OpenAIVerified interview challenge
Review a distributed job scheduler
Find the design choices that could lose a job, run it twice or leave it stuck after a failure.
Unlock with Full AccessThe challenge
Several internal teams share a service for evaluation and data-processing jobs. Work can last seconds or hours, and some jobs write to external systems. Multiple API replicas and schedulers must coordinate a common worker pool.
Review how the proposed system accepts, assigns, retries and cancels work. Explain where concurrent schedulers or a worker failure could change what actually runs, and what needs to change before teams depend on the service.
What you'll practise
Job ownership
Check how concurrent schedulers establish who is responsible for accepted work.
Failure recovery
Reason about retries, worker loss and jobs that remain marked as running.
Explain the issue, its consequence and the change you would make.