Intermediate interview questions in DevOps & Cloud, page 12
OpenTelemetry agent and gateway architecture
Agents run per-node for local collection and host enrichment; gateways are central, horizontally scaled pools for batching, tail sampling, and routing.
Event bus versus message queue for triggers
A queue is point-to-point buffered work for one consumer group; an event bus routes and filters one event to many decoupled subscribers. Event bus wins when many independent services must react.
When to build an Operator vs a Helm chart
Charts handle install-time templating; operators add continuous day-two logic like failover, backups, and scaling for stateful apps.
What is Git LFS and what are its CI/CD trade-offs?
This tests whether you understand Git's object model limits. A strong answer covers pointer indirection, smudge filters, and the shift of download burden to the LFS server in CI. A red flag is claiming LFS eliminates large file transfers entirely.
Key roles in incident response
Incident Commander coordinates and decides but does not fix; Communications Lead handles stakeholders; Operations/SMEs do hands-on diagnosis and remediation.
Design a multi-tenant model serving platform
Share infrastructure to cut cost while enforcing tenant data isolation, fair resource allocation against noisy neighbors, and per-tenant performance via quotas and autoscaling.
What is static analysis in automated builds, with examples?
This tests if you treat static analysis as a pre-runtime quality gate. A strong answer says it shifts feedback left via non-execution scans, citing cyclomatic complexity or unhandled promise rejections.
Breaking tunnel vision during an incident
Call out the assumption, ask for disconfirming evidence, list parallel hypotheses, split responders to investigate them, and anchor on what changed and the data.
Difference between metrics and logs
Metrics are aggregated numeric time series good for trends and alerting; logs are discrete timestamped event records good for detailed root-cause analysis.
What is a build artifact? Give Java, JS, and C++ examples.
Define artifacts as compiled outputs; list JAR/WAR for Java, webpack bundle for JS, and binary/.so for C++; note immutability.
Safeguards for automated remediation runbooks
Add rate limits and circuit breakers on restarts, escalate to humans after N attempts, log all actions, and check for cascading failure before acting.
High availability versus fault tolerance
HA minimizes downtime via redundancy and failover; fault tolerance survives failure with zero interruption.
Design a selective build strategy for a large monorepo
Tests monorepo dependency graph reasoning. Good answers model a DAG, compute reverse deps of the changed library, rebuild only affected targets via Bazel or Nx, and cache remotely. Red flag: directory triggers, full rebuilds, or testing the library alone.
Automating actions on error budget burn
Use multi-window burn-rate alerts; on fast burn, auto-trigger actions like halting deploys, rolling back, or scaling, with escalating tiers.
Blue/green versus canary deployments
Blue/green flips all traffic between two full environments; canary shifts a small slice gradually while watching metrics.
What is an artifact repository and why not just a shared filesystem?
Tests your grasp of immutability, metadata, and access control for build artifacts. A strong answer covers versioning, checksums, RBAC, and API retrieval that NFS lacks. Red flag: saying a shared filesystem is simpler and therefore enough for production.
Managing a risky release with feature flags
Deploy code dark behind an off flag, enable for internal then small percentage, monitor metrics, ramp gradually, then remove the flag.
Diagnosing slow auto-scaled PaaS workloads
Application metrics like request latency, throughput, and DB query time; infrastructure metrics like CPU, memory, and scaling lag.
How would you create and distribute reusable IaC components at scale?
This tests platform engineering governance at scale. A strong answer proposes a versioned module registry, policy-as-code guardrails, automated validation pipelines, and self-service documentation.
Designing a feature flagging service
Control plane (UI, store, targeting), SDKs that cache flags locally for zero-latency evaluation, streaming/CDN delivery for near-real-time updates, and stale-flag lifecycle tooling.
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