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Cloudkitchens·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

CloudKitchens SWE interview, got a concurrency design question that was more involved than I expected for a coding round. They wanted a full working implementation, not just a whiteboard sketch.

Questions Asked (1)

Q1

Design and implement a thread-safe restaurant order system where multiple threads can place orders, one or more chef threads cook them concurrently, and customer threads block until their specific order is ready for pickup. No deadlocks, no busy-waiting, each order cooked exactly once.

System DesignTechnical Trade-offsAlgorithms & Data Structures
Author's notes

This one took me a minute to even parse.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a design using a shared data structure with fine-grained locking and condition variables to coordinate between customers and chefs. Walk through the synchronization logic, ensuring each order is cooked exactly once and customers block efficiently without busy-waiting. Finally, discuss trade-offs and potential optimizations.

Pro tip: Emphasize the use of condition variables with a predicate loop to avoid spurious wakeups and ensure correctness, and mention how you would test for deadlocks and race conditions using stress tests.

1. Clarify Requirements and Constraints

Ask questions to confirm assumptions: number of chefs, order types, priority, cancellation, and whether orders can be batched. Clarify that 'cooked exactly once' means no duplicate cooking and no missed orders.

2. Design Data Structures and Synchronization

Propose a shared order queue (e.g., thread-safe queue) and a map from order ID to order status. Use a mutex to protect shared state and condition variables to signal order readiness and new orders.

3. Define Thread Roles and Interactions

Customer threads enqueue orders and then wait on a condition variable until their order is marked ready. Chef threads wait for orders, dequeue one, cook it, mark it ready, and signal the corresponding customer.

4. Address Edge Cases and Correctness

Ensure each order is cooked exactly once by having chefs atomically claim an order. Handle spurious wakeups with while loops. Prevent deadlocks by consistent lock ordering and avoiding nested locks.

5. Discuss Trade-offs and Optimizations

Compare fine-grained vs. coarse-grained locking, consider using a thread pool for chefs, and discuss scalability. Mention alternative approaches like message queues or actor model.

Key Points to Mention

  • Use of mutex and condition variables for efficient blocking without busy-waiting
  • Ensuring each order is cooked exactly once via atomic claim or state transition
  • Avoiding deadlocks by consistent lock acquisition and no nested locks
  • Handling spurious wakeups with predicate loops in condition variable waits
  • Trade-offs between fine-grained and coarse-grained locking
  • Testing strategy: stress tests, race detectors, and deadlock detection

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