--- title: Deploying GPU workload with Dynamic Resource Allocation description: Kubernetes 1.34 made Dynamic Resource Allocation (DRA) generally available, replacing the blunt `nvidia.com/gpu: 1` device plugin model with structured,... canonical: https://daily.dev/posts/deploying-gpu-workload-with-dynamic-resource-allocation-zjseztv9n twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Deploying GPU workload with Dynamic Resource Allocation | daily.dev og:description: Kubernetes 1.34 made Dynamic Resource Allocation (DRA) generally available, replacing the blunt `nvidia.com/gpu: 1` device plugin model with structured,... og:url: https://daily.dev/posts/deploying-gpu-workload-with-dynamic-resource-allocation-zjseztv9n og:image: https://api.daily.dev/og/posts/zJSEzTv9n.png og:image:alt: Deploying GPU workload with Dynamic Resource Allocation og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Deploying GPU workload with Dynamic Resource Allocation **[Cast AI](https://daily.dev/sources/castai)** · 10 min read · 0 upvotes · 0 comments ## Summary Kubernetes 1.34 made Dynamic Resource Allocation (DRA) generally available, replacing the blunt `nvidia.com/gpu: 1` device plugin model with structured, attribute-based GPU requests. DRA introduces four core objects: ResourceSlice (describes available hardware), DeviceClass (groups devices), ResourceClaimTemplate (per-pod GPU requirements), and ResourceClaim (shared across pods). A practical walkthrough shows deploying a CUDA Mandelbrot fractal renderer with precise GPU requirements (Ampere architecture, 20+ GB memory), then scaling it using three GPU sharing strategies: time-slicing (sequential access), MPS (concurrent CUDA processes with configurable thread percentages), and MIG (hardware-level partitioning into up to seven isolated 1g.5gb slices on an A100). CAST AI's autoscaler integrates natively with DRA, reading ResourceClaims to provision the cheapest matching instance type automatically, including setting up MIG partitions. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Understanding dynamic resource allocation in Kubernetes](https://daily.dev/posts/understanding-dynamic-resource-allocation-in-kubernetes-qr7yqzkhw) · CNCF · 0 upvotes · 0 comments --- Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#nvidia](https://daily.dev/tags/nvidia), [#gpu](https://daily.dev/tags/gpu) [View this post on daily.dev](https://daily.dev/posts/deploying-gpu-workload-with-dynamic-resource-allocation-zjseztv9n) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Deploying GPU workload with Dynamic Resource Allocation","url":"https://daily.dev/posts/deploying-gpu-workload-with-dynamic-resource-allocation-zjseztv9n","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/deploying-gpu-workload-with-dynamic-resource-allocation-zjseztv9n"},"datePublished":"2026-04-03T13:05:42.564Z","dateModified":"2026-04-03T13:06:09.479Z","description":"Kubernetes 1.34 made Dynamic Resource Allocation (DRA) generally available, replacing the blunt `nvidia.com/gpu: 1` device plugin model with structured,...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/342dd60a05971171af8bf2e0149285b7?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/342dd60a05971171af8bf2e0149285b7?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Cast AI","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Cast AI","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/e5868702aaf84d8293e56794e2c6629c","url":"https://daily.dev/sources/castai"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/deploying-gpu-workload-with-dynamic-resource-allocation-zjseztv9n","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"kubernetes,nvidia,gpu","timeRequired":"PT10M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Cast AI","item":"https://daily.dev/sources/castai"},{"@type":"ListItem","position":3,"name":"Deploying GPU workload with Dynamic Resource Allocation"}]} ```