There’s no one-size-fits-all approach to Kubernetes autoscaling. Fitting the right pieces together requires a deep understanding of the various autoscaling dimensions and the open-source projects that can plug in to meet specific use cases.

This session will explore the three key dimensions: cluster, horizontal, and vertical. We’ll start with the tools built into Kubernetes before moving onto the more advanced open-source projects—Karpenter and KEDA, which enhance flexibility and efficiency for each.

Attendees will learn:
- Strategies for cluster, horizontal and vertical autoscaling, their challenges, and solutions that improve on or replace them
- How to assess workload requirements to choose the right mix of autoscaling tailored to specific app needs
- Best practices to optimize deployments for peak performance and cost-efficiency for dynamic workloads