What Candidates Reported
Two firsthand OpenAI software-engineering reports describe a webhook platform. One report specifies customer endpoint lookup and retries for twenty-four hours; a later report emphasizes billions of requests, reliability, performance, and implementation detail. The shared signal is strong enough for company-specific practice, while exact interviewer follow-ups may vary.
Problem and Scope
Design durable event acceptance, endpoint configuration, signed HTTP delivery, retries, status inspection, and replay. Clarify delivery guarantees, retryable status codes, tenant controls, payload limits, retention, and what the acceptance response proves before choosing storage or queue technology.
Critical Design Decisions
The hard parts are durable acknowledgement, explicit attempt state, retry scheduling, and fairness under failure amplification. A strong design separates event facts from delivery attempts, versions endpoint secrets, uses leases or equivalent recovery for workers, controls concurrency per tenant and destination, and makes duplicates observable rather than pretending they cannot occur.
Failure Scenarios to Practise
Pressure-test the system with a lost success response, a destination failing for hours, a hot tenant, secret rotation during backlog, worker death after send, poison payloads, delayed scheduler recovery, operator replay, and regional storage failure. For each case, explain durable state, the next permitted action, and the metric that reveals trouble.
How the Answer Is Evaluated
MockMe scores scope and delivery semantics (15%), architecture and state (20%), scale and tenant fairness (25%), reliability and security (25%), and communication and trade-offs (15%). High scores require a defensible acknowledgement boundary, bounded duplicate semantics, durable retries, downstream protection, and a concrete recovery model.