Introduction
Example scenario
You work as a DevOps engineer for a growing video-editing company that provides a cloud-based video rendering service. Client application usage peaks at various times during any given 24-hour period. Due to this increasing and decreasing demand, the company needs to be able to scale its application accordingly to provide a better experience to its customers. Because the application is event-driven and receives a large number of events at various times, CPU and memory-based metrics aren't fully representative of the load on the system. You've been tasked with finding a scaling solution that will help the company achieve its scaling needs.
After experimenting with various options, you've determined that using Azure Kubernetes Services (AKS) and Kubernetes Event-driven Autoscaling (KEDA) fulfills all the requirements to scale for peak and off-peak usage.
Note
All exercises use the Azure Cloud Shell, which already has all the needed tooling installed. If you prefer to run the examples locally, you need to install Azure CLI and Kubectl.