Questions
10 of 10
Design a worker pool for processing 100,000 jobs with back-pressure and graceful shutdown.
Difficulty: 7/10
worker pool, back-pressure, graceful shutdown
A worker pool uses a buffered jobs channel for back-pressure, N goroutines as workers, a WaitGroup for tracking completion, and context cancellation for graceful shutdown.
Production-grade worker pool
Design notes
- 1
Buffer size controls back-pressure: smaller buffer = tighter back-pressure on producer
- 2
Close the jobs channel to signal workers — ranging over a closed channel exits cleanly
- 3
WaitGroup ensures all in-progress jobs complete before results channel is closed
- 4
For context-aware cancellation, pass ctx to each worker and select on ctx.Done()
- 5
Add a dead-letter queue or retry channel for failed jobs in production
Scenario Questions
0-2 years experience
- 1How would you implement a simple worker pool in Go to process 100,000 jobs without overwhelming the system?
- 2What happens if you close the job channel while some workers are still processing jobs?
- 3How would you signal the workers to stop once all jobs have been dispatched?
2-5 years experience
- 1You notice the job queue growing without bound under heavy load; how would you add back‑pressure to the pool?
- 2During a deployment the shutdown hangs—what could cause workers not to exit, and how would you fix it?
- 3If you need to limit concurrency to 50 workers but also prioritize high‑priority jobs, how would you modify the design?
5-8 years experience
- 1Design the pool to handle spikes up to 200,000 jobs while keeping latency low; discuss the trade‑offs between a buffered channel and a semaphore approach.
- 2Explain how you would implement graceful shutdown that drains in‑flight jobs, respects a timeout, and reports errors.
- 3What monitoring and tuning strategies would you put in place in production to detect deadlocks or resource exhaustion?
8+ years experience
- 1If the system must evolve to a distributed worker pool across multiple services, how would you refactor the design while preserving back‑pressure semantics?
- 2Discuss the impact of using context cancellation versus a custom shutdown protocol on cross‑team APIs and reliability.
- 3What long‑term maintenance concerns arise from coupling job ordering with back‑pressure, and how would you mitigate them?
Follow-up Questions
- Can you walk me through the shutdown sequence step by step?
- How would you test that back‑pressure works under load?
- What metrics would you expose to monitor the pool's health?