NVIDIA has introduced two open-source projects, NVIDIA Kubernetes Engine and NVIDIA Kubernetes Recipes, to establish managed container environments for high-performance computing. While the recipes tool functions as a reproducible build pipeline for validated node images and Helm charts, the engine provides the control plane to provision workload clusters. Together, they integrate bare-metal infrastructure managed by the NVIDIA Infra Controller to deliver GPU capacity. The initial deployment workflow also utilizes a dedicated command-line interface named nvkectl alongside an OpenTelemetry-based telemetry pipeline.
Key points
AI factory operators can use familiar Kubernetes APIs to supply GPU capacity across multi…: AI factory operators can use familiar Kubernetes APIs to supply GPU capacity across multiple hardware generations.
Software packaging and cluster provisioning are split into separate reproducible pipeline…: Software packaging and cluster provisioning are split into separate reproducible pipelines and control plane layers.
Production deployment is currently discouraged because both projects remain in public pre…: Production deployment is currently discouraged because both projects remain in public preview with evolving configurations and APIs.
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NVIDIA is announcing two open source projects for building and operating managed Kubernetes services on GPU infrastructure—NVIDIA Kubernetes Engine (NVKE) and NVIDIA Kubernetes Recipes (NVKR). Both are new projects available in public preview.
AI Factory customers often want to consume GPU capacity through the Kubernetes APIs, tools, and ecosystem they already use, with the factory operating their clusters. Delivering this service requires API-driven provisioning, tenant isolation, upgrades, and recovery, backed by service commitments. It also requires qualifying GPU hardware, networking, drivers, and runtime software across GPU generations and Kubernetes versions.
NVKE and NVKR divide this work between cluster management and reproducible software builds. NVKE provides the software to run a managed Kubernetes service, installed on the factory’s infrastructure, with APIs to provision and manage clusters. NVKR builds the operating system images, container images, and packages those clusters need, using recipes that define validated combinations of software versions and GPU generations. AI Factories retain control of their software, operations, service, and customer experience. Teams can adopt NVKE and NVKR projects together or independently.
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