Went with WebSocket for real-time delivery, which felt like the right call.
Start by clarifying functional and non-functional requirements, then design a high-level architecture that separates concerns (e.g., message ingestion, storage, delivery). Dive into scaling strategies for each component, discussing trade-offs between consistency, latency, and cost.
Pro tip: Emphasize idempotency and exactly-once semantics for message delivery, as these are critical for reliability at scale. Also, discuss how to handle message ordering per conversation, which is a common pitfall.
Ask questions to understand scale (users, messages per second), features (group chats, presence, search), and non-functional needs (latency, consistency, availability).
Sketch the main components: clients, API gateway, message service, storage (e.g., Cassandra for messages, Redis for presence), and real-time delivery (WebSockets).
Explain how to partition messages (by channel ID), replicate for fault tolerance, and use queues (Kafka) to decouple producers and consumers. Discuss fan-out strategies for group messages.
Compare consistency models (strong vs. eventual), storage options (SQL vs. NoSQL), and delivery guarantees (at-least-once vs. exactly-once). Justify choices based on requirements.
Discuss offline users, message ordering, deduplication, and failure recovery (e.g., retries, dead-letter queues).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Sequence numbers came up naturally when I was talking about missed messages, so I leaned into that for ordering too.
Start by clarifying the requirements: what ordering guarantees are needed (global vs per-key), what consistency model is acceptable, and what trade-offs are tolerable. Then propose a design that uses partitioning with per-partition ordering, and discuss mechanisms like sequence numbers, idempotent consumers, and deduplication to handle out-of-order or duplicate messages.
Pro tip: Emphasize that strict global ordering is often unnecessary and can be a scalability bottleneck; instead, focus on per-key ordering and idempotency to achieve correctness without sacrificing throughput.
Ask about the required ordering guarantees (global, per-key, causal), the expected scale, latency, and consistency needs. This ensures you design the right solution for the problem.
Partition messages by a key (e.g., user ID, conversation ID) to ensure all messages for that key go to the same partition, preserving order within that key. This avoids global coordination.
Use monotonically increasing sequence numbers per partition or per key. Consumers can buffer and reorder messages based on these numbers, or use watermarks to handle late arrivals.
Design consumers to be idempotent and include deduplication logic (e.g., message IDs) to handle duplicates and retries without violating ordering semantics.
Compare approaches like total order broadcast (e.g., ZooKeeper, Raft) versus per-key ordering, and explain when each is appropriate. Mention monitoring and failure recovery.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by acknowledging the problem: WebSocket connections are inherently unreliable, so you need a mechanism to track and replay missed messages. Then propose a solution using sequence numbers and a durable message store, and discuss trade-offs like storage cost, latency, and complexity.
Pro tip: Mention that you would use a monotonic sequence number per connection and store messages in a durable log (like Kafka) with a retention policy, and that the client should send its last received sequence number on reconnect to fetch missed messages. This shows you understand both the protocol and system design aspects.
Ask about message delivery guarantees (at-least-once, exactly-once), message volume, latency requirements, and client capabilities. This shows you consider the context before designing.
Propose assigning a unique, monotonically increasing sequence number to each message per client or per channel. The client acknowledges the last received sequence number.
Store messages in a durable, ordered log (e.g., Kafka, Redis Streams, or a database) with a retention period. On reconnect, the client sends its last sequence number, and the server replays all messages after that.
Discuss scenarios like long disconnections exceeding retention, duplicate messages, and ordering. Mention trade-offs: storage cost vs. reliability, latency vs. consistency, and complexity vs. simplicity.
Conclude with a recommended approach (e.g., sequence numbers + Kafka) and suggest monitoring, testing, and fallback mechanisms (e.g., REST API for missed messages).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Push vs pull, batching to reduce noise, per-user preferences.
Start by clarifying the requirements and constraints of the notification system, such as scale, latency, delivery guarantees, and user experience goals. Then, systematically discuss the key trade-offs across dimensions like push vs pull, real-time vs batching, reliability vs cost, and privacy vs personalization. Conclude by proposing a balanced design that aligns with the product priorities.
Pro tip: Acknowledge that trade-offs are context-dependent and often involve business considerations; for example, at OpenAI, balancing user engagement with privacy and cost is crucial. Show maturity by discussing how you would measure and iterate on these trade-offs post-launch.
Ask questions to understand the scale (e.g., millions of users), latency requirements (real-time vs eventual), delivery guarantees (at-least-once, exactly-once), and user expectations (e.g., read receipts, typing indicators).
Outline the main dimensions such as push vs pull, real-time vs batching, reliability vs cost, and privacy vs personalization. Explain each briefly.
For each dimension, discuss the pros and cons. For example, push notifications reduce latency but increase server load and battery usage; batching saves resources but delays delivery.
Suggest a hybrid approach that leverages strengths of both sides, such as using push for real-time messages and pull for less urgent notifications, or implementing a tiered priority system.
Mention how to measure success (e.g., delivery latency, user engagement, cost per notification) and iterate based on metrics and user feedback.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.