Scheduling, probes, workloads and the failure modes that come with them.
6 items · all topics
Explain the architectural difference between AWS ECS Fargate and Amazon EKS (Elastic Kubernetes Service).
ECS and EKS are both orchestrators. Fargate isn't: it's a compute mode that either one can run on, so all four combinations exist. The real comparison is ECS vs EKS on who operates what, and Fargate vs EC2 on whether you want to own nodes at all.
A pod is stuck in Pending for 10 minutes in production. Walk me through how you diagnose it.
Pending means the scheduler hasn't placed the pod on a node. The cause is almost always resources, node selection constraints, or an unbound volume, and `kubectl describe pod` tells you which within seconds if you read the Events section rather than guessing.
What happens if an Auto Scaling instance never becomes healthy?
Auto Scaling terminates and replaces an instance that never passes health checks, which is fine once and expensive in a loop. How long you burn depends on the grace period, the check thresholds, and which health check type the group is actually using. The fix is working out why it's unhealthy: usually startup config, a wrong health endpoint, or a grace period shorter than boot time.
You use GitOps and someone changes Kubernetes manually. Git still has the old config. What happens?
You get configuration drift: Git says one thing, the cluster says another. What happens next depends on whether the controller self-heals or just reports it. Either way the manual change is temporary, and the fix is to put the intended change into Git, not to argue with the controller.
Argo CD keeps reverting your emergency production change. Why, and what should you do?
Self-heal is doing exactly what it was configured to do: pulling the cluster back to what Git says. During an incident, mitigate through something the controller doesn't manage, then get the real change into Git fast rather than fighting reconciliation head on.
Git is the source of truth, but production differs from Git. How do you prove where the drift happened?
Compare state at each stage, Git, rendered manifests, what was applied, and the live cluster, and use Kubernetes' own metadata to name the culprit. managedFields records which controller last wrote each field, which usually answers the question outright without any guessing.