kubernetes-patterns

Kubernetes production deployments require readiness, liveness, and startup probes to improve availability and failover behavior. You can configure these probes alongside pod anti-affinity to ensure reliable workload operations and prevent traffic from routing to unready pods.

Implementing least-privilege RBAC in Kubernetes involves designing role bindings that restrict access to only necessary resources. This approach secures cluster networking and operations by applying production-grade safety guardrails around user and service account permissions.

Choosing Kubernetes autoscaling strategies depends on workload requirements: HPA for CPU/memory metrics, VPA for pod resource adjustments, Cluster Autoscaler for node scaling, and KEDA for event-driven needs. Selecting the appropriate controller ensures reliable scaling behavior.

Setting Kubernetes resource requests and limits establishes safer defaults for workloads by defining CPU and memory boundaries. Combined with namespace quotas and policies, these configurations prevent resource contention and ensure stable production cluster operations.

This Skill supports configuring network policies and ingress to implement secure networking for Kubernetes clusters. It provides production best practices for designing reliable services and ingress controllers that manage traffic routing for both stateless and stateful workloads.

Pod anti-affinity should be used in Kubernetes deployments when you need to improve availability and failover behavior across nodes. It prevents multiple replicas of the same workload from scheduling on the same node, ensuring operational reliability during node failures.