This one took me a minute to even scope properly.
Start by clarifying requirements and constraints, then propose a modular architecture with components for capture, storage, replay, and comparison. Emphasize handling stateful endpoints through session management and ordering via sequence numbers, and implement diff-tolerant comparison using normalization rules. Discuss trade-offs and scalability considerations.
Pro tip: Highlight the importance of idempotency and isolation when replaying against live services to avoid side effects, and suggest using a sandbox or mock environment for safe testing.
Ask questions to understand the scope: what protocols (HTTP/RPC), expected volume, latency requirements, and whether replay is against live or mock services. Clarify how stateful endpoints should be handled and what constitutes a diff-tolerant comparison.
Propose a capture mechanism that can intercept requests from live traffic or parse recorded logs. Store requests and expected responses in a structured format (e.g., JSON) with metadata like timestamps, sequence numbers, and session IDs.
Outline a replay engine that reads stored requests, orders them correctly (using sequence numbers or timestamps), and sends them to the target service. Handle stateful endpoints by maintaining session state (e.g., cookies, tokens) and ensuring requests are replayed in the correct order.
Implement a comparator that normalizes responses by ignoring volatile fields like timestamps and generated IDs. Use configurable rules (e.g., regex, JSON path) to define what to ignore, and provide a detailed diff report for mismatches.
Address trade-offs such as replay speed vs. accuracy, handling of non-deterministic responses, and scalability for large volumes. Mention potential optimizations like parallel replay with careful ordering, and isolation to avoid side effects.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.