Design Messaging App System

WhatsApp-like messaging system with queues, storage, and notifications.

Functional requirements

  • Users can send one-to-one and group text messages in real time.
  • Users can send images, videos, and documents up to 100 MB.
  • Messages must be delivered in order and exactly once per recipient.
  • Users can see read receipts and delivery status (sent / delivered / read).
  • Group chats support up to 1,000 members with fan-out delivery.
  • Users receive push notifications when the app is in the background.
  • Messages are end-to-end encrypted by default.
  • Users can delete messages for themselves or for all participants within a time window.
  • Offline users receive missed messages upon reconnection.
  • Users can share their real-time location for a configurable duration.

Non-functional requirements

  • Availability: 99.99% uptime; messages must not be lost even during partial outages.
  • Latency: message delivery end-to-end under 200 ms at the 95th percentile for online users.
  • Scalability: support 500 million daily active users and 100 billion messages per day.
  • Durability: messages persisted for 30 days; media stored for 90 days.
  • Throughput: ingest up to 1 million messages per second at peak.
  • Consistency: eventual consistency acceptable for delivery status; strong consistency for message order within a thread.
  • Security: end-to-end encryption; no server-side plaintext storage of message content.
  • Resumability: failed media uploads can resume from the last committed chunk.
  • Geo-distribution: data centres in each major region to comply with data residency laws.
  • Observability: real-time lag metrics per queue, alerting within 60 seconds of anomaly.

How the design evolves

Stage 1: Monolith MVP

Start with a single chat server and message store for core messaging flow.

What was missing: No separation of concerns, no redundancy, no async buffering, no rate limiting, no observability.

Why that's risky: Single point of failure, no protection from spikes, no monitoring, all traffic synchronous.

What gets added: Nothing yet (MVP).

Trade-offs: Simple, but not production ready.

Stage 2: Add Edge, Gateway, and Rate Limiting

Introduce edge, gateway, and rate limiting for security and performance.

What was missing: No edge security, no rate limiting, no separation of gateway and chat logic.

Why that's risky: Vulnerable to DDoS, no traffic shaping, gateway logic not isolated.

What gets added: Edge, gateway, and rate limiter.

Trade-offs: Slightly more complex.

Stage 3: Horizontal Scaling and Load Balancing

Add load balancer and multiple chat servers for scale and redundancy.

What was missing: No redundancy, no horizontal scaling, single chat server bottleneck.

Why that's risky: Single point of failure, cannot handle spikes.

What gets added: Load balancer, multiple chat servers.

Trade-offs: More complex deployment.

Stage 4: Async Queue, Worker Pool, and Fan-out

Add async queue and worker pool for message fan-out and delivery.

What was missing: No async buffering, no worker pool, all delivery synchronous.

Why that's risky: Spikes can overload chat servers, slow delivery blocks senders.

What gets added: Async queue, worker pool, idempotency.

Trade-offs: More moving parts, eventual consistency for delivery.

Stage 5: Media Storage, Notifications, and Observability

Add media store, notification service, and monitoring/logging.

What was missing: No media storage, no notification service, no observability, no circuit breaker.

Why that's risky: Media and notifications can overload chat servers, no alerting, notification failures can cascade.

What gets added: Media store, notification service, monitoring/logging, circuit breaker.

Trade-offs: More moving parts, more operational complexity.

Frequently asked questions

How do you ensure ordering of messages?

Use per-conversation partitions and sequence numbers in the message store.

How do you handle write amplification in message storage?

Use append-only logs and periodic compaction to reduce write amplification.

Why place a gateway in front of chat servers?

The gateway handles authentication, rate limiting, and connection routing.

What does the delivery worker enable?

Workers fan out messages asynchronously and allow retries without blocking chat servers.

Why split media storage from message storage?

Media has different access patterns and benefits from dedicated storage and CDN caching.

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User
CDN
Load Balancer
Server
Cache
Database
Blob Storage
Search Index
Queue
Worker
Rate Limiter
Service
API Gateway
Reverse Proxy
WebSocket Server
Third-party API

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Notes
Use clear names so your design intent is easy to understand.
Good
Name by business meaning
"Order API", "Restaurant Service"
Avoid
Generic names = zero signal
"Server 1", "API", "Queue"
A short description for each component makes feedback much better.
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  • APIs & services
  • Databases & storage
  • Traffic flow & scale

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Here’s a simple request flow that follows the expected layer order.

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