Kubernetes in Production: Lessons from the Trenches
Real-world experiences and battle-tested strategies for running Kubernetes clusters at scale.
Running Kubernetes in production environments requires more than just understanding the basics. After managing clusters serving millions of requests daily, we've learned valuable lessons about what works, what doesn't, and what truly matters.
Cluster Architecture Decisions
The foundation of a stable Kubernetes environment starts with smart architectural choices that balance reliability, cost, and operational complexity.
Multi-Tenancy vs. Dedicated Clusters
Shared clusters reduce overhead but increase blast radius. We've found that separating production and non-production workloads into distinct clusters prevents development mistakes from affecting live services. For large organizations, consider dedicated clusters per business unit or compliance boundary.
Node Pool Strategy
Use multiple node pools with different machine types to optimize costs. Run stateless workloads on preemptible instances, reserve standard instances for stateful services, and use high-memory nodes for data processing. Taints and tolerations ensure pods land on appropriate nodes.
Resource Management
Requests and Limits
Setting appropriate resource requests and limits is critical for cluster stability. Requests determine scheduling decisions—set them based on actual usage, not wishful thinking. Limits prevent runaway processes from affecting neighbors.
Quality of Service Classes
Understand how Kubernetes uses QoS classes to make eviction decisions:
- Guaranteed — Requests equal limits, highest priority
- Burstable — Requests less than limits, medium priority
- BestEffort — No requests or limits, first to be evicted
Networking Architecture
Service Mesh Considerations
Service meshes like Istio and Linkerd provide powerful traffic management and observability features, but they add complexity and latency. Start simple with Kubernetes Services and Ingress. Add a service mesh when you have specific needs like mTLS, advanced traffic splitting, or detailed request metrics.
Network Policies
Default-deny network policies are essential security practice. Explicitly allow only the traffic your applications need. This limits lateral movement in case of a breach and makes dependencies explicit.
Storage and Stateful Workloads
Running stateful applications in Kubernetes requires careful consideration. Use StatefulSets for applications that need stable network identities and persistent storage. Choose storage classes wisely—SSD-backed volumes for databases, standard disks for logs and backups.
Backup and Disaster Recovery
Implement automated backups for persistent volumes and etcd snapshots. Test recovery procedures regularly—untested backups are just expensive hopes. Tools like Velero simplify cluster migration and disaster recovery.
Deployment Strategies
Rolling Updates
Configure maxUnavailable and maxSurge carefully. Conservative settings reduce risk but slow deployments. More aggressive settings speed up rollouts but increase load during transitions.
Blue-Green and Canary Deployments
For critical services, implement progressive rollouts. Deploy new versions alongside old ones, gradually shift traffic, and monitor metrics closely. This approach catches issues before they affect all users.
Monitoring and Alerting
Comprehensive monitoring prevents surprises and enables quick incident response.
Critical Metrics to Track
- Node health — CPU, memory, disk usage
- Pod status — Restart counts, pending pods
- API server latency — Control plane performance
- Application metrics — Request rates, error rates, latency
Alert Fatigue Prevention
Alert on symptoms, not causes. Users don't care if a pod restarted—they care if the service is slow or unavailable. Focus alerts on user-impacting issues and use detailed logging for debugging.
Security Best Practices
RBAC Configuration
Implement least-privilege access control. Create specific roles for different teams and services. Avoid using cluster-admin except for break-glass scenarios.
Pod Security Standards
Enforce pod security policies or Pod Security Standards to prevent privileged containers, host namespace access, and other risky configurations. Start with warnings in non-production, then enforce in production.
Image Security
Scan container images for vulnerabilities before deployment. Use minimal base images, run containers as non-root users, and implement image signing to ensure supply chain integrity.
Cost Optimization
Kubernetes can be expensive without proper management. Set resource quotas per namespace, use horizontal pod autoscaling to right-size deployments, and leverage cluster autoscaling to match infrastructure to demand. Regularly review and remove unused resources.
Operational Lessons
Documentation Matters
Maintain runbooks for common operations and incident scenarios. Future you (and your on-call team) will appreciate clear instructions at 3 AM.
Gradual Upgrades
Stay current with Kubernetes versions, but don't jump to the latest release immediately. Test upgrades in non-production environments first and maintain a rollback plan.
Invest in Tooling
Good tooling improves productivity and reduces errors. Tools like kubectl plugins, k9s for cluster navigation, and GitOps platforms for deployment automation pay dividends over time.
Kubernetes is powerful but complex. Success comes from understanding fundamentals, implementing proven patterns, and continuously learning from production experience. Start simple, measure everything, and evolve based on real operational needs rather than theoretical best practices.