Kubernetes

Kubernetes turns container deployment into a declarative, self-healing control loop. I define desired state in manifests, and the platform converges to it — scheduling, scaling, and restarting to keep services healthy.

My working level is practical, not academic: Deployments and StatefulSets, Services and Ingress, ConfigMaps and Secrets, resource requests and limits, and liveness/readiness probes. Progress is rollouts with rollbacks; observability comes from the metrics and logs emitted through the standard tooling.

I keep cluster complexity proportionate. For teams that do not need it, a managed runtime or Kamal wins; where Kubernetes earns its keep, I value GKE/AKS managed control planes over hand-run clusters.

The declarative model is the whole point. I write the desired state in manifests and let the control loop converge to it, which means the config is the truth and the cluster self-heals toward it rather than relying on shell scripts and hope.

Workloads map cleanly to primitives. Deployments for stateless services, StatefulSets where persistent identity matters, and the right Service/Ingress wiring for stable routing — choosing the correct primitive is half the battle.

Resource management is how I avoid silent contention. Requests and limits per container, plus liveness/readiness probes, let the scheduler place work honestly and restart unhealthy pods before users notice.

Config and secrets are handled as first-class objects. ConfigMaps and Secrets keep configuration separate from the image, so a config change does not force a rebuild and secrets never bake into the artifact.

Rollouts are controlled by design. Rolling updates with health gating and automatic rollback give me safe progress, and I keep rollback as a first-class operation so a bad release is undone in seconds, not scrambled.

I am honest about when Kubernetes is the wrong tool. For a small estate, a managed runtime or Kamal is simpler. Where it earns its keep — real scale, multiple teams, and mature operability — I run it on a managed control plane to shed the toil of self-hosting.

I write the desired state in manifests and let the control loop converge to it. Config is the truth, and the cluster self-heals toward it rather than relying on scripts and hope.

Workloads map to the right primitive. Deployments for stateless services, StatefulSets where persistent identity matters, and stable Service/Ingress wiring for routing.

Resource requests and limits are set deliberately. The scheduler places work honestly and unhealthy pods restart before users notice, so contention is rare rather than silent.

Config and secrets are first-class objects. ConfigMaps and Secrets keep configuration out of the image, so a config change does not force a rebuild and secrets never bake into the artifact.

Readiness and liveness probes gate reality. A pod only receives traffic when it is actually ready, and restarts are driven by real health rather than guesswork.

Rollouts are controlled by design. Rolling updates with health gating and automatic rollback make forward progress safe and a bad release cheap to undo.

I keep complexity proportionate. Managed control planes (GKE/AKS) shed the toil of self-hosting, and I only run it where scale and threshold of teams genuinely justify it.

Observability rides the standard tooling. Metrics and logs are emitted through the normal path, so the platform stays debuggable as it grows.

When a small estate is better served by a managed runtime or Kamal, I say so. Kubernetes earns its keep at real scale and mature operability — not as a default sticker.