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
Hema Veeradhi is a Senior Data Scientist working in the Emerging Technology team part of the office of the CTO at Red Hat. Her current work focuses on solving business problems using open AI and ML solutions.
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 - C228Faculty of Information Technology, Brno University of Technology Božetěchova 1 / 2 612 00 BRNO Czech Republic
