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Dynamic Resource Allocation for GPU Allocation on Rafay's MKS (Kubernetes 1.34)

This blog demonstrates how to leverage Dynamic Resource Allocation (DRA) for efficient GPU allocation using Multi-Instance GPU (MIG) strategy on Rafay's Managed Kubernetes Service (MKS) running Kubernetes 1.34.

In our previous blog series, we covered various aspects of Dynamic Resource Allocation (DRA) in Kubernetes:

DRA is GA in Kubernetes 1.34

With Kubernetes 1.34, Dynamic Resource Allocation (DRA) is Generally Available (GA) and enabled by default on MKS clusters. This means you can immediately start using DRA features without additional configuration.

Prerequisites

Before we begin, ensure you have:

Deploy Workload using DRA ResourceClaim in Kubernetes

In the first blog in the DRA series, we introduced the concept of Dynamic Resource Allocation (DRA) that recently went GA in Kubernetes v1.34 which was released end of August 2025.

In the second blog, we installed a Kuberneres v1.34 cluster and deployed an example DRA driver on it with "simulated GPUs". In this blog, we’ll will deploy a few workloads on the DRA enabled Kubernetes cluster to understand how "Resource Claim" and "ResourceClaimTemplates" work.

Info

We have optimized the steps for users to experience this on their laptops in less than 5 minutes. The steps in this blog are optimized for macOS users.

Enable Dynamic Resource Allocation (DRA) in Kubernetes

In the previous blog, we introduced the concept of Dynamic Resource Allocation (DRA) that just went GA in Kubernetes v1.34 which was released in August 2025.

In this blog post, we’ll will configure DRA on a Kubernetes 1.34 cluster.

Info

We have optimized the steps for users to experience this on their macOS or Windows laptops in less than 15 minutes. The steps in this blog are optimized for macOS users.

Get Started with BioContainers using Rafay

In this step-by-step guide, the Bioinformatics data scientist will use Rafay's end user portal to launch a well resourced remote VM and run a series of BioContainers with Docker.

Get Started with Auto Mode for Amazon EKS with Rafay

This is Part 3 in our series on Amazon EKS Auto Mode. In the previous posts, we explored:

  1. Part 1: An Introduction: Learn the core concepts and benefits of EKS Auto Mode.
  2. Part 2: Considerations: Understand the key considerations before Configuring EKS Auto Mode.

In this post, we will dive into the steps required to build and manage an Amazon EKS cluster with Auto Mode template using the Rafay Platform. This exercise is specifically well suited for platform teams interested in providing their end users with a controlled self-service experience with centralized governance.