> This page is for Multi-Tenant, version v3.0 (default). > For other versions, use one of these documentation indexes: > - v3.0 (default): https://docs.nvidia.com/run-ai/multi-tenant/v3.0/llms.txt > - v2.26: https://docs.nvidia.com/run-ai/multi-tenant/v2.26/llms.txt > - v2.25: https://docs.nvidia.com/run-ai/multi-tenant/v2.25/llms.txt > - v2.24: https://docs.nvidia.com/run-ai/multi-tenant/v2.24/llms.txt > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/run-ai/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/run-ai/_mcp/server. # External Dependencies NVIDIA Run:ai's cluster components build on external open-source projects, pulled in as versioned Helm chart dependencies or Go modules rather than built from Run:ai source. NVIDIA Run:ai packages, configures, and manages these dependencies as part of the platform, so no separate installation or maintenance is required to use them. Helm chart dependencies are declared in [`runai-chart/Chart.yaml`](https://github.com/dsx-ai-factory/run-ai/blob/main/runai-cluster/cluster/runai-chart/Chart.yaml) and documented in the [Chart dependencies](https://github.com/dsx-ai-factory/run-ai/blob/main/runai-cluster/cluster/runai-chart/README.md#chart-dependencies) section of the runai-chart README. ## KAI Resource Management (KRM) **Source:** [`kai-scheduler/kai-resource-management`](https://github.com/kai-scheduler/kai-resource-management) **Dependency of:** `runai-chart` - a direct Helm chart dependency KAI Resource Management is a Kubernetes-native resource-management layer for KAI Scheduler, adding organizational abstractions - projects, departments, node pools, queues - and workload placement. Its Helm chart packages `nodepool-controller`, `project-controller`, `pod-group-assigner`, and `krm-operator`, replacing the versions of those controllers previously built from Run:ai's own cluster source, and declares KAI Scheduler as its own sub-chart dependency. ## KAI Scheduler **Source:** [`kai-scheduler/KAI-Scheduler`](https://github.com/kai-scheduler/KAI-Scheduler) **Dependency of:** KRM - a sub-chart dependency (`oci://ghcr.io/kai-scheduler/kai-scheduler`, declared in KRM's `Chart.yaml`), not a direct entry in `runai-chart` KAI (Kubernetes AI) Scheduler is an open-source, CNCF-donated AI-aware scheduling engine. It applies fair-share, preemption, bin-packing, and multi-node placement rules to GPU workloads, and is the engine underlying the NVIDIA Run:ai Scheduler. NVIDIA Run:ai integrates KAI with specific configuration overrides - the `go-operator` owns `kai-config` and the `kai-nodepool-controller` creates one KAI SchedulingShard per node pool. KAI's default queue, shard, and config-deployer components are disabled. ## gpu-fractioning **Source:** [`kai-scheduler/gpu-fractioning`](https://github.com/kai-scheduler/gpu-fractioning) **Dependency of:** KAI Scheduler - a sub-chart dependency, so it does not need its own entry in `runai-chart/Chart.yaml` gpu-fractioning is a Kubernetes operator that enables multiple pods to safely share a single GPU with enforced memory boundaries. It runs alongside KAI Scheduler: KAI Scheduler decides which fraction of which GPU a workload gets, and gpu-fractioning enforces that memory boundary on the node and exports per-pod metrics for the resulting fractional GPUs. ## kai-resource-management-api **Source:** [`kai-scheduler/kai-resource-management-api`](https://github.com/kai-scheduler/kai-resource-management-api) **Dependency of:** Run:ai's own cluster services (declared in each service's `go.mod`) - a Go module dependency, not a Helm chart dependency and not a separately running service The API-only counterpart to KRM: the CRD type definitions (`kai.resources`: Project, Department, NodePool, ManagedNodesConfig, KRMConfig). Any Run:ai service that reads or writes these CRDs imports this module for the typed Go structs, independent of which controller owns reconciling them - today that's a mix of Run:ai's own controllers and, once KRM is adopted, KRM's. Migrating legacy CRDs onto `kai.resources` runs automatically this release and self-gates once complete; it is not a customer-facing toggle. ## workload-map **Source:** [`dsx-ai-factory/workload-map`](https://github.com/dsx-ai-factory/workload-map) **Dependency of:** `runai-chart` - a direct Helm chart dependency (`oci://ghcr.io/dsx-ai-factory/workload-map/karta`, declared in `Chart.yaml`) Karta is a CRD-based resource abstraction layer with its own operator. It replaced the legacy `ResourceInterface` (RI) CRD as the way Run:ai represents and reconciles workload resource attachments in the cluster. The `karta-migrate` Helm hook handles the one-time migration from RI to Karta CRs on upgrade. --- ## Integrating a Custom Version To replace any of these dependencies with a custom build: 1. Fork the relevant external repository and make your changes. 2. Build and publish your custom chart to an OCI registry. 3. Update the dependency entry in [`runai-chart/Chart.yaml`](https://github.com/dsx-ai-factory/run-ai/blob/main/runai-cluster/cluster/runai-chart/Chart.yaml) - change `repository` to your registry and `version` to your build. 4. Run `helm dep update` in `runai-cluster/cluster/runai-chart/` to pull in your version. 5. Deploy with `helm upgrade` or via `local-dev.sh`.