Containerization and Workload Orchestration

Configure and troubleshoot container runtimes — containerd, CRI-O, and gVisor — including CRI integration, runtime classes, OCI spec customization, and performance tuning.

Harden containerized workloads and Kubernetes environments against CVEs, misconfigurations, and runtime threats using security benchmarks and policy tools.

Optimize Dockerfiles and container images for minimal size, faster build times, security hardening, and efficient layer caching in CI/CD pipelines.

Implement GitOps workflows with Argo CD or Flux for declarative, Git-driven Kubernetes application delivery, rollback automation, and multi-environment promotion pipelines.

Author, refactor, and debug Helm charts for Kubernetes application packaging, versioning, values management, and multi-environment deployment strategies.

Design production-grade Kubernetes clusters with best practices for scalability, HA, networking, and node pool configuration across cloud providers.

Architect Kubernetes multi-cluster topologies for high availability, disaster recovery, geo-distribution, and workload federation using KubeFed, Cluster API, or fleet management tools.

Build Kubernetes Operators and custom controllers using Operator SDK, Kubebuilder, or controller-runtime to automate complex stateful application lifecycle management.

Tune Kubernetes resource requests, limits, HPA, VPA, KEDA, and Cluster Autoscaler for cost efficiency, performance stability, and elastic workload scaling.

Design and implement service mesh solutions with Istio, Linkerd, or Cilium for mTLS, traffic management, observability, and zero-trust networking in Kubernetes.