Deployment in Kubernetes and cluster configuration

I take applications that are difficult to maintain in production and turn them into reliable, scalable services on Kubernetes. I start with containerization: compact multi-stage Docker images, pinned base image versions, fast startup and explicit error messages. Then I package everything into Helm charts so deployment is one predictable command, values are split by environment, and rolling back a failed release takes seconds, not a nervous night.

On the cluster side, I configure ingress with proper TLS, connect horizontal autoscaling based on real load, and set up liveness, readiness, and startup probes so traffic doesn't reach an unready pod. I keep secrets and configuration outside images, set requests and limits for each workload, and all desired state lives in git and is deployed through a GitOps pipeline that automatically brings the cluster to the desired state. I also handle hardening separately: network policies, RBAC, running containers non-root, plus monitoring, logs and alerts so you see problems before your users.

What's included:
— Containerization and optimized multi-stage images
— Helm charts with environment-specific values and safe rollbacks
— Ingress, TLS, autoscaling and health checks
— Secrets, configuration management and GitOps delivery
— Cluster configuration, hardening and monitoring