 OpenShift 4 is a system of Kubernetes and here we're using some techniques from the AI world. There's this term called AIOps which stands for AI augmented operations and here we're using technologies like anomaly detection which has been proven already in the financial industry to detect anomalies in stocks being traded or in the medical world where we can detect breast cancer by just looking at a large amount of images and machines and AI can detect these anomalies quite good. Why not apply the same techniques to our own IT world to detect if an IT deployment fails or if there's some anomaly in your large infrastructure deployment? So in the end the user just wants to have his underlying platform OpenShift running at 100%. So in an ideal case we detect as Red Hat potential issues out there and by proactively looking at the data and the logs and metrics coming from those users and fixing that issue he has a better user experience.