Kubernetes deployments & cluster hardening

I take applications that are hard to run in production and turn them into reliable, scalable services on Kubernetes. I start with containerization: clean, small multi-stage Docker images, pinned base versions, and apps that start fast and fail loudly when something is wrong. Then I package everything into Helm charts, so a deploy is one predictable command, values are separated per environment, and rolling back a bad release takes seconds instead of a panicked night.

On the cluster side I set up ingress with proper TLS, configure horizontal autoscaling on real load, and wire liveness, readiness and startup probes so traffic never reaches a pod that is not ready. Secrets and config stay out of the images, resource requests and limits go on every workload, and the whole desired state lives in git and rolls out through a GitOps pipeline that reconciles itself automatically. I also do the hardening that keeps you safe: network policies, RBAC, non-root containers, plus monitoring, logs and alerts so you see problems before your users do.

What you get:
— Dockerized apps and optimized multi-stage images
— Helm charts with per-environment values and safe rollbacks
— Ingress, TLS, autoscaling and health checks
— Secrets, config management and GitOps delivery
— Cluster setup, hardening and monitoring