Walmart Global Tech Containers & Kubernetes interview questions

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 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.

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.

Three propagation mechanisms live inside this one question and only one of them is automatic. Most candidates promise instant reloads; the kubelet has never promised that to anyone.

Quotas are admission-time contracts counted in requests, not measured usage. That single sentence explains most quota outages, most quota confusion, and the reason LimitRange must sit beside every quota.

Pull auth resolves on the node before any container exists. Candidates who can order the credential chain and read 401 versus 403 versus 429 in events diagnose this in minutes; the rest rotate secrets blind.

Anti-affinity is binary and falls over at scale; topologySpreadConstraints give you numeric skew control across labeled domains. The subtle parts are eligibility filtering before the skew math, and the fact that Kubernetes never rebalances anything for you.

Upgrades look like rolling restarts right up to the morning the CNI stops talking to the new kubelet. The scored answer is ordering, skew policy, and addon sequencing, not courage under pressure.

The classic five-second stall is rarely CoreDNS being slow; it is UDP, conntrack races and ndots expansion. The diagnosis ladder and the NodeLocal DNSCache fix separate operators from readers of architecture blogs.

Three API servers behind one health-checked endpoint, etcd on its own quorum, leader election everywhere else. The scored part is naming what degrades quietly before anything alerts.

Two-phase deletion, a controller that purges content, finalizers holding the door. Stuck CRD instances, dead webhooks and GitOps recreates are the real story; standards prevent the ticket.

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 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.