The interviewer had built this thing themselves, so every time I glossed over something they just stared at me and waited.
Start by clarifying requirements and constraints (e.g., scale, latency, isolation, supported languages) to scope the problem. Then present a high-level architecture with core components, data flow, and API design, and finally dive into scalability strategies like horizontal scaling, caching, and multi-region deployment. Emphasize trade-offs and justify your choices.
Pro tip: Proactively discuss failure modes and how to handle them (e.g., node failures, network partitions) to demonstrate production maturity. Also, tie scalability decisions back to cost and operational complexity, showing you understand real-world constraints.
Ask questions to understand expected scale (users, concurrent sessions), latency requirements, isolation needs, supported languages/tools, and budget. This ensures your design targets the right problem.
Outline the main components: API gateway, orchestrator, container runtime (e.g., Docker/Kubernetes), persistent storage, and networking. Describe how a user request flows from authentication to environment provisioning.
Define key APIs (e.g., create/start/stop environment, exec commands, file sync) and how they integrate with version control, CI/CD, and monitoring. Consider using WebSockets for interactive sessions.
Explain how to scale each layer: stateless services with load balancers, container orchestration with auto-scaling, distributed storage, caching, and multi-region deployment. Address bottlenecks like cold starts and resource contention.
Discuss trade-offs (e.g., isolation vs. density, latency vs. cost) and how to handle failures (e.g., retries, circuit breakers, graceful degradation). Mention monitoring and observability.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.