KEDA, the Kubernetes Event-Driven Autoscaler, does exactly what its name suggests: it enables the scaling of a Kubernetes cluster in relation to the number of events that must be processed. In our experience, using leading indicators like queue depth — rather than trailing indicators like CPU usage — is preferable. KEDA supports different event sources and comes with a catalog of more than 50 scalers for various cloud platforms, databases, messaging systems, telemetry systems, CI/CD systems and more. Our teams report that the ease with which KEDA can be integrated has allowed them to keep functionality in microservices in Kubernetes where they otherwise might have considered porting some of the event handling code to serverless functions.