Debug This Architecture

Failure Modes and Solutions:

1. WebSocket Server Failure:

   • Issue: If a single API server fails, all WebSocket connections to that server are lost, disrupting real-time collaboration.
   • Solution: Implement WebSocket reconnection logic on the client side, and distribute WebSocket connections across servers using a shared session store (e.g., Redis).
     • Trade-offs: Increased complexity in client reconnection logic and session management; potential latency due to network overhead from Redis.

2. PostgreSQL Write Overload:

   • Issue: Storing full HTML snapshots every 30 seconds could overwhelm PostgreSQL during high concurrency.
   • Solution: Use differential updates instead of full snapshots, storing only changes (deltas).
     • Trade-offs: More complex storage logic and conflict resolution; reduced storage costs but increased computational overhead.

3. Clock Skew in Timestamps:

   • Issue: Different client clocks might cause incorrect ordering of operations due to skew.
   • Solution: Introduce a centralized timestamping mechanism on the server side to assign consistent timestamps.
     • Trade-offs: Increased latency due to additional server processing; potential single point of failure if not properly distributed.

Race Conditions and Solutions:

1. Concurrent Edits on the Same Paragraph:

   • Issue: Two edits on the same paragraph could be processed out-of-order if relying solely on client timestamps.
   • Solution: Use Operational Transformation (OT) or Conflict-free Replicated Data Types (CRDTs) for conflict resolution.
     • Trade-offs: Complexity in implementing OT/CRDT algorithms; more robust and accurate real-time collaboration.

2. Polling Delay in Server Synchronization:

   • Issue: Servers polling every 2 seconds might miss rapid changes, causing delays in updates between servers.
   • Solution: Replace polling with a publish/subscribe model (e.g., Redis Pub/Sub) to notify servers of changes instantly.
     • Trade-offs: Requires additional infrastructure; lower latency and more efficient resource usage.

Scaling Bottlenecks and Solutions:

1. Load Balancer Round-Robin Distribution:

   • Issue: Round-robin may not distribute load evenly if sessions are sticky or some servers handle more active documents.
   • Solution: Implement sticky sessions based on document ID or user ID to ensure consistent routing.
     • Trade-offs: Uneven server load if some documents are more active; more predictable session management.

2. JWT Token Storage in localStorage:

   • Issue: localStorage is vulnerable to XSS attacks, potentially compromising JWT tokens.
   • Solution: Use HttpOnly cookies for storing JWT tokens instead of localStorage.
     • Trade-offs: Mitigates XSS risks; adds complexity with cookie management across different domains/subdomains.

3. CDN Caching of API Responses:

   • Issue: Caching API responses for 5 minutes may serve stale data for frequently updated documents.
   • Solution: Implement cache invalidation strategies (e.g., versioning documents or using short TTLs with cache purging on updates).
     • Trade-offs: Increased complexity in cache management; fresher data but potentially higher load on the backend.

By addressing these failure modes, race conditions, and bottlenecks, the architecture can become more robust, scalable, and efficient for real-time collaboration.