Start by clarifying requirements and scale, then design a modular system that separates matchmaking logic from game session allocation. Focus on trade-offs between match quality and queue time, and explain how to handle parties and regional latency constraints.
Pro tip: Emphasize that matchmaking is a multi-objective optimization problem; propose a scoring function that balances skill, latency, and wait time, and discuss how to tune weights dynamically based on player feedback and queue health.
Ask about player base size, game types, skill metrics, latency thresholds, and party sizes. Establish non-functional requirements like queue time targets and match quality expectations.
Outline components: matchmaker service, player/party queue, skill rating service, regional pools, and game session allocator. Explain data flow from player join to match formation.
Describe how to group players: use a scoring function combining skill difference, latency, and wait time. Discuss algorithms like greedy matching, bucket-based, or expandable search windows.
Explain how to treat parties as atomic units, compute party skill (e.g., average or weighted), and assign parties to regional pools based on member latencies. Discuss cross-region matching fallbacks.
Discuss trade-offs: strict skill matching increases queue time; strict latency limits pool size. Propose dynamic tuning, sharding by region/game mode, and monitoring for queue health.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.