Start by clarifying requirements and scale, then propose an inverted index mapping instance types to available servers, using a greedy allocation strategy to minimize fragmentation. Discuss concurrency with fine-grained locking or sharding, and fault tolerance with health checks and reallocation.
Pro tip: Emphasize that the system should be designed for observability and graceful degradation—e.g., if a node fails, the service should automatically mark it unhealthy and trigger reallocation without impacting ongoing allocations.
Ask about request patterns, instance type diversity, latency SLAs, and consistency needs. Confirm that nodes can satisfy multiple instance types and that allocation should be atomic.
Propose an inverted index from instance type to a set of available server IDs, plus a server metadata store. Consider using a distributed key-value store or in-memory sharded maps for scalability.
Use a greedy algorithm that picks servers with the fewest remaining compatible types to reduce fragmentation. For multiple instance types, solve as a bipartite matching or flow problem if needed.
Implement fine-grained locking per instance type or use optimistic concurrency with versioning. Ensure fairness by using queues or time-based priorities to prevent starvation.
Use heartbeats and health checks to detect node failures. On failure, mark node unavailable, release its allocations, and trigger reallocation for affected requests.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.