Explore an innovative approach to optimizing long test runtimes in CI/CD pipelines using open AIOps tools. Dive into the world of AI4CI, a set of Jupyter notebooks automated with Kubeflow pipelines, designed to collect data from Kubernetes CI/CD platforms, analyze KPI metrics, and develop ML models on OpenShift. Learn how the Optimal Stopping Point model can predict when a test is likely to fail, helping to efficiently manage development resources and resolve bottlenecks in CI/CD systems. Discover the potential of this cutting-edge solution presented by speakers Hema Veeradhi and Aakanksha Duggal at DevConf.CZ 2023, addressing the challenges of prolonged test durations in automated software development workflows.