How to Monitor Kubernetes Logs at Scale

Monitoring Kubernetes logs at scale involves establishing a robust log pipeline to manage high log volumes, ensure durability, and facilitate multi-cluster queries. This process can be streamlined using the openobserve-collector Helm chart, which configures an OpenTelemetry Collector as both a node-level agent and a cluster gateway, or by custom-assembling components like Fluent Bit and OpenTelemetry Collector for more granular control over memory usage and filtering. Logs should be sent to a backend that minimizes storage costs, such as an object-store-native system like OpenObserve, which supports long-term retention affordably. Efficient filtering and sampling should be implemented to reduce unnecessary data transfer and storage, while maintaining a health dashboard to monitor pipeline performance metrics such as queue depth and export errors. Ultimately, the goal is to create a scalable, efficient logging system that supports querying across multiple clusters without needing extensive infrastructure like a Kafka cluster.

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