I started with the WebSocket layer and worked outward, which felt right but I spent too long on connection management before touching storage.
Start by clarifying requirements and scale (e.g., number of concurrent users, message volume, latency needs), then sketch a high-level architecture covering WebSocket management, message flow, presence, and storage. Dive into key components like connection servers, message queues, and databases, discussing trade-offs and failure handling.
Pro tip: Emphasize idempotency and message ordering—use client-generated message IDs and server-side sequencing to handle retries and ensure consistency. Also, discuss how to scale WebSocket connections horizontally with a pub/sub layer like Redis or Kafka.
Ask about expected user count, concurrent connections, message throughput, latency requirements, and whether messages need to be persisted indefinitely. This shapes your design choices.
Outline the main components: WebSocket servers for real-time communication, a message queue for decoupling, a database for conversation history, and a presence service. Explain how they interact.
Detail WebSocket connection management (load balancing, heartbeats), message delivery guarantees (at-least-once, ordering), presence tracking (using Redis with TTL), and storage schema (e.g., Cassandra for messages).
Discuss trade-offs like consistency vs. availability, push vs. pull for presence, and scaling WebSocket servers horizontally with a pub/sub system. Mention how to handle reconnections and missed messages.
Recap the design, highlighting how it meets requirements and handles failures. Be open to feedback and suggest potential improvements or next steps.
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Talked about a message queue with a delivery status flag and falling back to push notification or inbox retrieval on reconnect.
Start by clarifying the requirements: scale, latency, consistency, and offline duration. Then propose a hybrid approach: use a message queue for reliable delivery and a combination of caching and persistent storage for chat history, with a focus on trade-offs between consistency and availability.
Pro tip: Mention that offline delivery is not just about storing messages but also about syncing state when the user reconnects, and that you'd use a push notification service to alert the user of new messages.
Ask about expected scale (users, messages per second), offline duration, and consistency requirements (e.g., read receipts, ordering).
Propose a message queue (e.g., Kafka, RabbitMQ) to handle asynchronous delivery, with per-user queues and retry logic. Use push notifications for offline users.
Suggest a combination of a fast cache (Redis) for recent messages and a durable database (Cassandra, DynamoDB) for long-term storage, considering write-heavy workload.
Design a sync protocol: when user comes online, fetch missed messages using a timestamp or sequence number, and update read status.
Compare consistency vs. availability (CAP theorem), cost, and complexity. Justify choices based on requirements.
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This was the core of the whole question really.
Start by explaining the need for a shared registry that maps user IDs to server nodes, then describe how messages are routed between nodes using a pub/sub or message queue system. Finally, discuss trade-offs like latency, scalability, and failure handling.
Pro tip: Mention that you would use consistent hashing to minimize reconnections when scaling, and highlight the importance of idempotent message delivery to handle duplicate messages.
When a client connects via WebSocket, the server registers the user's ID and its own node ID in a shared registry (e.g., Redis or a database). This mapping is used to locate the user later.
When a sender sends a message to a recipient on another node, the sender's node publishes the message to a channel or queue that the recipient's node subscribes to. The recipient's node then delivers the message over the existing WebSocket connection.
If a node fails, the registry entries for its users must be updated, and clients should reconnect to other nodes. Use heartbeats and timeouts to detect failures and trigger re-registration.
Use consistent hashing to distribute users across nodes and minimize reconnections when adding/removing nodes. Load balancers can route initial WebSocket connections to available nodes.
Compare approaches: direct node-to-node communication vs. message broker (e.g., Redis Pub/Sub, Kafka). Consider latency, reliability, complexity, and scalability.
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Came at the end and felt like a curveball after all the WebSocket depth.
Start by clarifying requirements and scale, then propose a decoupled, event-driven architecture using a scheduler, a rules engine, and a notification service. Focus on reliability, idempotency, and scalability while discussing trade-offs and monitoring.
Pro tip: Emphasize idempotency and failure handling—ensure emails aren't sent multiple times if the job retries, and consider using a distributed lock or a deduplication store. Also, mention the importance of tracking email engagement and allowing opt-outs to comply with regulations like CAN-SPAM.
Ask about expected user volume, email frequency, and any existing infrastructure. Confirm that '10 days' is a rolling window and that emails should be sent only once per inactivity period.
Identify how to efficiently find users who haven't logged in for 10 days. Propose an index on last_login_at and a query that runs periodically, or a change-data-capture approach if near-real-time is needed.
Outline a scheduled job (e.g., cron or cloud scheduler) that triggers a service to query eligible users, enqueue email tasks, and invoke an email service. Use a message queue to decouple and handle retries.
Describe how to prevent duplicate emails: use a unique constraint on (user_id, campaign_id) or a distributed lock. Implement retry logic with exponential backoff and dead-letter queues for failures.
Discuss monitoring metrics (emails sent, failures, latency) and logging. Suggest A/B testing email content and tracking open rates to optimize engagement.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.