When the CI/CD pipeline turns red, many DevOps teams have to start digging into the problem: searching through log files, identifying error patterns, narrowing down causes, and creating tickets. This process takes time, doesn’t scale, and ties up developer resources that are urgently needed elsewhere. The larger the project, the more pressing the problem becomes. After all, more commits mean more pipeline runs and more logs.
In this 20-minute webinar, Yu Zou, software developer at sepp.med, demonstrates how he has automated this very process with AI support. The “Pipeline Oracle” tool retrieves pipeline logs via API, analyzes and categorizes errors with LLM support, generates solution suggestions with confidence scores, and automatically creates tickets. Pipeline Oracle is not a theoretical concept. It was developed in just three days during an AI hackathon and uses a real-world example to demonstrate how the journey from an AI experiment to a productive workflow can look in practice.
DevOps leads and CI/CD managers, engineering leads, CTOs and development managers, test managers and QA leads, as well as senior developers
Yu Zou, software developer at sepp.med and trainer at the sepp.med Academy
Date: May 20, 2026, 11:00 AMDuration: 20 minutes + Q&A
Register now and take away concrete strategies on how AI automation measurably accelerates your pipeline analysis!
Yu Zou graduated from the University of Erlangen in 2019 with a masters degree in mechanical engineering with a focus on quality assurance and has been working at sepp.med since 2020. As a software developer, product quality is particularly important to him. He not only loves to implement the requirements, but also to discover the bugs through manual and automated tests in order to be able to fix them. With his academic background as an automation engineer, he also has a strong interest in automation for security testing of cyber-physical systems.
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