Airbnb Site Reliability Engineer Interview Preparation Guide (Mid-Level)
Airbnb's Site Reliability Engineer interview process for mid-level candidates consists of a structured evaluation across technical fundamentals, system design thinking, infrastructure expertise, and cultural alignment. The process includes an initial recruiter screen, a technical phone screen focusing on algorithmic problem-solving, and an on-site loop with four rounds covering coding, system design/infrastructure, operations/automation, and behavioral assessment. Each round emphasizes both technical excellence and Airbnb's collaborative culture. The entire process typically spans 4-6 weeks from initial contact to offer decision.
Interview Rounds
Recruiter Screening
What to Expect
Your initial conversation with an Airbnb recruiter (15-20 minutes) is an informal screening to assess your background, motivation, and cultural fit. The recruiter will explore your years of SRE experience, relevant technical background, and familiarity with Airbnb's platform and scale. They evaluate your communication clarity, enthusiasm for the role, and whether your career goals align with the position. This stage also confirms you understand SRE fundamentals and establishes whether you're ready for technical evaluation rounds.[1]
Tips & Advice
Research Airbnb's engineering blog and technical challenges before the call. Prepare a focused 30-second pitch about why you're specifically excited about SRE at Airbnb—reference concrete things you know about their platform (scale, multi-region deployment, incident response culture, etc.). Have 2-3 specific achievements ready: a monitoring system you built, an incident you led response on, or a major automation project that reduced toil. Show genuine understanding of what SRE means—not just 'keeping systems up' but balancing reliability with development velocity through observability, automation, and process. Ask informed questions about the team's on-call rotation, incident response processes, or infrastructure challenges. Be authentic and conversational rather than scripted.
Focus Topics
Cross-Team Collaboration and Communication
Demonstrate clear, thoughtful communication during the call. Give specific examples of collaborating with developers on reliability concerns, explaining SRE concepts to product teams, or coordinating incident response across groups. Show how you balance SRE's perspective with engineering team needs.
Practice Interview
Study Questions
Technical Skills and Tooling Experience
Provide specific overview of technical competencies: programming languages (Python, Go, Java, etc.), infrastructure platforms (Kubernetes, AWS, GCP), monitoring tools (Prometheus, DataDog, New Relic, etc.), configuration management (Terraform, Ansible), and incident response platforms you've used. Be honest about depth—distinguish between 'used in production' and 'familiar with.'
Practice Interview
Study Questions
SRE Background and Hands-On Experience
Clearly articulate your SRE journey: years of experience, specific responsibilities, key projects, and progression from junior to mid-level. Highlight hands-on work with monitoring platforms, incident response, infrastructure automation, and reliability engineering. For mid-level, demonstrate evolution in scope—perhaps you started responding to incidents and progressed to designing systems to prevent them.
Practice Interview
Study Questions
Motivation for SRE at Airbnb
Articulate why SRE specifically (not just engineering), why Airbnb specifically (not just any tech company), and how the role aligns with your career development. Reference Airbnb's scale, technical challenges, or cultural aspects that genuinely appeal to you. Avoid generic responses.
Practice Interview
Study Questions
Technical Phone Screen
What to Expect
In this 60-90 minute coding screen, you'll solve 1-2 algorithmic problems using a shared coding platform (typically HackerRank or similar). Problems focus on data structures (arrays, linked lists, trees, graphs, hash maps) and algorithms (searching, sorting, BFS/DFS, dynamic programming), typically at medium difficulty. You're evaluated on problem-solving approach, code quality, optimization thinking, and communication throughout the process.[1]
Tips & Advice
Spend 30-45 minutes on each problem. For mid-level, interviewers expect thoughtful, optimized solutions—not brute force. Start by clarifying requirements and constraints, discuss your approach before coding (think out loud about trade-offs), write clean code with meaningful variable names, handle edge cases explicitly, and test with examples. Focus on optimization naturally—explain your complexity analysis and why you chose that approach. If stuck, communicate your thinking rather than staying silent. Ask clarifying questions when problem statements are ambiguous. Practice on LeetCode medium problems to build speed and pattern recognition. For mid-level, time management matters—solve efficiently within the window without perfection.
Focus Topics
Dynamic Programming and Optimization
Understand recursive problem-solving, memoization, and dynamic programming approaches. Practice classic DP problems: fibonacci variants, coin change, longest subsequences, knapsack, and path counting. Learn to identify DP problems and convert recursive solutions to iterative with space optimization.
Practice Interview
Study Questions
Hash Tables and Frequency-Based Problems
Master hash table design and applications. Understand collision handling, load factors, and custom hash functions. Practice problems using hash maps for optimization: finding duplicates, frequency counting, substring problems, two-sum variants, and anagram detection.
Practice Interview
Study Questions
Problem-Solving Communication and Complexity Analysis
Master the interview process: clarify requirements explicitly, discuss approach and trade-offs before coding, explain algorithmic choices clearly, analyze time and space complexity of your solution, identify edge cases, and test thoroughly. Communicate throughout rather than working silently.
Practice Interview
Study Questions
Trees and Graphs Algorithms
Understand tree traversals (inorder, preorder, postorder, level-order), binary search trees, balanced tree concepts, and graph algorithms (BFS, DFS, shortest path algorithms, topological sort, cycle detection). Practice problems involving tree construction, LCA (lowest common ancestor), path finding, and graph connectivity.
Practice Interview
Study Questions
Arrays and Strings Manipulation
Master problems involving array searching, sorting, manipulation, and string operations. Includes techniques like two-pointer methods, sliding windows, prefix sums, binary search, and string transformations. Practice problems like finding duplicates, merging intervals, rotating arrays, pattern matching, and dynamic array resizing.
Practice Interview
Study Questions
On-Site Coding Round
What to Expect
During your on-site (or virtual) visit, you'll have a 45-60 minute coding interview with a dedicated engineering interviewer. You'll solve 1-2 algorithmic problems at medium-to-hard difficulty, typically more challenging than the phone screen. You're evaluated on problem-solving depth, code quality, optimization thinking, and your ability to discuss and defend your approach. The interviewer also assesses your debugging skills and how you handle unexpected questions or edge cases.[1]
Tips & Advice
Write clean, production-ready code from the start—treat it as if it will be code-reviewed. Use meaningful variable names, add comments for complex logic, and structure code logically. Optimize your solution naturally rather than writing brute force first, then optimizing. For mid-level, interviewers expect efficiency-conscious thinking upfront. Include proper error handling and input validation. Verify your solution works with multiple test cases including edge cases. Be prepared for follow-up questions like 'How would you handle X constraint?' or 'Can you optimize further?' Stay engaged with the interviewer—if you get stuck, think out loud and ask for hints rather than going silent. Show curiosity about why the problem matters or how it relates to real systems.
Focus Topics
Edge Cases and Comprehensive Testing
Systematically identify edge cases: empty inputs, single elements, maximum sizes, negative numbers, duplicates, null values, and boundary conditions. Handle these cases explicitly in your code. Walk through your solution with diverse test cases before declaring completion.
Practice Interview
Study Questions
Production Code Quality and Maintainability
Write code that is clean, well-structured, and easy to understand. Use clear naming conventions, organize code logically, include helpful comments for non-obvious logic, and maintain consistent style. Include appropriate error handling, input validation, and null checks. For mid-level, code quality is a significant evaluation dimension—as important as correctness.
Practice Interview
Study Questions
Optimization and Complexity Trade-offs
Analyze time and space complexity of your solution. Understand trade-offs between different approaches (speed vs. memory, simplicity vs. optimization). For mid-level, explain why your chosen approach is appropriate for the constraints. Discuss optimization naturally without prompting—show efficiency-conscious thinking.
Practice Interview
Study Questions
Medium to Hard Coding Problem Patterns
Master coding patterns appearing in harder problems: multi-step algorithms, complex graph problems, advanced tree operations, sophisticated DP solutions, and problems requiring multiple data structures. Practice problems that require combining multiple techniques or non-obvious approaches.
Practice Interview
Study Questions
System Design and Infrastructure Architecture Round
What to Expect
In this 45-60 minute round, you'll design a system or infrastructure architecture for reliability at scale. Unlike SWE system design (which focuses on service architecture), SRE system design emphasizes monitoring architecture, incident response systems, observability infrastructure, deployment pipelines, or scaling strategies. You might be asked 'Design a monitoring system for Airbnb's booking service,' 'How would you architect incident detection and response,' or 'Design a canary deployment system.' For mid-level, expect scenarios focused on single services or small infrastructure domains at medium scale, not enterprise-wide systems.[1]
Tips & Advice
Start by clarifying requirements: scale, availability targets, failure modes, and constraints (cost, latency, etc.). For mid-level, spend time understanding the problem deeply before designing. Discuss trade-offs openly—reliability vs. complexity, automation vs. manual intervention, cost vs. availability. Include monitoring, alerting, and observability in your design from the start, not as an afterthought. Draw diagrams communicating your architecture clearly. Use specific technologies you know (Prometheus, Kubernetes, Terraform, etc.) rather than vague 'load balancers.' Discuss failure scenarios: 'What happens if the monitoring system fails?' or 'How do we detect this failure?' Include human factors: runbooks, escalation procedures, on-call rotation considerations. Be prepared to discuss scalability: 'What happens at 10x traffic?' Mention SLO/SLA concepts and error budgets in your design thinking.
Focus Topics
Infrastructure Scalability and Capacity Management
Design systems that scale with demand. Discuss horizontal vs. vertical scaling trade-offs, auto-scaling policies, database scaling strategies (sharding, read replicas), caching layers, and burst capacity handling. Plan for growth through capacity forecasting, trend monitoring, and proactive provisioning.
Practice Interview
Study Questions
Distributed Systems Trade-offs and Data Consistency
Understand CAP theorem, consistency models (strong vs. eventual), partition tolerance, and availability-consistency trade-offs. Design systems making intentional choices about these trade-offs based on requirements. Discuss replication strategies and their consistency implications.
Practice Interview
Study Questions
High Availability and Fault Tolerance Architecture
Design systems for high availability through redundancy, geographic distribution, and failover mechanisms. Understand load balancing strategies, replication patterns, multi-region deployment, and graceful degradation under failure. Identify and eliminate single points of failure. For mid-level, focus on practical, implementable reliability patterns.
Practice Interview
Study Questions
Incident Detection, Response, and Recovery Processes
Design end-to-end incident response: automated detection systems, alert routing and escalation, incident command procedures, runbooks, triage processes, mitigation strategies, recovery procedures, and communication protocols. Include post-incident review mechanisms. Design for human factors—how teams coordinate during stress.
Practice Interview
Study Questions
Monitoring, Observability, and Alerting Architecture
Design comprehensive monitoring and observability systems: metrics collection, log aggregation, distributed tracing, and dashboards. Plan alerting strategies minimizing false positives while catching real issues. Include thresholds, escalation policies, and notification routing. Understand the three pillars of observability: metrics, logs, and traces. For mid-level, design specific to problem constraints.
Practice Interview
Study Questions
Infrastructure, Automation, and Operations Round
What to Expect
This 45-60 minute round focuses on practical SRE operations: infrastructure-as-code, automation strategies, deployment safety, SLO/SLA/error budget management, and operational excellence. You might discuss your approach to infrastructure automation, design a deployment pipeline, explain how you'd define SLOs for a service, or describe your strategy for reducing operational toil. This round evaluates hands-on experience with real operational challenges and your philosophy around automation and reliability.[1][4]
Tips & Advice
Use concrete examples from your previous work: an infrastructure automation project, a deployment system you built, or an incident response process you improved. Be specific about tools and frameworks (Terraform, Ansible, Kubernetes, etc.) you've actually used in production. Discuss SLO definition thoughtfully—explain how you'd determine appropriate targets based on business requirements and cost-reliability trade-offs. Show understanding of error budgets and how to use them to balance reliability with feature velocity. Be prepared for scenarios like 'Tell me about a time you had to choose between automation investment and manual toil' or 'How would you handle a service with unreliable dependency?' Show thoughtfulness about automation—discuss when it's worth investing in automation vs. accepting manual processes. Mention your post-incident review philosophy and how you prevent recurring failures.[2][4]
Focus Topics
Performance Optimization and Capacity Planning
Discuss systematic approaches to performance optimization: profiling, bottleneck identification, database optimization techniques, caching strategies, and load testing. Include capacity planning methodology: monitoring capacity trends, forecasting growth, and proactively provisioning resources. Understand relationships between performance, reliability, and operational cost.
Practice Interview
Study Questions
Deployment Strategies and Release Safety
Discuss deployment strategies (blue-green deployments, canary releases, rolling deployments, feature flags) and when to use each. Understand how to minimize deployment risk through staged rollouts, monitoring during deployment, and quick rollback capabilities. Include CI/CD pipeline design and automated testing requirements before production.
Practice Interview
Study Questions
Automation, Toil Reduction, and Engineering Philosophy
Understand the distinction between toil (repetitive manual work) and engineering work. Discuss strategies for identifying, quantifying, and automating toil. Include specific examples: deployment automation, incident response automation, backup processes, configuration management, log management. Know when automation ROI makes sense vs. when manual processes are acceptable.
Practice Interview
Study Questions
Infrastructure as Code (IaC) and Infrastructure Automation
Master infrastructure-as-code tools (Terraform, CloudFormation, Ansible, etc.) you've used in production. Understand version control for infrastructure changes, automated testing of infrastructure changes, reproducible deployments, and disaster recovery through IaC. Discuss benefits (consistency, auditability, speed) and challenges (state management, complexity, testing strategies).
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Study Questions
SLO, SLA, and Error Budget Management
Understand SLO definition (how to set appropriate targets based on business requirements), SLA implications, error budget concepts, and how to use error budgets to balance feature velocity with reliability investments. Discuss trade-offs: tighter SLOs require more investment but provide better reliability. Show how you'd communicate error budget status to product teams.
Practice Interview
Study Questions
Behavioral and Values Alignment Round
What to Expect
In this 45-60 minute round, an interviewer explores your past experiences, how you handle challenges, your collaboration style, and alignment with Airbnb's values. You'll answer questions like 'Tell me about a significant incident you responded to,' 'Describe a difficult technical trade-off you made,' 'How do you work with engineers who disagree with reliability trade-offs,' and 'What does Airbnb's mission mean to you.' For mid-level SREs, interviewers evaluate your maturity in handling complex situations, your ability to mentor junior colleagues, sound judgment in reliability decisions, and authentic connection to Airbnb's culture.[1]
Tips & Advice
Prepare 4-5 detailed stories using the STAR method (Situation, Task, Action, Result), showcasing: managing a major incident, mentoring a junior engineer, making a difficult reliability-velocity trade-off, resolving a disagreement with colleagues, and improving system reliability significantly. Show emotional maturity and genuine learning from failures—avoid blaming others. Demonstrate how you balance SRE's reliability mission with business needs and developer productivity. Connect experiences to Airbnb's values: belonging (inclusive incident response, blameless post-mortems), community (cross-team collaboration), trust (reliability focus), and bias toward action (fast incident response, automation). Ask thoughtful questions revealing interest in Airbnb's SRE culture specifically. Be authentic and specific rather than generic. For mid-level, show evidence of growth from junior to mid-level, mentorship capabilities, and mature judgment in complex situations.
Focus Topics
Airbnb Values and Mission Alignment
Connect your experiences to Airbnb's core values: belonging (inclusive, collaborative teams), community (supporting each other), trust (reliability focus), and bias toward action (rapid incident response, automation drive). Discuss what 'belong anywhere' means to you in the context of SRE work. Show genuine understanding of Airbnb's business and how your SRE work enables their mission.
Practice Interview
Study Questions
Learning from Failures and Continuous Improvement
Discuss a time you made a mistake or when a system you built had significant issues. Show how you handled it professionally, what you learned, and how you prevented similar issues. Include your approach to post-incident reviews: blameless culture, psychological safety, actionable improvements. Show curiosity about root causes rather than surface symptoms.
Practice Interview
Study Questions
Technical Trade-off Decision Making
Share a story about making a difficult trade-off: reliability vs. feature velocity, automation investment vs. accepting toil, manual safety vs. deployment speed, or cost vs. availability. Explain your decision-making process, how you involved stakeholders and engineers, how you communicated the decision, and the outcome. Show mature judgment balancing competing priorities.
Practice Interview
Study Questions
Major Incident Response and Crisis Leadership
Prepare a detailed incident story: what happened, how you responded, your specific actions during the incident (communication, prioritization, decision-making), how you managed stress and helped others, what you learned, and improvements implemented. For mid-level, show leadership during incidents—perhaps coordinating across teams, mentoring someone responding to their first incident, or making critical decisions under time pressure.
Practice Interview
Study Questions
Cross-Functional Collaboration and Influence
Share examples of working effectively with developers, product managers, other SREs, or leadership. Discuss how you built trust, communicated technical concepts to non-technical stakeholders, influenced decisions, resolved disagreements constructively, and fostered collaboration. Show examples of mentoring junior colleagues or leading technical discussions.
Practice Interview
Study Questions
Frequently Asked Site Reliability Engineer (SRE) Interview Questions
Sample Answer
Sample Answer
Sample Answer
kubectl exec -it svc/db-admin -- pg_isready -h primary.db.cluster
# or run cloud provider console checkssh db-primary "uptime; df -h /var/lib/postgresql; journalctl -u postgresql -n 200 --no-pager | tail -n 50"psql -h replica1 -c "SELECT now()-pg_last_xact_replay_timestamp() AS lag;"ssh db-primary "sudo systemctl start postgresql"# use orchestrator/tooling:
orchestrator -c failover --candidate replica1 --forcepsql -h new-primary -c "CREATE TEMP TABLE t(id int); INSERT INTO t VALUES(1); SELECT * FROM t;"Sample Answer
Sample Answer
Sample Answer
Sample Answer
Sample Answer
#!/usr/bin/env bash
NODE="$1"
BATCH=5 # number of stateless pods to evict concurrently
PAUSE=60 # seconds to wait between stateful pod evictions
# 1) Prevent new pods
kubectl cordon "$NODE"
# 2) Evict non-stateful pods in batches (ignore DaemonSets, mirror pods)
kubectl get pods --all-namespaces --field-selector spec.nodeName="$NODE" -o jsonpath='{range .items[*]}{.metadata.namespace}{" "}{.metadata.name}{" "}{.metadata.ownerReferences[0].kind}{"\n"}{end}' \
| awk '$3!="DaemonSet" && $3!="Node" {print $1"/"$2}' \
| head -n $BATCH \
| xargs -r -n1 -I{} kubectl evict -n $(echo {} | cut -d/ -f1) --name=$(echo {} | cut -d/ -f2) --force --grace-period=60 || true
# 3) Evict remaining stateless pods until none left
while kubectl get pods --all-namespaces --field-selector spec.nodeName="$NODE" -o jsonpath='{range .items[*]}{.metadata.namespace}{" "}{.metadata.name}{" "}{.metadata.ownerReferences[0].kind}{"\n"}{end}' \
| awk '$3!="StatefulSet" && $3!="DaemonSet" && $3!="Node" {print $1"/"$2}' | grep -q .; do
kubectl get pods --all-namespaces --field-selector spec.nodeName="$NODE" -o jsonpath='{range .items[*]}{.metadata.namespace}{" "}{.metadata.name}{" "}{.metadata.ownerReferences[0].kind}{"\n"}{end}' \
| awk '$3!="StatefulSet" && $3!="DaemonSet" && $3!="Node" {print $1"/"$2}' \
| xargs -r -n1 -P"$BATCH" -I{} sh -c 'kubectl evict -n $(echo {} | cut -d/ -f1) --name=$(echo {} | cut -d/ -f2) --grace-period=60 || true'
sleep 5
done
# 4) Evict stateful pods one-by-one with pause (respect PDBs)
kubectl get pods --all-namespaces --field-selector spec.nodeName="$NODE" -o jsonpath='{range .items[*]}{.metadata.namespace}{" "}{.metadata.name}{" "}{.metadata.ownerReferences[0].kind}{"\n"}{end}' \
| awk '$3=="StatefulSet" {print $1"/"$2}' \
| while read nspod; do
ns=$(echo $nspod | cut -d/ -f1)
pod=$(echo $nspod | cut -d/ -f2)
kubectl evict -n "$ns" --name="$pod" --grace-period=120 || kubectl delete pod -n "$ns" "$pod" --grace-period=120 --wait
sleep $PAUSE
done
# 5) Final drain (should be no non-daemonset pods left)
kubectl drain "$NODE" --ignore-daemonsets --delete-local-data --force --grace-period=60 || trueSample Answer
Sample Answer
Recommended Additional Resources
- Designing Data-Intensive Applications by Martin Kleppmann
- Site Reliability Engineering by Google (O'Reilly)
- The Site Reliability Workbook by Google (O'Reilly)
- The Phoenix Project by Gene Kim
- LeetCode (practice medium-level coding problems)
- System Design Primer GitHub repository
- Grokking System Design Interview
- Airbnb Engineering & Data Science Blog
- AWS Well-Architected Framework
- Google Cloud Architecture Framework
- Kubernetes Official Documentation
- Terraform Best Practices
- Prometheus Monitoring Documentation
- Incident Response & Post-Mortem Culture resources
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