Developing AI tools for developers by leveraging the data made openly available by OpenShift and Kubernetes CI platforms.
AIOps is a critical component of supporting any Open Hybrid Cloud infrastructure. As the systems we operate become larger and more complex, intelligent monitoring tools and response agents will become a necessity. In an effort to accelerate the development, access and reliability of these intelligent operations, we aim to provide access to an open community with open operations data and an open infrastructure for data scientists and DevOps engineers to collaborate.
One major component of the software development and operations workflow is Continuous Integration (CI), which involves running automated builds and tests of software before it is merged into a production code base. For example, if you are developing a container orchestration platform like Kubernetes or OpenShift, these are huge code bases with large builds and many tests that will produce a lot of data that can be difficult to parse if you are trying to figure out why a build is failing or why a certain set of tests aren’t passing.
OpenShift, Kubernetes and a few other platforms have made their CI data public. This is real world multimodal production operations data, a rarity for public data sets today. This presents a great starting point and a first initial area of investigation for the AIOps community to tackle. Our aim is to cultivate open source AIOps projects by developing, integrating and operating AI tools for CI by leveraging the open data that has been made available by OpenShift, Kubernetes and others.