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Kubernetes can improve deployment safety and resilience, but it also raises the cost of operations. For small projects, the right decision depends less on container count and more on support burden, monitoring maturity, release frequency, and team capacity.
Kubernetes requests and limits are not tuning details. They decide where pods can run, how much capacity the cluster reserves, when workloads throttle, and when containers are killed. Used well, they reduce cost and make scaling predictable. Used poorly, they hide waste and create production-only failures.
Zero-downtime deployment in Kubernetes is not just a rolling update setting. For backend APIs, queues, database migrations, long-running requests, and SIGTERM handling, availability depends on how the application lifecycle and cluster lifecycle cooperate.
Kubernetes monitoring is not about collecting every metric first. It is about knowing which signals expose user impact, resource pressure, failed scheduling, and unsafe autoscaling before the incident spreads.
Graceful shutdown in Go is not just handling SIGTERM. In production, it is a lifecycle contract between your application, Kubernetes, load balancers, background workers, and message brokers.
Most Kubernetes pod failures are not mysterious once you separate symptoms from causes. This guide explains CrashLoopBackOff, OOMKilled, ImagePullBackOff, logs, events, and probes through a practical diagnosis workflow.