Kubernetes Deployment Guide
From cluster provisioning to production monitoring. A practical guide to running reliable Kubernetes workloads on AWS EKS and GCP GKE.
Cluster Architecture
Node Pools
Separate pools for general workloads, memory-intensive (Redis, databases), and GPU-accelerated (ML inference). Use spot/preemptible for batch jobs.
Namespaces
Isolate environments (dev, staging, prod) and services in separate namespaces with resource quotas and network policies.
Ingress
NGINX Ingress Controller with cert-manager for automatic TLS. Use path-based routing for microservices behind a single domain.
Service Mesh
Istio or Linkerd for mTLS between services, traffic splitting for canary deployments, and distributed tracing.
Deployment Strategy
Default strategy. Gradually replace pods with zero downtime. Set maxUnavailable: 0 and maxSurge: 25% for safe rollouts.
Route a small percentage of traffic to new version. Monitor error rates and latency before full promotion.
Run two identical deployments. Switch traffic at the load balancer level for instant rollback capability.
Monitoring Stack
Prometheus + Grafana for cluster and application metrics. Use kube-prometheus-stack Helm chart.
Fluentd/Fluent Bit to aggregate logs into Elasticsearch or CloudWatch. Structured JSON logging from apps.
Jaeger or Tempo for distributed tracing. Instrument apps with OpenTelemetry SDK.
Alertmanager with PagerDuty/Slack integration. Alert on pod restarts, high error rates, and resource pressure.
Need help with Kubernetes? Get in touch for cluster architecture review or deployment support.