are needed.

Fluent Bit

• Overview: Fluent Bit is a lightweight, fast log processor and forwarder that is part of the Fluentd ecosystem. It shares much of Fluentd’s functionality but with a lower resource footprint, making it ideal for environments with limited resources.

• Pros:

  • Lightweight and fast, ideal for resource-constrained environments.

  • Supports many of the same plugins as Fluentd, including integration with AWS services.

  • Less configuration overhead than Fluentd.

• Cons:

  • Limited advanced processing capabilities compared to Fluentd.

  • Not as feature-rich, which may limit its use in more complex log aggregation pipelines.

• Use Case: Ideal for lightweight logging needs, edge devices, or smaller Kubernetes clusters where resource efficiency is a priority.

AWS CloudWatch Container Insights

• Overview: AWS CloudWatch Container Insights is a managed service provided by AWS to collect, aggregate, and visualize logs and metrics from your containerized applications on EKS.

• Pros:

  • Seamless integration with AWS services, no need for additional setup.

  • Provides built-in visualizations and monitoring for Kubernetes metrics and logs.

  • Simplifies log collection for AWS-native Kubernetes environments.

• Cons:

  • Limited customization and flexibility compared to Fluentd and Fluent Bit.

  • Can become expensive as log volume increases.

  • Primarily focuses on AWS, lacking multi-cloud or on-premise integration options.

• Use Case: Best suited for teams fully committed to the AWS ecosystem and those looking for a managed logging service with minimal setup.

Conclusion

Logging in Kubernetes requires more than just capturing container output; it involves orchestrating logs across multiple layers of the platform. AWS CloudWatch can handle basic logging, but to get the most out of your logs while optimizing costs, a dedicated log collector is often necessary. Fluentd, Fluent Bit, and AWS CloudWatch Container Insights each provide unique benefits depending on your environment’s scale and complexity.

• Fluentd: Best for complex environments requiring extensive log processing and integration.

• Fluent Bit: Lightweight and efficient for smaller clusters or environments where resource usage is a concern.

• AWS CloudWatch Container Insights: An excellent option for those who want AWS-native integration with minimal setup but may not need the flexibility of the other solutions.

By choosing the right log collection strategy, you can ensure better observability and performance in your Kubernetes clusters while keeping costs under control.