Technology

Kubernetes

Container orchestration: autoscaling, self-healing, smooth deployments and configuration management.

About the technology

I have used Kubernetes for five years to orchestrate containerized applications in production where fault tolerance, scalability and predictable releases matter. The platform takes on what previously required manual labor: distributing containers across nodes, restarting failed processes, load balancing and scaling to traffic. I describe infrastructure declaratively as manifests and understand the key abstractions: the Pod as the minimal unit of execution, Deployment for managing replicas and smooth updates, StatefulSet for stateful workloads, DaemonSet, Service for network access and Ingress for routing external traffic. I move configuration and secrets into ConfigMap and Secret, separating them from images. I pay special attention to application health: I configure liveness, readiness and startup probes so that traffic goes only to ready pods and stuck ones are restarted. I correctly set CPU and memory requests and limits, which is critical for scheduling and cluster stability, and design applications for graceful shutdown with SIGTERM handling. For scaling I use the Horizontal Pod Autoscaler based on load metrics, and the node autoscaler for the whole cluster. I roll out releases with rolling-update strategies, and when needed canary and blue-green, to reduce risk and roll back quickly. I organize application management through Helm charts and the GitOps approach, where the cluster state is stored in Git and applied automatically, which ensures reproducibility and an audit trail of changes. I build observability on Prometheus and Grafana for metrics, centralized log collection and distributed tracing to quickly find the causes of incidents. I solve network-security questions through NetworkPolicy, RBAC permission separation and namespace isolation. I understand the operational subtleties well: pod eviction, PodDisruptionBudget availability budgets, affinity and anti-affinity for load distribution, and working with persistent volumes. Kubernetes in my projects is not a trendy tool for its own sake but a way to give the system self-healing, elasticity and safe releases without downtime under real user load.

Experience

5 years in production

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