~/talk

Autothrottle: A Practical Bi-Level Approach to Resource Management for SLO-Targeted...

name:Zibo Wang
links:none on file
name:Pinghe Li
links:none on file
links:none on file
name:Feng Wu
links:none on file
links:none on file
slides:none on file

A bi-level framework called Autothrottle pairs lightweight per-service controllers (Captain) with an application-level learner (Tower) that outputs throttle ratio targets. Tower runs a contextual bandit online, Captain uses closed-loop control every second, and the system maps throttle ratio to end-to-end latency. Evaluated on three microservice apps with production traces and a 21-day replay, it reduces CPU use up to 26.21% versus the best baseline (and up to 93.84% versus all baselines), avoids many k8s violations (71 of 480 hours), and runs with low overhead.

AI-written summary · about

  1. 0:00The microservice challenge
  2. 3:38Limitations of current methods
  3. 6:39The auto-throttle framework
  4. 8:11Using throttle ratios
  5. 10:44Controller implementations
  6. 12:54Evaluation and results
  7. 16:18Conclusion
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