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Friday, June 16 • 3:00pm - 3:35pm
Optimize Long Test Runtimes Using Open AIOps

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In this era of automation, continuous integration and delivery(CI/CD) with code hosting platforms has played a vital role in software development workflows. A huge number of contributions are made to Open Source projects and are subjected to automated tests/builds before being merged. However, some tests run for longer durations than expected and are often painful as they block the CI/CD process.
In this session, we will introduce an open AIOps tool called AI4CI that consists of a set of Jupyter notebooks automated using Kubeflow pipelines and collects data from K8s CI/CD platforms, analyze and visualize the KPI metrics, develop and deploy ML models using Openshift.
By analyzing the test failure times, we aim to predict an Optimal Stopping Point for a test after which the test is most likely going to fail and better support in managing the development resources efficiently. The attendees will learn about how the Optimal Stopping Point model can resolve the bottlenecks in CI/CD systems.

avatar for Aakanksha Duggal

Aakanksha Duggal

Senior Data Scientist, Red Hat Inc
Aakanksha Duggal is a Senior Data Scientist in the Emerging Technologies Group at Red Hat. She is a part of the Data Science team and works on developing open source software that uses AI and machine learning applications to solve engineering problems.
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. Hema is a staunch... Read More →

Friday June 16, 2023 3:00pm - 3:35pm CEST
E104 | Talks