Debug This Architecture

Potential Failure Modes, Race Conditions, and Scaling Bottlenecks

1. WebSocket Connection Management

• Issue: When a user reconnects to a different server due to load balancer round-robin distribution, their previous WebSocket connection is lost.
  • Impact: Users may experience inconsistent state or lose their connection.
  • Solution: Implement a sticky session or session persistence mechanism at the load balancer level. Alternatively, maintain a centralized registry of client connections using Redis, allowing any server to broadcast messages to all connected clients.
  • Trade-off: Sticky sessions can lead to uneven load distribution, while a centralized registry adds an extra layer of complexity and latency.

2. Last-Write-Wins Conflict Resolution

• Issue: The current strategy relies on client clocks, which can be out of sync or manipulated.
  • Impact: Potential for incorrect conflict resolution.
  • Solution: Use a server-generated timestamp or implement Operational Transformation (OT) to handle concurrent edits more robustly.
  • Trade-off: Server-generated timestamps simplify conflict resolution but may still lead to loss of data in case of concurrent edits. OT is more complex to implement but preserves all edits.

3. Polling PostgreSQL for Changes

• Issue: Frequent polling (every 2 seconds) can lead to high database load.
  • Impact: Increased latency and potential database bottleneck.
  • Solution: Replace polling with a more efficient mechanism like PostgreSQL's LISTEN/NOTIFY or Debezium for change data capture.
  • Trade-off: LISTEN/NOTIFY requires a persistent connection from each server to PostgreSQL, while Debezium adds another component to manage.

4. Document Storage as Full HTML Snapshots

• Issue: Saving full HTML snapshots every 30 seconds can lead to storage and performance issues.
  • Impact: Large documents or frequent updates can cause storage growth and slower retrieval.
  • Solution: Implement a more efficient storage strategy, such as storing diffs or using a version control system like Git internally.
  • Trade-off: Storing diffs or using version control adds complexity in reconstructing document history and managing storage.

5. JWT Token Management

• Issue: JWT tokens are stored in localStorage and expire after 24 hours.
  • Impact: Users will be logged out after token expiry, and XSS vulnerabilities can expose tokens.
  • Solution: Implement a refresh token mechanism to obtain new JWT tokens without requiring user re-authentication. Consider using HttpOnly cookies for token storage.
  • Trade-off: Refresh tokens add complexity and require secure storage. HttpOnly cookies mitigate XSS risks but may be vulnerable to CSRF.

6. CDN Caching for API Responses

• Issue: Caching API responses for 5 minutes can serve stale data.
  • Impact: Users may see outdated information.
  • Solution: Implement cache invalidation strategies (e.g., using cache tags or versioning) to ensure that updated data is reflected promptly.
  • Trade-off: Cache invalidation adds complexity and requires careful planning to avoid cache thrashing.

7. Database Read Replicas for Read-Heavy Operations

• Issue: While read replicas help with scaling reads, write operations are still directed to the primary database.
  • Impact: Potential bottleneck on the primary database.
  • Solution: Consider sharding or using a distributed database to further scale write operations.
  • Trade-off: Sharding or distributed databases add significant operational complexity.

8. Document Partitioning by Organization ID

• Issue: Uneven distribution of documents across partitions can lead to hotspots.
  • Impact: Some partitions may become bottlenecks.
  • Solution: Implement a more granular partitioning strategy or use a consistent hashing algorithm to distribute data more evenly.
  • Trade-off: More complex partitioning strategies require careful planning and may add latency due to increased complexity in data retrieval.

9. Real-Time Sync Across Multiple Servers

• Issue: The current architecture relies on each server polling PostgreSQL, which can lead to delays in propagating changes across servers.
  • Impact: Users connected to different servers may experience delays in seeing each other's updates.
  • Solution: Implement a pub/sub messaging system (e.g., Redis Pub/Sub, RabbitMQ) for broadcasting changes across servers in real-time.
  • Trade-off: Adds another component to manage and introduces potential latency due to message propagation.

Summary of Proposed Solutions and Trade-Offs

1. Centralized WebSocket Connection Registry: Simplifies broadcasting but adds complexity.
2. Server-Generated Timestamps or Operational Transformation: Improves conflict resolution at the cost of complexity.
3. LISTEN/NOTIFY or Debezium: Reduces database load but introduces new dependencies.
4. Diff Storage or Version Control: Optimizes storage but complicates document reconstruction.
5. Refresh Tokens and Secure Storage: Enhances security but adds complexity.
6. Cache Invalidation Strategies: Ensures data freshness but requires careful planning.
7. Sharding or Distributed Database: Scales write operations but is operationally complex.
8. Granular Partitioning or Consistent Hashing: Balances data distribution but may add retrieval latency.
9. Pub/Sub Messaging System: Improves real-time sync across servers but introduces new components and potential latency.

Each proposed solution comes with its trade-offs, requiring careful consideration of the specific needs and constraints of the collaborative document editor.