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Introduction
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Classroom Contents
Scalable Anomaly Detection - With Zero Machine Learning
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- 1 Introduction
- 2 Netflixs Microservices
- 3 Time Series Database
- 4 Alerts Only for Zul
- 5 Dynamic Thresholds
- 6 Adaptive Thresholds
- 7 Anomaly Detector Raju
- 8 Results
- 9 No Machine Learning
- 10 How We Built It
- 11 Impact Graph
- 12 Context
- 13 Accuracy
- 14 Operational Burden
- 15 Realtime alerting
- 16 Realtime events
- 17 Mantis
- 18 How it works
- 19 Querying
- 20 Stream Processing
- 21 Aggregate
- 22 Job Chain
- 23 Requirements
- 24 Median estimation
- 25 Mad
- 26 Raju
- 27 Simple
- 28 Recovery Detection
- 29 Recovery Algorithm
- 30 What Raju Looks Like
- 31 Permutations
- 32 Data Visualization
- 33 Impact Assessment
- 34 Timeline of Events
- 35 What is API
- 36 Another needle in a haystack
- 37 Example
- 38 Gold Standard KPI
- 39 Spinnaker Events
- 40 Emailing the culprits
- 41 Benefits
- 42 Conclusion
