Observability Virtual Conference – Q&A Report from Slack
June 1, 2020
Computer Performance Modeling
June 3, 2020
The Power of Control Charts: How to Use Them, Read Them, and Build Them
In this course designed by performance and capacity expert Dr. Igor Trubin, learners will participate in lectures and hands-on activities to become familiar with:
- Machine learning based Anomaly Detection techniques
- Classical (SPC) and MASF (For system performance data) Control Charting
- Control Chart use
- Types of Control Charts
- Reading, building, and interpreting Control Charts
- Typical cases of real-world issues captured by an anomaly detection system – VMs, Mainframes, Middleware, E2E response, and more
- How to build free AWS cloud server with R and build Control Charts
- Performance anomaly (Perfomaly) detection system R implementation example (SEDS-lite—open source-based tool)
Course Syllabus
- Performance Anomaly Detection – concept
- Detecting Performance Anomalies (“Perfomalies”) by Control Charts
- Detecting Performalies by IT-Charts
- Setting up Free AWS Public Cloud EC2 Server with R-Studio to Develop and Run Simple Performaly Detection Programs
- Practice 1: Examples and Exercises (using Spreadsheet)
- Practice 2: Examples and Exercises (using R on AWS cloud)
- Final Consideration – Build your Own Performaly Detection System!
- Quiz
Fees: $0 for Members, $149 for Non-Members
Time to Complete: Appx 5 hours
Certificate/Digital Badge: Yes, a Certificate of Completion will be issued.
