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# Description
Expert in real-time communication systems, including WebSockets, Socket.IO, SSE, and WebRTC.
# SKILL.md
name: websocket-engineer
description: Expert in real-time communication systems, including WebSockets, Socket.IO, SSE, and WebRTC.
WebSocket & Real-Time Engineer
Purpose
Provides real-time communication expertise specializing in WebSocket architecture, Socket.IO, and event-driven systems. Builds low-latency, bidirectional communication systems scaling to millions of concurrent connections.
When to Use
- Building chat apps, live dashboards, or multiplayer games
- Scaling WebSocket servers horizontally (Redis Adapter)
- Implementing "Server-Sent Events" (SSE) for one-way updates
- Troubleshooting connection drops, heartbeat failures, or CORS issues
- Designing stateful connection architectures
- Migrating from polling to push technology
Examples
Example 1: Real-Time Chat Application
Scenario: Building a scalable chat platform for enterprise use.
Implementation:
1. Designed WebSocket architecture with Socket.IO
2. Implemented Redis Adapter for horizontal scaling
3. Created room-based message routing
4. Added message persistence and history
5. Implemented presence system (online/offline)
Results:
- Supports 100,000+ concurrent connections
- 50ms average message delivery
- 99.99% connection stability
- Seamless horizontal scaling
Example 2: Live Dashboard System
Scenario: Real-time analytics dashboard with sub-second updates.
Implementation:
1. Implemented WebSocket server with low latency
2. Created efficient message batching strategy
3. Added Redis pub/sub for multi-server support
4. Implemented client-side update coalescing
5. Added compression for large payloads
Results:
- Dashboard updates in under 100ms
- Handles 10,000 concurrent dashboard views
- 80% reduction in server load vs polling
- Zero data loss during reconnections
Example 3: Multiplayer Game Backend
Scenario: Low-latency multiplayer game server.
Implementation:
1. Implemented WebSocket server with binary protocols
2. Created authoritative server architecture
3. Added client-side prediction and reconciliation
4. Implemented lag compensation algorithms
5. Set up server-side physics and collision detection
Results:
- 30ms end-to-end latency
- Supports 1000 concurrent players per server
- Smooth gameplay despite network variations
- Cheat-resistant server authority
Best Practices
Connection Management
- Heartbeats: Implement ping/pong for connection health
- Reconnection: Automatic reconnection with backoff
- State Cleanup: Proper cleanup on disconnect
- Connection Limits: Prevent resource exhaustion
Scaling
- Horizontal Scaling: Use Redis Adapter for multi-server
- Sticky Sessions: Proper load balancer configuration
- Message Routing: Efficient routing for broadcast/unicast
- Rate Limiting: Prevent abuse and overload
Performance
- Message Batching: Batch messages where appropriate
- Compression: Compress messages (permessage-deflate)
- Binary Protocols: Use binary for performance-critical data
- Connection Pooling: Efficient client connection reuse
Security
- Authentication: Validate on handshake
- TLS: Always use WSS
- Input Validation: Validate all incoming messages
- Rate Limiting: Limit connection/message rates
---
2. Decision Framework
Protocol Selection
What is the communication pattern?
β
ββ **Bi-directional (Chat/Game)**
β ββ Low Latency needed? β **WebSockets (Raw)**
β ββ Fallbacks/Auto-reconnect needed? β **Socket.IO**
β ββ P2P Video/Audio? β **WebRTC**
β
ββ **One-way (Server β Client)**
β ββ Stock Ticker / Notifications? β **Server-Sent Events (SSE)**
β ββ Large File Download? β **HTTP Stream**
β
ββ **High Frequency (IoT)**
ββ Constrained device? β **MQTT** (over TCP/WS)
Scaling Strategy
| Scale | Architecture | Backend |
|---|---|---|
| < 10k Users | Monolith Node.js | Single Instance |
| 10k - 100k | Clustering | Node.js Cluster + Redis Adapter |
| 100k - 1M | Microservices | Go/Elixir/Rust + NATS/Kafka |
| Global | Edge | Cloudflare Workers / PubNub / Pusher |
Load Balancer Config
- Sticky Sessions: REQUIRED for Socket.IO (handshake phase).
- Timeouts: Increase idle timeouts (e.g., 60s+).
- Headers:
Upgrade: websocket,Connection: Upgrade.
Red Flags β Escalate to security-engineer:
- Accepting connections from any Origin (*) with credentials
- No Rate Limiting on connection requests (DoS risk)
- Sending JWTs in URL query params (Logged in proxy logs) - Use Cookie or Initial Message instead
---
3. Core Workflows
Workflow 1: Scalable Socket.IO Server (Node.js)
Goal: Chat server capable of scaling across multiple cores/instances.
Steps:
-
Install Dependencies
bash npm install socket.io redis @socket.io/redis-adapter -
Implementation (
server.js)
```javascript
const { Server } = require("socket.io");
const { createClient } = require("redis");
const { createAdapter } = require("@socket.io/redis-adapter");const pubClient = createClient({ url: "redis://localhost:6379" });
const subClient = pubClient.duplicate();Promise.all([pubClient.connect(), subClient.connect()]).then(() => {
const io = new Server(3000, {
adapter: createAdapter(pubClient, subClient),
cors: {
origin: "https://myapp.com",
methods: ["GET", "POST"]
}
});io.on("connection", (socket) => {
// User joins a room (e.g., "chat-123")
socket.on("join", (room) => {
socket.join(room);
});// Send message to room (propagates via Redis to all nodes) socket.on("message", (data) => { io.to(data.room).emit("chat", data.text); });});
});
```
---
Workflow 3: Production Tuning (Linux)
Goal: Handle 50k concurrent connections on a single server.
Steps:
-
File Descriptors
- Increase limit:
ulimit -n 65535. - Edit
/etc/security/limits.conf.
- Increase limit:
-
Ephemeral Ports
- Increase range:
sysctl -w net.ipv4.ip_local_port_range="1024 65535".
- Increase range:
-
Memory Optimization
- Use
ws(lighter) instead of Socket.IO if features not needed. - Disable "Per-Message Deflate" (Compression) if CPU is high.
- Use
---
5. Anti-Patterns & Gotchas
β Anti-Pattern 1: Stateful Monolith
What it looks like:
- Storing users = [] array in Node.js memory.
Why it fails:
- When you scale to 2 servers, User A on Server 1 cannot talk to User B on Server 2.
- Memory leaks crash the process.
Correct approach:
- Use Redis as the state store (Adapter).
- Stateless servers, Stateful backend (Redis).
β Anti-Pattern 2: The "Thundering Herd"
What it looks like:
- Server restarts. 100,000 clients reconnect instantly.
- Server crashes again due to CPU spike.
Why it fails:
- Connection handshakes are expensive (TLS + Auth).
Correct approach:
- Randomized Jitter: Clients wait random(0, 10s) before reconnecting.
- Exponential Backoff: Wait 1s, then 2s, then 4s...
β Anti-Pattern 3: Blocking the Event Loop
What it looks like:
- socket.on('message', () => { heavyCalculation(); })
Why it fails:
- Node.js is single-threaded. One heavy task blocks all 10,000 connections.
Correct approach:
- Offload work to a Worker Thread or Message Queue (RabbitMQ/Bull).
---
7. Quality Checklist
Scalability:
- [ ] Adapter: Redis/NATS adapter configured for multi-node.
- [ ] Load Balancer: Sticky sessions enabled (if using polling fallback).
- [ ] OS Limits: File descriptors limit increased.
Resilience:
- [ ] Reconnection: Exponential backoff + Jitter implemented.
- [ ] Heartbeat: Ping/Pong interval configured (< LB timeout).
- [ ] Fallback: Socket.IO fallbacks (HTTP Long Polling) enabled/tested.
Security:
- [ ] WSS: TLS enabled (Secure WebSockets).
- [ ] Auth: Handshake validates credentials properly.
- [ ] Rate Limit: Connection rate limiting active.
Anti-Patterns
Connection Management Anti-Patterns
- No Heartbeats: Not detecting dead connections - implement ping/pong
- Memory Leaks: Not cleaning up closed connections - implement proper cleanup
- Infinite Reconnects: Reloop without backoff - implement exponential backoff
- Sticky Sessions Required: Not designing for stateless - use Redis for state
Scaling Anti-Patterns
- Single Server: Not scaling beyond one instance - use Redis adapter
- No Load Balancing: Direct connections to servers - use proper load balancer
- Broadcast Storm: Sending to all connections blindly - target specific connections
- Connection Saturation: Too many connections per server - scale horizontally
Performance Anti-Patterns
- Message Bloat: Large unstructured messages - use efficient message formats
- No Throttling: Unlimited send rates - implement rate limiting
- Blocking Operations: Synchronous processing - use async processing
- No Monitoring: Operating blind - implement connection metrics
Security Anti-Patterns
- No TLS: Using unencrypted connections - always use WSS
- Weak Auth: Simple token validation - implement proper authentication
- No Rate Limits: Vulnerable to abuse - implement connection/message limits
- CORS Exposed: Open cross-origin access - configure proper CORS
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