DevOps & Cloud Featured

Automated CI/CD Pipeline to Kubernetes

End-to-end CI/CD pipeline using GitHub Actions to build, test, and deploy containerized applications to Kubernetes with ArgoCD for GitOps.

DevOps Platform Engineer SRE

GitLab CI Kubernetes Helm ArgoCD Docker AWS EKS Trivy Prometheus HPA External Secrets Operator AWS Secrets Manager Istio

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The Problem

Our microservices deployment to Kubernetes was a painful manual process requiring 90+ minutes per release. Engineers had to manually build Docker images, update YAML manifests with new image tags, apply configurations with kubectl, and pray nothing broke. We experienced configuration drift across dev, staging, and production environments, with different resource limits and replica counts causing production incidents. Rollbacks required reverting Git commits and manually applying old manifests, taking 20-30 minutes during critical outages. Secrets were hardcoded in manifests, creating security vulnerabilities. We had zero visibility into deployment health, no progressive rollout strategy, and scaling decisions were purely manual guesswork. The on-call team dreaded deployments, scheduling them only during business hours "just in case."

The Solution

**CI/CD Pipeline Design**: Architected a GitLab CI pipeline with six stages: build (Docker image creation), test (unit + integration tests in isolated containers), security scan (Trivy for vulnerabilities, Hadolint for Dockerfile best practices), deploy-dev (automatic on feature branch), deploy-staging (automatic on main branch), and deploy-production (manual trigger with approval). Configured pipeline caching reducing build times by 50%.

**Kubernetes Deployment Strategy**: Implemented Helm charts for templated configurations with environment-specific values files. Configured rolling updates with readiness/liveness probes ensuring zero-downtime deployments. Set up HorizontalPodAutoscaler (HPA) for automatic scaling based on CPU and custom metrics from Prometheus. Created PodDisruptionBudgets to maintain availability during voluntary disruptions.

**GitOps Workflow**: Integrated ArgoCD for continuous deployment, watching Git repository for manifest changes and automatically syncing to clusters. Configured application health assessment with automatic rollback on failed deployments. Implemented Git-based approval workflow where production deployments require merge to release branch.

**Secrets Management**: Integrated Kubernetes External Secrets Operator pulling secrets from AWS Secrets Manager, eliminating hardcoded credentials. Configured automatic secret rotation every 30 days. Implemented sealed secrets for GitOps-friendly secret management in version control.

Key Highlights

Reduced deployment time from 90 minutes to 6 minutes (93% improvement)
Achieved zero-downtime deployments with automated health checks
Implemented auto-scaling handling 10x traffic spikes (100 to 1000 concurrent users)
Reduced rollback time from 30 minutes to 45 seconds (98% improvement)
Eliminated all hardcoded secrets improving security posture
Increased deployment frequency from 1x/week to 40+ times/week
Configured canary deployments with automatic promotion/rollback
Built multi-environment consistency with 95% configuration shared via Helm
Reduced container image size by 60% with distroless base images
Integrated cost monitoring showing $3K monthly Kubernetes spend optimization
Created deployment dashboards with real-time pod health and resource usage
Passed security audit with zero Kubernetes misconfigurations