Kubernetes at Scale: Production Lessons Learned

Running Kubernetes at scale presents unique challenges. What works for a 3-node cluster often breaks at 500 nodes. In this article, we share lessons learned from production deployments managing thousands of containers for our enterprise clients.

Lesson 1: Resource Management Is Critical

Properly configure resource requests and limits for all containers. "Requests" guarantee the resources a container gets, while "limits" cap what it can use. Without this, you'll face unpredictable scheduling (Noisy Neighbor problem), evictions, and performance issues. Always set memory limits to prevent OOM kills taking down the node.

Lesson 2: Monitoring and Observability

Implement comprehensive monitoring from day one. You can't ssh into a server to check logs anymore. Track cluster health (etcd latency, API server readiness), node status, and pod metrics. Use structured logging and distributed tracing (Jaeger/Zipkin) to follow requests across services.