~/talk

Autoscaling Containers... with Math

slides:none on file

Custom autoscaler built and tested against GKE using the Heapster API to read CPU and Kubernetes replication controller API to set replicas, sampling every 5s. Models fit with an R script (example: CPU_next = 0.94·CPU_current − 0.2·instances) and a simple proportional/PID approach controls scale decisions. Demo drives 20k→40k qps, observes CPU hitting ~400% then replicas increase and settle; default HPA behaves roughly as a proportional controller. Code and benchmarks live at Espinoza/control-theory on GitHub.

AI-written summary · about

  1. 0:00Introduction to speaker
  2. 1:02Conventional system operations
  3. 3:01Introduction to control theory
  4. 4:44History of automation
  5. 6:41Architectural components
  6. 8:32Linear system modeling
  7. 10:46Evaluating controller stability
  8. 13:05System responsiveness
  9. 14:44Proportional controllers
  10. 16:53Integral and derivative terms
  11. 18:43Handling non-linear behavior
  12. 19:35Advanced control applications
  13. 21:45Resources for further learning
  14. 22:20Scaling demonstration
  15. 26:08Analyzing scaling results
  16. 28:15Scaling down and delays
  17. 31:11Q&A and conclusion
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