Boost AI efficiency with GPU autoscaling on OpenShift

This blog post discusses the importance of autoscaling in Red Hat OpenShift to enhance responsiveness and efficiency, particularly for GPU-accelerated applications. It covers various autoscaling mechanisms, how to set up a custom metrics autoscaler using KEDA and Prometheus, and provides detailed instructions for configuration and testing. Key components include horizontal and vertical pod autoscaling, cluster autoscaling, and the implementation of custom metrics based on workload demands.