Engineering

Top 10 Site Reliability Engineer Interview Questions (2026)

SREs sit at the intersection of software engineering and operations — they own reliability as a product. These 10 questions reveal whether a candidate can design meaningful SLOs, manage incidents with calm authority, and systematically eliminate toil rather than simply firefighting.

Each question includes interviewer guidance on what a strong, average, and weak answer looks like, so your entire hiring panel evaluates candidates on the same standard.

10 targeted questions SLO / incident / toil coverage 3 pro tips Updated April 2026

The 10 Interview Questions

Walk me through how you would define SLIs and SLOs for a new microservice launching in three weeks.

This foundational question tests whether the candidate views reliability as a measurable engineering outcome or a vague aspiration. A good SRE starts with the user journey, not the server.

What to look for Strong candidates begin by identifying user-facing journeys (latency, availability, correctness), then select SLIs that directly measure those journeys. They specify an SLO window (28-day rolling or calendar month), articulate why 99.9% vs 99.5% depends on business context, and proactively mention error-budget burn rates. Weak candidates describe vague metrics like "CPU usage" or "uptime" without connecting them to user experience.

Your error budget for a critical API burned through 40% in 48 hours. What do you do?

Error budgets only work if teams act on them. This question tests whether the candidate treats budget burn as a real signal that triggers an operational response or treats it as an abstract number to report.

What to look for Look for a structured response: immediate investigation of what drove the burn (deployment, traffic pattern, dependency failure), discussion with the product team about whether to halt feature releases, a postmortem trigger, and a concrete remediation plan. Strong candidates also mention adjusting burn-rate alert thresholds. Weak candidates immediately talk about lowering the SLO target rather than fixing the underlying issue.

Describe a major incident you owned from detection to resolution. What would you do differently?

Incident command is a core SRE competency. This behavioral question surfaces real experience with the chaos of production outages and the candidate's ability to maintain structured thinking under pressure.

What to look for Strong candidates describe clear role separation (IC, comms lead, scribe), structured runbooks or decision trees, frequent stakeholder updates at defined intervals, and a mitigation-first approach before root-cause deep dives. The retrospective portion should reflect genuine blameless post-mortem culture — finding systemic gaps, not blaming individuals. Red flags: "I solved it alone" narratives or post-mortems that blamed human error without systemic fixes.

How do you identify and systematically eliminate toil in your team?

The Google SRE book recommends keeping toil below 50% of an SRE's time. This question tests whether the candidate actively tracks, prioritizes, and automates repetitive operational work rather than normalizing it.

What to look for Look for a systematic approach: tracking toil in a backlog with estimated hours saved, categorizing by frequency and impact, then automating or eliminating rather than optimizing. Strong candidates describe specific examples — automated ticket routing, self-healing runbooks, or eliminating manual deployment steps. Weak candidates describe individual automation projects without a broader toil-reduction program or without measuring the time saved.

How do you conduct a post-mortem that actually prevents recurrence rather than just documenting what happened?

Post-mortems are only valuable when they produce lasting systemic changes. This question evaluates whether the candidate runs post-mortems as learning rituals or as compliance exercises.

What to look for Strong candidates describe a blameless facilitator model, structured timelines with contributing factors (not just "root cause"), and action items with owners and due dates tied to SLO improvement. They track action-item completion rate as a team health metric and schedule follow-up reviews. Look for mention of sharing post-mortems across teams to build institutional knowledge. Weak candidates describe post-mortems as internal reports that get filed and forgotten.

You notice p99 latency on a database-backed service doubled overnight without a deployment. How do you diagnose this?

This technical scenario tests structured debugging skills, observability fluency, and systems-level thinking — the daily craft of a working SRE.

What to look for A methodical approach: confirm the signal is real (rule out instrumentation drift), check for traffic volume or shape changes, examine database slow-query logs, check for lock contention or table bloat, look at connection pool saturation, and correlate with any upstream dependency changes. Strong candidates mention USE/RED methodology, trace sampling, and specific tools (Datadog, Grafana, pg_stat_statements). Weak candidates jump straight to "restart the database" without diagnosing first.

What does your production readiness review checklist include, and how do you enforce it?

PRRs are how SREs shift reliability left. This question reveals whether the candidate collaborates with development teams before launch rather than only responding to production failures.

What to look for Look for comprehensive checklists covering: defined SLOs with error budgets, runbook for top 3 failure modes, load test results, graceful degradation behavior, alerting thresholds tuned to SLO, on-call rotation assigned, rollback plan documented, and dependency blast-radius analyzed. Strong candidates describe PRRs as collaborative conversations, not gatekeeping audits. They mention adapting the checklist by service criticality and involving developers in authoring runbooks.

How have you used chaos engineering to validate system resilience, and what did you learn?

Chaos engineering separates teams that verify resilience from those that merely hope for it. This question tests whether the candidate runs controlled experiments or avoids chaos out of fear.

What to look for Strong candidates describe a hypothesis-driven approach: define the steady state, form a hypothesis about what should survive, inject failure in a controlled scope (starting with staging), and measure deviation from steady state. They should cite specific failure modes tested (dependency outage, latency injection, node failure) and concrete improvements made afterward. Look for evidence they stopped a chaos experiment that went wrong. Weak candidates conflate chaos engineering with random outages or describe it as "too risky to try."

How do you design an on-call rotation that is sustainable and doesn't burn out your team?

On-call sustainability is a retention issue. This question tests whether the candidate understands the human side of reliability engineering and can build a system that people won't quit to escape.

What to look for Look for: defined response time SLAs by severity tier, rotation size (minimum 4–6 engineers for weekly shifts), alert volume targets (no more than 2 actionable pages per shift on average), comp time or reduced load after heavy on-call weeks, shadow rotations for new members, and systematic alert fatigue reduction. Strong candidates treat high alert volume as a bug to fix, not a normal condition. They distinguish between reactive paging and proactive capacity alerts.

How do you balance the 50% operational / 50% engineering split that Google's SRE model recommends?

Without an intentional split, SRE teams drift into pure ops work. This question tests whether the candidate has thought about workload governance and has tools to enforce it.

What to look for Strong candidates describe tracking operational work time (pages, tickets, manual deployments) with actual measurements rather than estimates, using that data in team planning to carve out engineering time, and escalating to engineering leadership when the balance tilts too far. They understand that the split is a constraint that drives automation investment, not just a nice-to-have. Weak candidates describe the 50/50 as aspirational without any mechanism to enforce it.

3 Pro Tips for Hiring SREs

Lessons from teams that have built high-performing SRE functions.

Test both engineering depth and operational breadth

SRE sits between software engineering and operations — candidates who only shine in one domain will struggle with the other. Include both a systems debugging exercise and a coding/automation task in your process.

Use a real incident as your scenario interview

Sanitize and share an actual outage your team experienced. Ask the candidate to walk through how they would investigate it step by step. This reveals how they think under realistic ambiguity far better than contrived puzzles.

Assess developer relationship skills explicitly

SREs who antagonize development teams create silos. Ask specifically how candidates have pushed back on releases, enforced PRR criteria, or negotiated SLO targets with product teams. Look for collaborative assertiveness, not gatekeeping.

Frequently Asked Questions

How many interview rounds should an SRE hiring process include?

Most teams use 4–5 rounds: a recruiter screen, a systems fundamentals interview, a practical debugging or on-call simulation, a cross-functional collaboration round, and a hiring-manager values fit conversation. Include at least one live troubleshooting exercise.

What technical skills are non-negotiable for SRE candidates?

SLO/SLI design and error-budget policy, Linux internals and networking fundamentals, infrastructure-as-code (Terraform or equivalent), distributed systems concepts (CAP theorem, consensus), and proficiency in at least one systems language (Go or Python). Observability tooling fluency is also critical.

How do you assess an SRE candidate's incident management skills?

Present a realistic outage scenario and ask them to walk through detection, triage, communication, mitigation, and post-mortem. Look for structured thinking under pressure, clear stakeholder communication habits, and a blameless post-mortem mindset.

What differentiates a great SRE from a good sysadmin?

Great SREs treat reliability as a software engineering problem. They automate toil systematically, design SLOs that reflect user experience, partner with development teams to shift reliability left, and use error budgets to make data-driven release decisions rather than defaulting to change freezes.

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