Oracle DevOps Engineer interview questions

Two different resources produce the same errno, and the second one is invisible unless you know to look. One command distinguishes them.

A beginner question with a senior follow-up hiding in it. Once you know a hard link is a second name for an inode, log rotation and backup behaviour both stop being mysterious.

The two-syscall duet behind every process on the box. The follow-ups live in what survives the transition, and candidates who skip that fail the next question.

A routine cloud operation with three layers that can quietly disagree. The strong answer is an ordered procedure you could run during business hours, without a reboot.

Enterprise loops pair these topics because they test L2 literacy plus vendor coordination together. The scored insight is that LACP spreads flows, not packets, and needs the switch to agree.

Everyone knows ulimit -n. The interview question is which process inherits which value, why limits.conf did nothing for your service, and how you size the ceiling honestly.

Patching is easy; surviving the rollout is the interview. Staged rings with health gates, what livepatching can and cannot buy you, and the rollback plan you write before starting.

Copy-on-write freezes a point-in-time view while the database keeps writing. Fat snapshots overflow into invalid backups and thin pools exhaust into frozen volumes: size both deliberately.

Transparent versus explicit hugepages is a control question, not a size question. Fork-heavy stores suffer THP copy-on-write amplification while large-resident databases gain TLB reach.

The junior-filter question that still separates candidates who understand the model from those who memorised a definition. The answer is three mechanical differences and one economic one.

The services-and-enterprise interview staple. There is a defensible answer and it is not 'always re-platform': the decision is a function of change tolerance, deadline reality and what the workload is worth.

Four options with genuinely different costs, and the requirement is usually narrower than it first sounds. Establish whether it is about the network path, the data residency, or the provider's retention terms, because those need different answers.

Terraform shapes the world; images define what boots inside it. Bake contents into versioned artifacts on a patch cadence, roll fleets by replacement, and keep user_data for identity and wiring only.

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.

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.

Provisioning is a four-actor handshake between the PV controller, a sidecar, a driver and a backend. Knowing who calls whom turns every stuck PVC from mystery into checklist.

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.

Two cleanup mechanisms hide behind one taint: image garbage collection removes unreferenced images by LRU at threshold crossings, while eviction kills pods. Candidates who conflate them fail this question quietly.

Driver, container toolkit, device plugin, DCGM and discovery must version-match on every node. The operator reconciles that ladder from one ClusterPolicy CR; MIG, upgrades and host kernels are where it bites.

Kubernetes does not see GPUs, it sees an extended resource that something has to advertise. When that advertisement is missing or wrong, the scheduler is behaving correctly and the node is lying.

Rings, SLI gates and Git-expressed promotion: sync waves order resources inside a cluster, but fleet sequencing is an automation you design on top.

An SLA is a price list for failure signed before the failures. Bring the measured distribution, negotiate methodology and exclusions harder than the headline number, and phase targets with dates.

Emergency mode after a storage change is usually one line in fstab. What interviewers score is your order of operations and whether your recovery preserves data-mount dependencies.

This one separates people who read journals from people who restart harder. The exit code and signal systemd already recorded usually name the disease.

The box looks CPU-starved but the CPUs are starving themselves. Reading the reclaim loop correctly separates people who have sat on the console from people who have read about it.

Split-brain writes are a fencing failure first and a data problem second. Freeze writes, read the divergence boundary from replication positions, and let the payment ledger arbitrate reality.

The pods are Pending, the nodes are Ready, and the GPUs have vanished from allocatable. Something changed on the node under a fleet that nobody considered part of the deploy surface.

Experienced answers are ordered and verifiable: minimal base, benchmark applied as code, identity and exposure next, then continuous proof it stayed that way. Checklists recited out of order are the tell.

The default answer is 'horizontal' because interviews reward it. The correct answer names the constraint that makes distribution expensive and knows when one big machine is the engineering choice.

Every candidate lists the three isolation models. The offer-worthy answer prices them per tenant, does the migration fan-out arithmetic, and lands on a hybrid with reversal conditions.

Three sharing modes with three different isolation guarantees. MIG partitions the hardware, MPS shares the SMs, time-slicing just interleaves contexts, and picking wrong turns a latency SLO into a lottery.

GPUs fail gradually before they fail loudly. Xid errors, ECC retirement, thermal throttling and a degraded NVLink all produce a node that is up, schedulable, and slowing every gang it joins.

The driver, the container toolkit, the CUDA runtime inside the image and the framework build all have to agree. Upgrade the wrong one first and every pod on the node fails to start with an error that names none of them.

At sixteen GPUs and above, the network is the computer. Collectives run at the speed of the worst link in the group, and placement decides which link that is.

GPU capacity is not elastic the way CPU is. On-demand means whatever is left after the reservations, and in a tight region that is nothing, so the availability problem and the cost problem are the same problem.

A mixed fleet is the normal state, not a transitional one, because capacity arrives when it arrives. The failure is a scheduler that treats two very different cards as the same countable unit.

Checkpoint too rarely and a failure costs hours of GPU time. Checkpoint too often and you pay for stalled GPUs writing terabytes to storage. There is an arithmetic answer and most teams never do it.

The question that separates people who have debugged a hung rollout from people who have read about one. The interesting half is not the signal, it is PID 1.

A staple of every networking round, and the follow-up is always about TLS termination. Knowing which layer sees what decides most of the answer.

The oldest question in systems interviewing and still the best, because it is unbounded: the interviewer stops you when you run out of depth, and where you stop is the score.

The question that reveals whether someone knows what load average actually counts on Linux. It is not a CPU metric, and that single fact resolves the whole thing.

The classic ephemeral port exhaustion question. Most candidates know the phrase TIME_WAIT; far fewer know which side accumulates it and why the popular fix is dangerous.

The scripting round in disguise. The constraint is the question: it exists to see whether you stream or whether you load, and everything else is about whether the script is safe to run twice.

Everyone recites the four letters. The scoring answer walks each packet across the wire and knows the places the exchange silently dies.

Interviewers use this to sort memorised trivia from people who have chased a slow lookup. Three roles, one bit, and the caching rules most candidates repeat incorrectly.