After trying several Prometheus exporters, I think I’m ready to fight the final boss: Monitoring a Windows cluster with Prometheus. I need a dashboard where I can monitor all the Windows machines in a single pane of glass. Let’s do it.

In this article, you’ll learn, through an example, how to configure Keda to deploy a Kubernetes Horizontal Pod Autoscaler (HPA) that uses Sysdig Monitor metrics. Keda is an open source project that allows using Prometheus queries to scale Kubernetes pods. In Trigger a Kubernetes HPA with Prometheus metrics, you learned how to install and configure Keda to create a Kubernetes HPA triggered by a standard Prometheus query.

In this article, you’ll learn how to configure Keda to deploy a Kubernetes HPA that uses Prometheus metrics. The Kubernetes Horizontal Pod Autoscaler can scale pods based on the usage of resources, such as CPU and memory. This is useful in many scenarios, but there are other use cases where more advanced metrics are needed – like the waiting connections in a web server or the latency in an API.