← Confluent Interview Insights
No diagram needed, which I thought would make it easier.
Start by clarifying requirements (scale, read/write ratio, feed types) and then present a high-level architecture. Dive into database schema design with normalization considerations and API endpoints that support efficient feed retrieval and updates. Emphasize trade-offs and scalability, especially given Confluent's focus on event streaming.
Pro tip: Leverage Confluent's core competency by discussing how Kafka can be used to ingest and process feed updates in real-time, and how that integrates with your database and API layers.
Ask about expected scale (users, feeds, items), read/write patterns, latency requirements, and whether feeds are personalized or global. This ensures your design meets actual needs.
Outline components: feed ingestion, storage, API layer, and caching. Mention how data flows from sources to consumers, possibly using a message queue like Kafka.
Propose tables for feeds, items, subscriptions, and user-feed mappings. Discuss indexing, partitioning, and denormalization for read efficiency.
Define RESTful endpoints for creating feeds, adding items, subscribing, and fetching feeds. Include pagination, filtering, and authentication considerations.
Discuss how to scale reads/writes (caching, sharding, replication) and trade-offs between consistency and availability. Mention monitoring and failure handling.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.