--- title: Multi-Cloud and Cross-Region GPU Capacity for Kubernetes AI description: GPU capacity is simultaneously scarce and underutilized — average GPU utilization in production Kubernetes clusters sits at just 5%, yet half of GPU cloud... canonical: https://daily.dev/posts/multi-cloud-and-cross-region-gpu-capacity-for-kubernetes-ai-rzrutxnm5 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Multi-Cloud and Cross-Region GPU Capacity for Kubernetes AI | daily.dev og:description: GPU capacity is simultaneously scarce and underutilized — average GPU utilization in production Kubernetes clusters sits at just 5%, yet half of GPU cloud... og:url: https://daily.dev/posts/multi-cloud-and-cross-region-gpu-capacity-for-kubernetes-ai-rzrutxnm5 og:image: https://api.daily.dev/og/posts/rzruTxNM5.png og:image:alt: Multi-Cloud and Cross-Region GPU Capacity for Kubernetes AI 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. # Multi-Cloud and Cross-Region GPU Capacity for Kubernetes AI **[Cast AI](https://daily.dev/sources/castai)** · 14 min read · 0 upvotes · 0 comments ## Summary GPU capacity is simultaneously scarce and underutilized — average GPU utilization in production Kubernetes clusters sits at just 5%, yet half of GPU cloud providers are sold out of H100/H200 capacity. Cast AI's OMNI Compute addresses this by extending a single EKS, GKE, or AKS cluster to source GPU, TPU, and CPU across AWS, GCP, and OCI regions without application code changes. Built on the open-source Liqo project, edge locations appear as virtual nodes in the existing cluster, enabling standard Kubernetes scheduling across clouds. Built-in GPU sharing includes time-slicing (up to 48 replicas) and MIG partitioning (up to 7 isolated instances on A100/H100/H200). Cost savings of 2–5x versus average market price are possible by provisioning in the cheapest available region, though cross-cloud egress fees must be factored into total cost of ownership. The approach is best suited for inference and batch workloads; distributed multi-node training should stay within a single cloud for low-latency interconnects. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What does Cast AI's OMNI Compute do for Kubernetes GPU scheduling? OMNI Compute is a unified compute control plane that automatically discovers available GPU, TPU, and CPU resources across cloud providers and regions, then extends existing Kubernetes clusters to consume them without application code changes. It launched January 12, 2026, supporting Amazon EKS, Google GKE, and Azure AKS as main clusters, with edge locations in any AWS, GCP, or OCI region. _Teams weighing multi-cloud GPU strategies can track releases like this one on daily.dev._ ### Can a single Kubernetes cluster span multiple cloud providers for GPU workloads? Yes, using the open-source Liqo project, a main EKS, GKE, or AKS cluster can peer with edge locations across other cloud providers, which appear as virtual nodes under the castai-omni namespace. Workloads schedule to them using standard node selectors, taints, and tolerations, with Cast AI managing cloud accounts in each edge location, so no separate IAM roles are needed. _Engineers designing multi-cloud Kubernetes architectures follow updates like this on daily.dev._ ### Why is average GPU utilization so low on Kubernetes clusters despite GPU shortages? GPU utilization across production Kubernetes clusters averages just 5% pre-optimization, with AKS at 2%, EKS at 5%, and GKE at 6%, even while half of GPU cloud providers surveyed by SemiAnalysis reported being completely sold out of H100 and H200 capacity by April 2026. Fewer than 2% of GPU workloads run on Spot Instances, meaning most teams pay full On-Demand rates despite widespread idle capacity. _Anyone optimizing GPU spend on Kubernetes can follow cost data and trends like this on daily.dev._ ## Similar posts on daily.dev - [GPU Cloud Pricing in 2026: What AI Compute Really Costs](https://daily.dev/posts/gpu-cloud-pricing-in-2026-what-ai-compute-really-costs-3qdtmbswu) · Cast AI · 0 upvotes · 0 comments - [Cast AI vs SkyPilot: Two Approaches to Finding GPUs Across Clouds](https://daily.dev/posts/cast-ai-vs-skypilot-two-approaches-to-finding-gpus-across-clouds-nrtjdlmix) · Cast AI · 0 upvotes · 0 comments - [Building an AI factory on Kubernetes](https://daily.dev/posts/building-an-ai-factory-on-kubernetes-m4brxz3ty) · CNCF · 1 upvotes · 0 comments - [The Kubernetes GPU Stack Every MLOps Engineer Should Know in 2026](https://daily.dev/posts/the-kubernetes-gpu-stack-every-mlops-engineer-should-know-in-2026-hfvak84h8) · Medium · 8 upvotes · 1 comments - [Multi-cluster GKE Inference Gateway helps scale AI workloads](https://daily.dev/posts/multi-cluster-gke-inference-gateway-helps-scale-ai-workloads-79zwldgpg) · Google Cloud · 3 upvotes · 0 comments --- Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#gpu](https://daily.dev/tags/gpu), [#finops](https://daily.dev/tags/finops), [#multi-cloud](https://daily.dev/tags/multi-cloud) [View this post on daily.dev](https://daily.dev/posts/multi-cloud-and-cross-region-gpu-capacity-for-kubernetes-ai-rzrutxnm5) ```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":"Multi-Cloud and Cross-Region GPU Capacity for Kubernetes AI","url":"https://daily.dev/posts/multi-cloud-and-cross-region-gpu-capacity-for-kubernetes-ai-rzrutxnm5","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/multi-cloud-and-cross-region-gpu-capacity-for-kubernetes-ai-rzrutxnm5"},"datePublished":"2026-07-23T12:14:40.195Z","dateModified":"2026-09-13T19:41:40.771Z","description":"GPU capacity is simultaneously scarce and underutilized — average GPU utilization in production Kubernetes clusters sits at just 5%, yet half of GPU cloud...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/066af7f2bbf087fa821690780010fdb0?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/066af7f2bbf087fa821690780010fdb0?_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/multi-cloud-and-cross-region-gpu-capacity-for-kubernetes-ai-rzrutxnm5","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"kubernetes,gpu,finops,multi-cloud","timeRequired":"PT14M"} {"@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":"Multi-Cloud and Cross-Region GPU Capacity for Kubernetes AI"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/multi-cloud-and-cross-region-gpu-capacity-for-kubernetes-ai-rzrutxnm5#faq","mainEntity":[{"@type":"Question","name":"What does Cast AI's OMNI Compute do for Kubernetes GPU scheduling?","acceptedAnswer":{"@type":"Answer","text":"OMNI Compute is a unified compute control plane that automatically discovers available GPU, TPU, and CPU resources across cloud providers and regions, then extends existing Kubernetes clusters to consume them without application code changes. 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