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Friday, January 24 • 4:30pm - 5:55pm
I See Metrics: Anomaly Detection on OpenShift

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Monitoring your applications with Prometheus and figuring out relevant metrics to alert on can be a tough task. What if you had an automated AI based technique to help you identify these metrics? Introducing the Prometheus Anomaly Detection framework! In this workshop we will walk through all the tools required to setup your own anomaly detection framework for prometheus metrics. We will see how to:
1. Setup a sample application to generate metrics
2. Configure Prometheus to collect the metrics
3. Use a python library to get metrics into a suitable format
4. Train machine learning models to perform time series forecasting
5. Use Grafana to create insightful dashboards and setup alerts

avatar for Hema Veeradhi

Hema Veeradhi

Senior Data Scientist, Red Hat
Hema Veeradhi is a Senior Data Scientist working in the Emerging Technologies team part of the office of the CTO at Red Hat. Her work primarily focuses on implementing innovative open AI and machine learning solutions to help solve business and engineering problems.

Anand Sanmukhani

Software Engineer, Red Hat AICoE
Software Engineer, working with the AIOPs team at Red Hat. Usually spend my days struggling with yaml errors in kubernetes and openshift deployments.

Friday January 24, 2020 4:30pm - 5:55pm CET
Workshop Room C - C228 Faculty of Information Technology, Brno University of Technology Božetěchova 1 / 2 612 00 BRNO Czech Republic