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Missed deadline = failure\nFirm Real-Time: Missed deadline = degraded quality\nSoft Real-Time: Missed deadline = performance drop\n```\n\n### WebSocket Implementation\n```javascript\n\u002F\u002F Server\nconst wss = new WebSocket.Server({ port: 8080 });\nwss.on('connection', ws => {\n  ws.on('message', message => {\n    broadcast(message);\n  });\n});\n\n\u002F\u002F Client\nconst ws = new WebSocket('ws:\u002F\u002Flocalhost:8080');\nws.onmessage = (event) => {\n  updateUI(JSON.parse(event.data));\n};\n```\n\n### Streaming Architectures\n```python\n# Apache Kafka + Spark Streaming\nfrom pyspark.streaming import StreamingContext\nssc = StreamingContext(sc, 1)\nkafka_stream = KafkaUtils.createDirectStream(\n    ssc, ['topic'], {'bootstrap.servers': 'localhost:9092'}\n)\n```\n\n### Latency Optimization\n```\nTarget latencies:\n- Hard real-time: \u003C 1ms\n- Trading systems: \u003C 10ms\n- Gaming: \u003C 50ms\n- Web updates: \u003C 100ms\n```\n\n### Event-Driven Patterns\n```javascript\n\u002F\u002F Event sourcing\nconst store = createStore((state, event) => {\n  switch (event.type) {\n    case 'USER_UPDATED':\n      return { ...state, user: event.data };\n  }\n});\n\n\u002F\u002F CQRS pattern\nCommand: writeModel.execute(command)\nQuery: readModel.query(query)\n```\n\n### Technologies\n- WebSockets, SSE\n- Apache Kafka, RabbitMQ\n- Redis Pub\u002FSub\n- gRPC streaming\n- WebRTC\n- Edge computing\n\n### Monitoring\n```python\n# Latency tracking\nfrom prometheus_client import Histogram\nrequest_latency = Histogram('request_latency_seconds')\n```\n","## What I do\n- Build real-time data pipelines\n- Implement WebSocket communication\n- Design streaming architectures\n- Handle time-sensitive processing\n- Manage event-driven systems\n- Optimize latency requirements\n\n## When to use me\nWhen building applications requiring immediate data processing, live updates, or time-critical operations.\n\n## Key Concepts\n\n### Real-Time 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