This one has a few layers and I underestimated the failure-handling part at first.
Start by modeling components and dependencies as a directed graph, then use topological sort (e.g., Kahn's algorithm) to determine initialization order while detecting cycles. Discuss failure handling with rollback or retry strategies, and tie it to a real service startup flow like DoorDash's microservices, emphasizing idempotency and observability.
Pro tip: Emphasize that in production, you'd likely use a battle-tested dependency injection framework or orchestrator rather than reinventing the wheel, but understanding the underlying algorithm is crucial for debugging and customizing behavior.
Represent each component as a node and dependencies as directed edges. This abstraction allows you to apply graph algorithms for ordering and cycle detection.
Use Kahn's algorithm or DFS-based topological sort to produce a linear order. If a cycle is detected, report the circular dependency and fail fast with a clear error.
For each component, attempt initialization; on failure, either retry with backoff, skip dependents, or rollback already initialized components. Ensure idempotency and log failures with context.
In a real service, this routine runs during bootstrap, possibly with health checks and readiness probes. Consider parallel initialization where dependencies allow, and expose metrics for startup time and failures.
Compare custom implementation vs. using a DI container or orchestration tool. Address scalability, dynamic dependencies, and how to handle partial failures in distributed systems.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.