# Dynamic Resource Allocation

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## Empowering Platform Teams: Doing More with Less in the Kubernetes Era
This blog details the specific features of the Rafay Platform Version 4.0 Which Further Simplifies Kubernetes Management and Accelerates Cloud-Native Operations for Enterprises and Cloud Providers

[Read Now](https://mailto:Info@rafay.co/ai-and-cloud-native-blog/empowering-platform-teams-doing-more-with-less-in-the-kubernetes-era)

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## Dynamic Resource Allocation for GPU Allocation on Rafay's MKS (Kubernetes 1.34)
[Read Now](https://mailto:Info@rafay.co/ai-and-cloud-native-blog/dynamic-resource-allocation-for-gpu-allocation-on-rafays-mks-kubernetes-1-34)

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## Deploy Workload using DRA ResourceClaim in Kubernetes
In this 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.

[Read Now](https://mailto:Info@rafay.co/ai-and-cloud-native-blog/deploy-workload-using-dra-resourceclaim-in-kubernetes)

## Introduction to Dynamic Resource Allocation (DRA) in Kubernetes
In this post, we’ll look at how a new GA feature in Kubernetes v1.34 — Dynamic Resource Allocation (DRA) — aims to solve these problems and transform GPU scheduling in Kubernetes.

[Read Now](https://mailto:Info@rafay.co/ai-and-cloud-native-blog/introduction-to-dynamic-resource-allocation-dra-in-kubernetes)

## Rethinking GPU Allocation in Kubernetes
Kubernetes has cemented its position as the de-facto standard for orchestrating containerized workloads in the enterprise.

[Read Now](https://mailto:Info@rafay.co/ai-and-cloud-native-blog/rethinking-gpu-allocation-in-kubernetes)