Traditional autoscaling tools have underperformed in their attempts to provision Kubernetes resources while controlling costs. We’ve seen this in wide scale overprovisioning and the massive inefficiency that results. 

New resource optimization tools have emerged to fill the gap by building on the native Kubernetes autoscaling functionality to balance reliability with cost through ML and automation. Learn how these new autoscaling approaches lay the foundation for Kubernetes optimization in a hands-on workshop with experts from Amazon Web Services (AWS) and StormForge. 

You’ll be guided through the configuration and full implementation of Karpenter and StormForge Optimize Live in a sandbox environment. 

What you will learn: 

• Karpenter’s unique approach to streamlining node scaling operations 
• How Karpenter outperforms the native Kubernetes Cluster Autoscaler (CAS)
• The importance of setting workload requests and limits and how critical they are to cost optimization
• How you can efficiently rightsize requests at scale using machine learning and automation with StormForge

Why Attend:

With the ability to implement these tools effectively, you can see up to 70% efficiency, improving app performance, reliability, and cost efficiency while reducing manual toil.

Who Should Attend:

• Platform & DevOps Engineers
• SREs
• Cloud Architects
• Kubernetes Administrators