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Real-time stream processing and analytics engine #31

@konard

Description

@konard

Goal: Establish streaming as our core competitive advantage

Current Status: ✅ Basic streaming working
Next Level: Advanced stream processing

Revolutionary Stream Features:

  • Stream analytics: $.stream().analyze() - real-time metrics
  • Stream transforms: $.stream().map().filter().reduce()
  • Stream splitting: $.stream().split(predicate)
  • Stream merging: $.merge(stream1, stream2)
  • Stream buffering strategies: sliding windows, batching
  • Stream backpressure handling

Real-time Analytics:

const stats = await $`tail -f access.log`
  .stream()
  .analyze({
    errorRate: line => line.includes('ERROR'),
    responseTime: line => extractTime(line),
    throughput: true
  });

Stream Processing Pipeline:

await $`docker logs -f app`
  .stream()
  .filter(line => line.includes('ERROR'))
  .map(parseErrorLog)
  .batch(10)
  .forEach(sendAlerts);

Competitive Advantage:

  • No competitor has real-time stream processing
  • Live analytics during command execution
  • Memory-efficient processing of large outputs
  • Real-time alerting and monitoring

Use Cases:

  • Log monitoring and alerting
  • CI/CD pipeline analytics
  • Real-time data processing
  • Live system monitoring

Success Metrics:

  • Stream processing examples
  • Performance vs buffered approaches
  • Real-world monitoring use cases

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