This is the kind of question where you can go deep fast and still feel like you barely scratched the surface.
Start by clarifying the requirements: what does 'strong consistency' mean in this context (e.g., linearizability, serializability, ACID)? Then propose a design that separates the write path (e.g., using a consensus protocol like Raft or Paxos for the core ledger) from the read path (e.g., using read replicas or caching for scalability). Discuss trade-offs between consistency, latency, and throughput, and how to scale horizontally while maintaining correctness.
Pro tip: Emphasize that strong consistency and high scalability are not mutually exclusive if you partition the ledger by account or shard, and use a two-phase commit or distributed transactions only where necessary. Also, mention real-world examples like Stripe's own architecture or Google Spanner to show practical awareness.
Ask questions to understand the expected transaction volume, latency requirements, and what 'strong consistency' entails (e.g., linearizability, serializability). Also clarify if the ledger is append-only and if it needs to support multi-currency or multi-account transactions.
Propose a core ledger service that uses a consensus protocol (e.g., Raft) to replicate a write-ahead log across multiple nodes for durability and consistency. For scalability, partition the ledger by account ID or use a sharding scheme, ensuring that transactions involving multiple shards use a distributed transaction protocol like two-phase commit.
Design an append-only data model with immutable entries, each with a unique transaction ID and timestamps. Use a storage engine that supports ACID transactions (e.g., PostgreSQL with serializable isolation) or a distributed SQL database like Spanner. Consider using a log-structured merge-tree (LSM) for high write throughput.
Scale horizontally by sharding the ledger across multiple nodes, with each shard handling a subset of accounts. Use a routing layer to direct transactions to the appropriate shard. For cross-shard transactions, implement a two-phase commit or use a distributed transaction coordinator. Add read replicas to scale reads.
Discuss trade-offs: stronger consistency may increase latency; sharding can complicate cross-shard transactions. Explain how to handle failures: use leader election, retries with idempotency keys, and ensure exactly-once semantics. Mention monitoring and alerting for consistency violations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Felt a bit out of left field after the ledger question.
Structure your answer around a clear integration plan: start by defining the requirements and evaluating the library, then design a thin abstraction layer to isolate it, and finally walk through data flow, error handling, and deployment considerations. Emphasize trade-offs and production readiness, showing how you'd minimize coupling and ensure reliability.
Pro tip: Show that you think about the library as an implementation detail: wrap it behind your own interface so you can swap it out later without touching business logic. Also, mention how you'd handle API keys and rate limits securely, which is crucial for Stripe's production environment.
Ask about expected scale, latency, and feature needs. Evaluate the library's API, licensing, maintenance, and performance to ensure it fits.
Create a thin wrapper or adapter that exposes only the functionality you need, using your own types and interfaces to decouple from the library.
Define how data enters and exits the library, including transformation, caching, and synchronization with your app's state.
Implement retries, fallbacks, and logging for library failures. Ensure errors are translated into your app's error model.
Consider bundling, versioning, feature flags, and monitoring. Ensure the integration can be rolled out safely and rolled back if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.