Live Panel Webinar

5 Kubernetes Autoscaling Use Cases Deconstructed by AWS and StormForge

Featuring Rodrigo Bersa, Specialist Solutions Architect for Containers and AppMod, Amazon Web Services

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Meet the Speakers

A headshot photo of Rodrigo Bersa

Rodrigo Bersa

Specialist Solutions Architect for Containers and AppMod, Amazon Web Services

Rodrigo Bersa is a Specialist Solutions Architect for Containers and AppMod, with a focus on Security and Infrastructure-as-Code automation. In this role, Rodrigo aims to help customers achieve their business goals by leveraging best practices on AWS Containers Services, such as Amazon EKS, Amazon ECS, and Red Hat OpenShift on AWS (ROSA) during their Cloud Journey, when building new environments, or migrating existing technologies.

John Platt

John Platt

Chief Technology Officer

John Platt has a Ph.D. in Applied Mathematics and has spent most of his career building Machine Learning-powered products. Throughout his career, he constantly found himself using machine learning to solve infrastructure-related problems. His desire to automate mundane tasks combined with a desire to solve hard problems with mathematics is what led him to his current role as CTO of StormForge, which focuses on Kubernetes resource optimization.

July 31, 12pm ET | 9am PT

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. 

Get detailed guidance through this highly technical approach with experts from Amazon Web Services and StormForge. They’ll provide a short overview of the three key autoscaling dimensions (cluster, horizontal, and vertical) before diving into how each can be leveraged to navigate the specs associated with different use cases. 

    You’ll learn:

    • Strategies for each dimension, their challenges, and how advanced open-source projects like Karpenter and KEDA can 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