Intermediate everything in DevOps & Cloud, page 2
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.
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.
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.
First-SRE 90-day plan at a startup
Listen and measure first, pick one high-impact service, define SLIs/SLOs and basic alerting, then show reduced toil or incidents to leadership.
Designing shallow vs deep health checks
Shallow checks confirm the process is alive; deep checks verify dependencies; use shallow for liveness/load-balancer routing and deep sparingly to avoid…
Rolling update vs blue-green deployment
Rolling replaces instances gradually with minimal extra capacity but mixes versions; blue-green runs two full environments for instant switch and rollback at double the cost.
Writing high-quality postmortem action items
Good action items are specific, assigned to an owner, prioritized, tracked to completion, and ideally prevent recurrence rather than just detect faster.
Calculating downtime for a 99.9% SLO
0.1% of 30 days is roughly 43 minutes of allowed downtime; healthy budget enables faster shipping while depletion slows or freezes deploys.
Keeping a postmortem blameless after an admission
Acknowledge the courage, redirect from who to why the system allowed it, ask what guardrails were missing.
Conducting a Production Readiness Review
Assess monitoring and alerting, capacity and load testing, failure modes and dependencies, on-call and runbooks, and rollback or release safety.
Embedded vs consulting SRE engagement models
Embedded SREs sit inside one team for deep impact but limited reach; consulting SREs advise many teams broadly but shallowly.
A team keeps blowing its error budget. First steps?
Analyze where the budget is burning via SLIs and postmortems, validate the SLO and SLIs are sound, then partner blamelessly on the top fixes.
Automating chaos in CI/CD for continuous verification?
Run codified experiments against staging or canary with pass/fail on steady-state SLIs; prerequisites are observability, automated abort, and isolation.
Resource faults versus network faults: when each matters?
Resource faults probe local saturation and autoscaling; network faults probe distributed-call resilience like timeouts and retries.
Why does 200ms latency drop requests? Diagnose it.
Little's Law shows added latency raises in-flight requests, exhausting the thread or connection pool; check pool saturation, timeouts, and retries.
How do you run your first production chaos experiment?
Pick a low-risk known weakness, define a measurable hypothesis, brief stakeholders and on-call, run small with an abort, then analyze and fix.
Zero-downtime index migration on a hot table?
Build the index concurrently to avoid table locks, run off-peak with monitoring, and keep it reversible since dropping an index is cheap.
Mitigating risk from an unproven external dependency?
Timeouts and circuit breakers to fail fast, bulkheads to isolate resources, fallbacks or cached/degraded responses.
Reliability patterns for queue-based job processing?
Retries with backoff and jitter for transient faults, dead-letter queues plus a poison-message limit, idempotent handlers and visibility timeouts.
Front-end performance budgets
A performance budget is an enforced limit on metrics like Core Web Vitals and bundle size, checked in CI to fail builds that regress.
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