Your question is Kubernetes Production Pitfalls. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
What are the common pitfalls when working with Kubernetes in a production environment?
Discuss the practical failure modes you would look for when deploying and operating containerized machine-learning or backend services. Cover resource requests and limits, scheduling, autoscaling, networking, storage, security, deployments, observability, configuration, and disaster recovery. Explain how you would detect and mitigate the most important issues. Do not assume a particular cloud provider or business domain.