How GitLab.com Uses Long-Term Monitoring Data for Capacity Forecasting

How GitLab.com Uses Long-Term Monitoring Data for Capacity Forecasting

CNCF [Cloud Native Computing Foundation] via YouTube Direct link

System Capacity Planning

5 of 18

5 of 18

System Capacity Planning

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How GitLab.com Uses Long-Term Monitoring Data for Capacity Forecasting

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  1. 1 Intro
  2. 2 A series of Postgres saturation events..
  3. 3 Definitions: Resources
  4. 4 Saturation Events vs. Mitigation Time
  5. 5 System Capacity Planning
  6. 6 Load Testing Maximum Capacity
  7. 7 Guessing Maximum Capacity
  8. 8 Modelling Maximum Capacity
  9. 9 Estimating System Capacity is Hard
  10. 10 Resource Capacity, not System Capacity
  11. 11 Resource/Service Matrix
  12. 12 Measuring Utilization Consistently
  13. 13 Prometheus Recording Rules
  14. 14 Aggregating to Reduce Data
  15. 15 Real-time Utilization Monitoring (Detail)
  16. 16 Using Thanos for Long-Term Metrics Storage
  17. 17 First Attempt at Forecasting: Linear Regression
  18. 18 Runaway Session State Bug

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