Lyft DevOps / SRE Interview Questions

1.Tell me about a time you were on-call for a service that went down. Walk me through what happened and how you handled the incident from start to finish.

2.Tell me about your most challenging production outage. How did you lead the response and what did you learn from it?

3.Describe a time you worked on a system that had to handle location data or real-time matching. What were the unique challenges and how did you solve them?

4.Walk me through a time you reviewed another team's system design and pushed back on their approach. What was your feedback and how did they respond?

5.Tell me about a time you had to design monitoring or safeguards to prevent fraud or ensure user safety in a system you managed.

6.Describe a time you broke apart a monolithic system into services or combined services that had grown too complex. What drove that decision?

7.You're setting up monitoring for Lyft's real-time matching service that connects riders with drivers. The service processes 50,000 requests per second during peak hours. What key metrics would you track and what alerting thresholds would you set?

8.Walk me through how you would set up disaster recovery for Lyft's driver dispatch system across multiple AWS regions. The system needs to maintain service during regional outages.

9.Lyft's payment processing service needs to handle spikes during events like New Year's Eve when ride volume increases 10x in certain cities. How would you design autoscaling to handle this traffic pattern?

10.Describe how you would implement canary deployments for Lyft's pricing algorithm service. This service calculates ride prices in real-time and any bugs could overcharge or undercharge riders.

11.You're tasked with migrating Lyft's driver location tracking from a monolithic service to microservices. The current system processes 100,000 location updates per second from active drivers. Walk me through your migration approach.

12.You need to set up log aggregation for Lyft's 2,000+ microservices running on Kubernetes. The system needs to handle 50TB of logs per day while keeping costs reasonable. How would you architect this?

13.Design an alerting system for Lyft's Envoy service mesh that manages traffic between 2,000+ microservices. The system needs to detect network partitions and cascading failures before they impact riders.

14.Design a backup and recovery system for Lyft's driver earnings database that processes $2 billion in payments annually. The system must support point-in-time recovery and meet financial audit requirements while handling 100,000 transaction updates per minute.

15.You need to design a configuration management system for Lyft's pricing algorithms that can safely push price changes to specific cities within 30 seconds. Any misconfiguration could cause surge pricing to break during peak hours.

16.Walk me through how you'd design capacity planning for Lyft's driver dispatch system during major events like New Year's Eve, when demand surges 15x in specific neighborhoods but driver supply doesn't scale proportionally.

17.Design a secrets management system for Lyft's driver background check API integrations. The system stores SSNs and handles requests from 50+ different government and third-party verification services with varying compliance requirements.

18.You're designing a deployment system for Lyft's mobile SDKs that get embedded in driver and rider apps. A bad SDK release could break ride requests for millions of users, and you can't force immediate app store updates.

19.Tell me about a time you had to convince another team to adopt a change that would improve reliability but required extra work from them. How did you approach it?

20.Walk me through a time when you had to make a tough operational decision during a high-pressure situation, like a major outage or capacity crisis. How did you balance speed with thoroughness?

21.Describe a situation where you had to push back on a timeline or technical decision because you believed it would compromise system safety or reliability. What was the outcome?

22.Tell me about a time when you inherited a service or system that was poorly documented or had reliability issues. How did you approach fixing it while keeping it running?

23.Describe a time you had to coordinate an incident response that involved multiple teams you didn't directly manage. How did you ensure effective communication and resolution?

24.Tell me about a time you championed a significant infrastructure change or tool adoption that required getting buy-in from senior engineers across multiple teams. What was your strategy?

25.Estimate how much storage Lyft needs to retain location data for all driver trips in a given year. Walk me through your calculation and key assumptions.

26.You notice that Lyft's driver app is consuming 40% more battery than normal, and driver complaints are increasing. How would you systematically diagnose what changed?

27.Estimate the cost impact if our Envoy service mesh added an average of 5ms latency to every internal API call across Lyft's microservices architecture.

28.Design a chaos engineering program for Lyft's payment processing pipeline that handles driver earnings payouts worth $2 billion annually. What experiments would you run and how would you measure success?

29.Lyft's surge pricing algorithm needs to update prices every 30 seconds across 300+ cities during peak demand. Estimate the infrastructure cost and design the deployment strategy to ensure price accuracy.

30.You're investigating why Lyft's rider app shows 'no drivers available' in downtown SF during rush hour when the driver heat map shows 200+ active drivers in that area. Walk me through your diagnostic approach.