Question 1

Tell me about a time when you had to balance feature delivery pressure with system reliability concerns. How did you handle it?

Accepted Answer

At my previous company, the product team wanted to deploy a new feature before a major marketing campaign, but our error budget was nearly exhausted. I organized a meeting with stakeholders to present our SLO data and explain the risks. I proposed a middle ground: deploying the feature with additional monitoring and feature flags for quick rollback. We implemented comprehensive alerting and canary deployment to minimize risk. The feature launched successfully with zero customer impact, and we improved our deployment process for future releases.

Question 2

Describe a major incident you led the response for. What was your approach and what did you learn?

Accepted Answer

I led response for a database outage affecting 40% of our users. I immediately established an incident command structure, delegated roles for communication and investigation, and ensured regular status updates. While the team worked on the root cause, I coordinated with customer support and prepared rollback options. We identified a memory leak in a recent deployment and executed a rollback within 45 minutes. Post-incident, I facilitated a blameless postmortem that resulted in improved deployment testing and automated rollback procedures. This incident taught me the importance of clear communication and having predefined response procedures.

Question 3

Give me an example of when you automated a manual process. What was the impact?

Accepted Answer

Our team spent 2-3 hours weekly manually scaling applications based on traffic patterns. I analyzed historical data and created automated scaling policies using Kubernetes HPA and custom metrics. I developed Terraform modules for consistent deployment and integrated Slack notifications for scaling events. The automation reduced manual intervention by 95% and improved response time to traffic spikes from 15 minutes to under 2 minutes. This freed up the team to focus on more strategic reliability improvements and saved approximately 12 hours per week across the team.

Question 4

Explain how you would design and implement SLOs and SLIs for a high-traffic web application. What metrics would you choose and why?

Accepted Answer

I'd start by identifying user-critical journeys like login, search, and checkout. For SLIs, I'd measure availability (success rate of requests), latency (95th percentile response time), and throughput (requests per second handled successfully). I'd set SLOs like 99.9% availability, 95th percentile latency under 200ms, and error rate below 0.1%. I'd implement measurement at load balancers for accuracy and use time-window based error budgets. For tooling, I'd use Prometheus for metrics collection, Grafana for visualization, and custom alerting when error budget burn rate exceeds thresholds. This approach ensures SLOs align with actual user experience rather than internal system metrics.

Question 5

How would you troubleshoot a Kubernetes application that's experiencing intermittent connectivity issues?

Accepted Answer

I'd start by checking service and pod status with kubectl get pods,svc,endpoints to ensure proper registration. Next, I'd examine network policies and service mesh configurations if applicable. I'd use kubectl logs to check application logs and kubectl describe to review events and resource constraints. For network-level debugging, I'd use tools like kubectl exec to run tcpdump or netstat from within pods. I'd check DNS resolution with nslookup and verify kube-proxy configuration. If using a service mesh like Istio, I'd examine proxy logs and check for circuit breaker configurations. I'd also monitor for resource exhaustion and check if intermittent issues correlate with deployment events or traffic patterns.

Question 6

Describe your approach to monitoring a microservices architecture. What tools and techniques would you use?

Accepted Answer

I'd implement the three pillars of observability: metrics, logs, and traces. For metrics, I'd use Prometheus with service-level indicators like request rate, error rate, and latency for each service. For distributed tracing, I'd implement OpenTelemetry to track requests across service boundaries and identify bottlenecks. For logging, I'd use structured logging with correlation IDs and aggregate logs using ELK stack or similar. I'd implement synthetic monitoring to proactively test critical user journeys and set up dashboards showing service dependencies and health. Alert fatigue prevention would be crucial, so I'd focus on symptom-based alerting rather than cause-based, using techniques like alert grouping and escalation policies.

Question 7

Your production database is experiencing high latency during peak hours, affecting 30% of user requests. How would you approach this problem?

Accepted Answer

First, I'd establish incident response procedures and communicate with stakeholders about the impact. I'd immediately check for obvious causes like long-running queries, lock contention, or resource exhaustion. I'd examine database metrics including CPU, memory, disk I/O, and connection counts. If resources are maxed out, I'd consider immediate scaling or query optimization. I'd analyze slow query logs and check for missing indexes or poorly performing queries deployed recently. For immediate relief, I might implement read replicas or caching layers. I'd coordinate with development teams to optimize problematic queries and consider implementing connection pooling if not already present. Post-resolution, I'd conduct a thorough postmortem and implement monitoring to prevent recurrence.

Question 8

A new deployment has increased error rates by 5%, but it's within your error budget. The development team wants to keep the deployment. What do you do?

Accepted Answer

I'd first investigate the nature of the errors to understand user impact and whether they represent a degrading trend. While within budget, a 5% increase could indicate underlying issues that might worsen. I'd analyze error patterns, affected user segments, and correlation with specific features. I'd propose enhanced monitoring and alerting for the new deployment while gathering more data. I'd work with the development team to identify root causes and create a plan for addressing them. If errors are acceptable and stable, I'd document the decision and ensure we have rollback procedures ready if the situation deteriorates. I'd also update our monitoring to detect if error rates continue climbing beyond acceptable thresholds.

Question 9

Why are you interested in Site Reliability Engineering, and what attracts you to this role?

Accepted Answer

I'm passionate about SRE because it combines my love for software development with systems thinking and operational excellence. I enjoy the challenge of designing resilient systems that can handle scale while maintaining reliability. What attracts me most is the focus on automation and the scientific approach to reliability through SLOs and error budgets. I appreciate how SRE bridges the gap between development and operations, enabling faster delivery without sacrificing stability. The continuous learning aspect is exciting - from distributed systems to new technologies like service mesh and chaos engineering. I'm motivated by the direct impact SRE has on user experience and business success through improved reliability and performance.

Question 10

Where do you see yourself in your SRE career in the next 5 years?

Accepted Answer

In five years, I see myself as a senior SRE or SRE team lead, having developed deep expertise in distributed systems and cloud-native technologies. I want to be recognized as a subject matter expert in areas like chaos engineering, observability, and reliability patterns. I'm interested in mentoring junior engineers and helping shape SRE practices across the organization. I'd like to contribute to the SRE community through speaking at conferences or open-source contributions. From a technical perspective, I want to stay current with emerging technologies like serverless, edge computing, and AI/ML operations. Ultimately, I see myself driving strategic reliability initiatives that have significant business impact while continuing to grow my technical and leadership skills.

Overview

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1. Why are you interested in Site Reliability Engineering, and what attracts you to this role?

2. Where do you see yourself in your SRE career in the next 5 years?

3. What do you consider your greatest strength as an SRE, and how has it benefited your previous teams?

4. Describe a technical challenge you're currently trying to improve or learn more about.

5. What questions do you have about our SRE team, infrastructure, or engineering culture?

6. Explain how you would design and implement SLOs and SLIs for a high-traffic web application. What metrics would you choose and why?

7. How would you troubleshoot a Kubernetes application that's experiencing intermittent connectivity issues?

8. Describe your approach to monitoring a microservices architecture. What tools and techniques would you use?

9. How would you implement automated incident response for a production system? Walk me through your approach.

10. Explain how you would migrate a monolithic application to microservices while maintaining system reliability.

11. How would you design a deployment pipeline that minimizes risk while enabling fast delivery?

12. Describe how you would handle capacity planning for a rapidly growing service.

13. How would you implement and maintain effective alerting to minimize alert fatigue while ensuring critical issues are caught?

14. Tell me about a time when you had to balance feature delivery pressure with system reliability concerns. How did you handle it?

15. Describe a major incident you led the response for. What was your approach and what did you learn?

16. Give me an example of when you automated a manual process. What was the impact?

17. Tell me about a time when you had to convince a development team to make changes for reliability improvements.

18. Describe a situation where you had to learn a new technology quickly to solve a critical problem.

19. Tell me about a time when you disagreed with a technical decision made by senior leadership. How did you handle it?

20. Describe a time when you made a mistake that impacted system reliability. How did you handle it?

21. Tell me about a time when you had to work with limited resources to improve system reliability.

22. Describe a situation where you had to prioritize multiple competing reliability issues. How did you decide what to focus on first?

23. Tell me about a time when you had to advocate for investing in infrastructure or tooling improvements that weren't immediately visible to business stakeholders.

24. Your production database is experiencing high latency during peak hours, affecting 30% of user requests. How would you approach this problem?

25. A new deployment has increased error rates by 5%, but it's within your error budget. The development team wants to keep the deployment. What do you do?

26. Your team is asked to support a new service, but you're already at capacity. How would you handle this request?

27. You discover that a critical security patch will require a system restart during business hours. How do you proceed?

28. Your monitoring system is generating false positive alerts frequently. How would you address this while ensuring you don't miss real issues?

29. A developer wants to deploy a change that you believe could impact system stability, but they disagree. How do you handle this conflict?

30. Your primary cloud provider is experiencing a major outage affecting your service. Walk me through your response.

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