Accenture Containers & Kubernetes interview questions

Both solve the same surface problem and they disagree about how. The answer that scores names what each one makes hard, and notices that the GitOps tool you use changes the calculus.

Default-deny egress breaks name resolution before it breaks anything else, and every connection times out confusingly. The practitioners are the ones who test with positive AND negative probes and know their CNI's fine print.

Pod-level SIGTERM handling and node-level shutdown coordination are different mechanisms, and conflating them is the trap. The kubelet can only drain pods on power-off if it participates in systemd's shutdown sequence.

Tenancy is a dial from policy-based soft isolation to hard cluster boundaries with a virtual-control-plane middle ground. The scored answer picks by blast radius requirements and names what each model still leaves shared.

Exit codes, the previous-container log, and a little-known file at /dev/termination-log that carries a container's last words into kubectl output. Scale triage starts with classification, not with opening pods.

Kind precedence orders manifests, hooks jump the queue with their own weights and delete policies, and --atomic plus --wait turn hope into rollback. Split charts along blast radius, not folder aesthetics.

The single most common Kubernetes interview question, and the one where a vague answer is most obvious. Every stage you name is a place the interviewer can ask you to debug.

Asked in nearly every senior Kubernetes loop, and most candidates answer with a feature list. The scoring answer names the three problems it solves and then argues for not adopting it.

Both run pods, so the answer sounds obvious until an interviewer asks what happens when you delete one. The guarantees are narrower and more specific than most candidates think.

Everyone can recite the three. The scoring answer is what each failure causes, and why a badly configured liveness probe is more dangerous than none at all.

The pair everyone configures and few can explain. QoS hints at eviction risk, but usage versus requests and Pod priority determine node-pressure ranking, and CPU and memory behave completely differently when you exceed them.

The question that finds out whether you know Kubernetes networking or just use it. The model has three rules and everything about CNI follows from them.

Almost always a finalizer, and the fast fix is the one that loses data. The safe answer explains what the finalizer is protecting against before removing it.

A practical question with a precise answer, and the size is not the real cost. Pull time on every node, registry storage, and attack surface all scale with it.

The scheduler is behaving correctly, which is the part that confuses people. It optimises placement at admission time and never revisits, so a cluster drifts out of balance by design.

Cilium became the default CNI on major managed platforms for a reason that is mechanical rather than fashionable. The iptables datapath degrades with service count, and eBPF replaces a linear scan with a map lookup.

A specific configuration trap with a clean explanation. Both controllers act on the same signal from opposite directions, and the result oscillates.

PDB governs voluntary disruptions only and does not gate rolling updates at all. Candidates who say 'it keeps N pods alive' have just described the part it does not do.

The senior tells are level-triggered reconciliation and finalizer semantics. The partition question separates people who have written a controller from people who have installed one.

The friendliest DaemonSet question there is, and it still separates people who have operated one from people who have read about one. The scheduling rules hide the traps.

Init containers are the easy half. The hard half is why plain sidecars race your app at both ends of the pod's life, and what restartPolicy Always changes about that.