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

SeniorPrefer not to say
May 2026

Summary

Stripe system design round for a software engineer role. The whole interview was built around a single multi-part problem that kept layering on complexity, which I wasn't fully prepared for going in.

Questions Asked (1)

Q1

Design a load balancer that distributes WebSocket connections across multiple Jupyter servers. Start with basic assignment logic, then extend it to handle disconnections, object-level stickiness, per-server capacity limits, and graceful server shutdown with connection re-routing.

System DesignTechnical Trade-offsData Modeling
Author's notes

This was five questions disguised as one.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design a basic load balancer with a simple assignment strategy like round-robin or least connections. Iteratively extend the design to handle disconnections, object-level stickiness, per-server capacity limits, and graceful shutdown, discussing trade-offs at each step. Emphasize scalability, fault tolerance, and consistency.

Pro tip: Demonstrate awareness of real-world constraints by discussing how to handle sticky sessions without overloading servers, and how to ensure zero-downtime during server shutdowns. Mention monitoring and metrics for capacity planning.

1. Clarify Requirements and Assumptions

Ask questions to understand scale, expected number of connections, server capacity, and stickiness requirements. Define what 'object-level stickiness' means (e.g., same user or notebook session routed to same server).

2. Design Basic Load Balancing

Propose a simple assignment strategy such as round-robin or least connections. Discuss how the load balancer tracks server states and assigns new WebSocket connections.

3. Handle Disconnections and Reconnections

Explain how to detect disconnections (heartbeats, timeouts) and update server load. For reconnections, decide whether to reassign or attempt to route back to the same server based on stickiness.

4. Implement Object-Level Stickiness and Capacity Limits

Introduce a mapping (e.g., consistent hashing or a lookup table) to route connections for the same object (user, notebook) to the same server. Enforce per-server capacity limits by rejecting or queuing connections when full.

5. Graceful Shutdown and Re-routing

Describe a process for draining connections from a server being shut down: stop accepting new connections, notify clients to reconnect, and re-route existing connections to other servers without data loss.

Key Points to Mention

  • Consistent hashing for stickiness while minimizing rebalancing when servers are added/removed
  • Health checks and heartbeats to detect server failures and disconnections
  • Capacity limits and backpressure mechanisms to prevent overload
  • Graceful shutdown with connection draining and client reconnection logic
  • Trade-offs between stickiness and load distribution (e.g., hot spots)
  • Monitoring and metrics for server load and connection counts

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