NVIDIA publishes Workload Map for describing Kubernetes AI workloads

NVIDIA detailed Workload Map, a project that gives Kubernetes workloads a shared structural description so schedulers, controllers and platforms can read distributed jobs without framework-specific parsing code. It ships as a Kubernetes CRD plus a Go library, along with a catalog of prebuilt definitions covering JobSet, PyTorchJob, RayCluster, RayJob, RayService, KServe, Knative, MPIJob, NVIDIA NIM, LeaderWorkerSet, Milvus, Grove PodCliqueSet and NVIDIA Dynamo. The project, formerly called Karta, is available now from NVIDIA's repository, and its CLI installs through Homebrew. KAI Scheduler and NVIDIA Run:ai already consume the definitions, and Elotl's Nova uses them for multi-cluster scheduling. Teams can add other workload types by writing their own YAML definition.