AI-Driven Kubernetes: Mastering Reliability and Predictive Performance

ClusterGuard AI
When developers deploy applications to your OpenShift cluster, sometimes pods fail to start due to issues like missing secrets, not enough resources, or configuration errors. Currently, developers wonder why their app isn't working, and we have to manually check logs and debug the issue.
Developing ClusterGuard AI will continuously watches your cluster . When something breaks, it automatically reads the error logs, figures out what went wrong, and sends a teams message to the team explaining the problem and how to fix it

AI-Powered Kubernetes Autoscaling Using IPA (Intelligent Pod Autoscaler):
Represents a paradigm shift from reactive to predictive infrastructure management. Unlike traditional Kubernetes autoscaling mechanisms (HPA, VPA, Cluster Autoscaler) that respond to current resource utilization, IPA leverages machine learning models to forecast future demand and proactively scale applications before traffic spikes occur.

The Envoy: Ingress is Out. Gateway is In. Meet Envoy.

Nginx Ingress has been the go-to solution for getting traffic into Kubernetes clusters for years, but its time is up. The Kubernetes community is moving forward with the Gateway API, a modern and flexible way to handle traffic routing. This is a big shift for anyone running Kubernetes because Ingress has been the default choice for so long.

When it comes to Gateway API implementations, Envoy is leading the pack. It doesn’t just replace Nginx—it brings a whole new set of features like rate limiting, circuit breaking, request transformations, and better observability. In this session, we’ll look at how easy it is to swap out Nginx for Gateway API CRDs and start using Envoy’s advanced capabilities to build a smarter, more resilient traffic management setup.