Automatically Detect the Top Performance & Scalability Issues in Distributed Architectures

Automatically Detect the Top Performance & Scalability Issues in Distributed Architectures

USENIX via YouTube Direct link

Inspired by Dynatrace's internal „Performance Signature as Code

11 of 16

11 of 16

Inspired by Dynatrace's internal „Performance Signature as Code

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Automatically Detect the Top Performance & Scalability Issues in Distributed Architectures

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  1. 1 Intro
  2. 2 Distributed Trace Example from StepStone (AWS Summit Berlin 2019)
  3. 3 In distributed architectures we need to answer: Who is depending on me? What is the risk of change?
  4. 4 N+1 Call Pattern across distributed "Product Service"
  5. 5 LANDBAY
  6. 6 Cascading N+1 Query Pattern: This is a single End-2-End Distributed Trace
  7. 7 Payload Flood: "Doc Creation" sequential across distributed services
  8. 8 Refactor: Only send relevant data to specialized services
  9. 9 Keptn from 10000ft: Declarative Workflows + Event-Triggered Actions
  10. 10 Root Cause: Lengthy manual approval in existing delivery pipelines
  11. 11 Inspired by Dynatrace's internal „Performance Signature as Code
  12. 12 SLI/SLO-based evaluation implementation in Keptn
  13. 13 Solution: Automate Approval through SLI/SLO-based Quality Gates
  14. 14 Demo: Automated SLI/SLO Validation based on Dynatrace Dashboards
  15. 15 Keptn-Closed-Loop Remediation with Keptn 0.7
  16. 16 Automate Distributed Problem Detection & Remediation

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