How WhatsApp Handles 40 Billion Messages Per Day

WhatsApp efficiently handles 40 billion daily messages through a distributed architecture leveraging Erlang/OTP for concurrency, end-to-end encryption via the Signal Protocol, and optimized data routing. Key components include a load-balanced server fleet, message queuing with in-memory storage, and horizontal scaling to manage peak loads while maintaining low latency and high reliability.

Core Technical Concepts/Technologies

• Erlang/OTP: For high concurrency and fault tolerance
• Signal Protocol: End-to-end encryption (E2EE)
• Distributed Systems: Load balancing, sharding, and horizontal scaling
• In-Memory Storage: Ephemeral message queuing (RAM)
• XMPP (modified): Lightweight messaging protocol

Main Points

• Architecture:

  • Stateless Servers: Handle authentication/encryption; scale horizontally.
  • Message Queues: Stored in RAM for low-latency delivery; persisted only if offline.
  • Load Balancing: Distributes traffic evenly across global data centers.

• Encryption:

  • E2EE implemented via Signal Protocol, with keys exchanged during session setup.
  • Metadata minimized to enhance privacy.

• Optimizations:

  • Message Batching: Reduces overhead by grouping acknowledgments.
  • Connection Pooling: Reuses TCP connections to minimize latency.
  • Sharding: User data partitioned by unique ID for parallel processing.

• Scalability:

  • Read Replicas: Handle read-heavy workloads (e.g., group chats).
  • Automatic Failover: Erlang’s "let it crash" philosophy ensures resilience.

Technical Specifications

• Protocol: Modified XMPP (reduced overhead vs. HTTP).
• Storage: Messages deleted from servers after delivery; offline messages use SQLite.
• Code Example: Erlang’s gen_server behavior manages message queues (not shown in detail).

Key Takeaways

1. Concurrency First: Erlang/OTP enables handling millions of simultaneous connections.
2. Ephemeral Storage: RAM-based queues prioritize speed, with persistence as fallback.
3. Privacy by Design: E2EE and minimal metadata collection are core tenets.
4. Horizontal Scaling: Stateless services and sharding support massive growth.
5. Protocol Efficiency: Custom XMPP reduces bandwidth vs. traditional HTTP.

Limitations/Caveats

• Metadata Exposure: While messages are encrypted, sender/receiver and timestamps are visible.
• Offline Storage: SQLite may bottleneck under extreme load.
• Global Consistency: Trade-offs exist in multi-region replication (e.g., eventual consistency).

Areas for Exploration:

• Quantum-resistant encryption upgrades.
• Edge computing for further latency reduction.