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Google·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
May 2026

Summary

System design round at Google for a software engineer role. The question was a big one: design a full collaborative code notebook service end to end, including execution, proxying, custom JAR uploads, and all the REST API plumbing. Walked away feeling like I covered maybe 70% of what they were looking for.

Questions Asked (1)

Q1

Design a collaborative, editable code notebook service where users can upload custom JAR files with a fully qualified class and method name, submit execution requests with arguments, and retrieve results through a proxy. Define the REST API endpoints and request/response schemas for uploading code, submitting executions, fetching logs and results, and cancelling jobs. Also discuss sandboxing, dependency management, resource limits, concurrency, and result streaming.

System DesignAPI & IntegrationsTechnical Trade-offs
Author's notes

This was a lot to hold in your head at once.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints (e.g., scale, security, latency) with the interviewer. Then present a high-level architecture covering API design, execution flow, and sandboxing, and dive into trade-offs for each component. Finish by discussing operational concerns like monitoring and failure handling.

Pro tip: Emphasize security and isolation early, as executing user-provided code is the biggest risk. Show you understand that sandboxing and resource limits are non-negotiable for a production system.

1. Clarify Requirements and Scope

Ask questions to understand expected scale, latency, security requirements, and supported languages. Confirm whether the service is multi-tenant and what level of isolation is needed.

2. Design REST API and Schemas

Define endpoints for uploading JARs, submitting executions, fetching logs/results, and cancelling jobs. Specify request/response formats, status codes, and error handling.

3. Architect Execution and Sandboxing

Describe how to run user code securely: use containers or microVMs, enforce resource limits (CPU, memory, time), and manage dependencies. Discuss class loading and isolation.

4. Handle Concurrency and Streaming

Explain how to manage concurrent executions, queueing, and scaling. Describe mechanisms for streaming logs and results in real-time, such as WebSockets or SSE.

5. Address Trade-offs and Operations

Discuss trade-offs between isolation levels, performance, and cost. Cover monitoring, logging, failure recovery, and how to handle dependency conflicts.

Key Points to Mention

  • Sandboxing techniques: containers (Docker), microVMs (Firecracker), or gVisor for strong isolation.
  • Resource limits: CPU, memory, disk, and execution time quotas per job.
  • Dependency management: classloader isolation, dependency resolution, and caching.
  • Concurrency: job queue, worker pool, and autoscaling based on load.
  • Result streaming: WebSockets, Server-Sent Events (SSE), or long polling for real-time updates.
  • API design: RESTful endpoints with clear schemas, idempotency, and pagination for logs.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.