Use Cases, Patterns, and Recommendations

At this point, you’ve learned about the mechanics of KEDA and Karpenter – how they work, how to configure them, and how to troubleshoot them. But knowing how the tools work is different from knowing how and when you can actually use them in your environment. This final part is about connecting all of that to common use cases and practical patterns.

We’ll start by looking at common use cases where KEDA and Karpenter are a great fit: web applications that need to handle variable traffic, batch jobs that run based on events, GPU workloads where compute costs can get out of hand quickly, and how to cost-optimize your cluster further with proper rightsizing and compute flexibility. For each one, you’ll learn about the specific considerations and best practices that make autoscaling work reliably.

Then we’ll cover two patterns that come up constantly in production. The first is about shutting down non-production...