Real-time stream processing and analytics engine

[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