Tony has provided the following feedback on your session:

Rafael demonstrated strong architectural thinking and communication throughout this complex system design mock focused on Slack-like messaging at OpenAI scale. He showed an ability to balance real-time messaging guarantees with practical tradeoffs in availability, latency, and complexity. The conversation was structured, with strong pacing and technical depth.

Areas of strength included:

• Solid assumptions and scalability awareness, including both peak and average load estimations.
  
  
• Fast and structured breakdown of functional requirements, plus thoughtful CAP theorem tradeoff discussions (e.g., high availability at system level vs. strong consistency in message delivery).
  
  
• Deep familiarity with websocket vs. long polling, and good initiative in focusing the discussion on online users first.
  
  
• Clear high-level design with workflow and entity expansion — modeling thread as parent of message, supporting both 1-1 DMs and channels.
  
  
• Strong understanding of entity relationships (user, message, channel, channel_participants, etc.) and how those power the backend.
  
  
• Great breakdown of websocket message events and payload structures.
  
  
• Excellent treatment of media message handling — pre-signed S3 URLs, media keys, upload parallelism, and why URLs don’t need to be tracked.
  
  
• Smart inclusion of CDNs and recipient-side media fetching using keys.
  
  
• Consideration for multi-device session management, local caching, and handling message history fetch with pagination.
  
  
• Strong modeling of offline inbox flows and flush-on-reconnect behavior.
  
  
• Good insight into hot channels (celebrity-style) — switching to pull rather than push.
  
  
• Nuanced discussion of message ordering, including lock-based service-level monotonic timestamps vs. Kafka queue partitioning by chat_id.
  
  
• Concrete breakdown of websocket connection flow and Redis TTL caching, including:
  
  
  
  1. User connects to ws server
     
     
  2. WS fetches chat_ids
     
     
  3. WS caches mapping with TTL lease
     
     
  4. WS subscribes to topic
     
     
  5. WS unsubscribes on TTL expiry
     
     
  6. Device+user-level mapping for deduplication
     
     
• Good idempotency design using dedupe keys
  
  

Areas for improvement:

• Start with clearer assumptions, especially around initial channel creation and setup, before jumping into message sending logic.
  
  
• Re-order some discussion — consider covering online/offline scenarios first, then deletion logic, to keep narrative clean.
  
  
• For message history fetch, discuss both volume and latency challenges more deeply — e.g., timestamp and message_id-based indexing in metadata DB to preserve order.
  
  
• For celebrity channels, consider inbox message expiry after 30 days, and fetching from DB only on user-triggered access (with optional caching layer).
  

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