Went in without having specifically prepped for system design, which was a mistake in hindsight.
Start by clarifying requirements and constraints (e.g., scale, supported languages, real-time collaboration, security). Then propose a high-level architecture covering frontend, backend, storage, and compute, and dive into critical components like code execution isolation and real-time sync. Finally, discuss trade-offs, scalability, and potential integrations with AI/ML services.
Pro tip: Emphasize security and isolation for code execution, as running untrusted code is a major risk; mention using containers or microVMs (e.g., Firecracker) and strict resource limits. Also, highlight how you would leverage OpenAI's models for features like code completion or debugging assistance.
Ask questions to understand expected scale, supported languages, collaboration features, and security needs. Define functional and non-functional requirements.
Outline the main components: frontend (editor UI), backend services (API gateway, auth, project management), storage (file system, database), and compute (code execution). Sketch a diagram.
Focus on code execution isolation (sandboxing), real-time collaboration (CRDTs/OT), and file storage (versioning, sync). Discuss technologies and trade-offs.
Explain how to scale each component (e.g., horizontal scaling, caching, CDN) and ensure fault tolerance (replication, backups). Address latency and global distribution.
Detail security measures (auth, encryption, sandboxing) and how to integrate AI features (code completion, error detection) using OpenAI's APIs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.