> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nvcf/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nvcf/_mcp/server.

# NVCF Self-Hosted 0.6.0 Release Notes

NVCF Self-Hosted 0.6.0 is a stable release. It adds asynchronous task
workloads, multi-cluster control-plane management, OpenAI-compatible LLM
routing, single-mode Multi-Instance GPU (MIG) support, and control-plane
observability. It also adds Early Access support for optional NVIDIA Dynamo and
Grove operator integration.

## Highlights

| Feature | Status | Summary |
| --- | --- | --- |
| NVIDIA Cloud Tasks (NVCT) | GA | Run asynchronous GPU jobs to completion without keeping an online endpoint. |
| Multi-cluster GPU management | GA | Register and manage multiple GPU clusters from one NVCF control plane. |
| Dynamo operator integration | Early Access, optional | Install optional NVIDIA Dynamo and Grove operators on GPU clusters. |
| LLM API Gateway | GA | Route OpenAI-compatible chat completions, Responses, and embeddings by model. |
| Single-mode MIG | GA | Expose single-strategy MIG profiles as NVCF instance types. |
| Control-plane observability | GA | Export metrics, logs, and optional traces from control-plane services. |

## NVIDIA Cloud Tasks (NVCT)

NVIDIA Cloud Tasks (NVCT) adds an asynchronous workload type for
run-to-completion GPU jobs. Tasks are the batch counterpart to Cloud Functions:
functions stay online to serve invocation requests, while tasks run to
completion and release GPU capacity when they finish.

Use NVCT for batch inference, fine-tuning, evaluation, solvers, data
preparation, and other GPU workloads that do not require an always-on endpoint.

## Multi-Cluster GPU Management

A single NVCF control plane can now register and manage multiple GPU clusters.
Each cluster keeps its own identity and configuration, so operators can expand
across regions, cloud providers, or on-premises environments without running a
separate NVCF control plane for each cluster.

After registration, workloads can deploy to the available clusters through the
same control-plane API.

## Dynamo Operator Integration

NVCF can integrate with optional NVIDIA Dynamo and Grove operators installed on
each GPU cluster. KAI Scheduler is a separate prerequisite for using these
components.

This integration is Early Access and optional.

## LLM API Gateway

The LLM API Gateway provides an OpenAI-compatible entry point for LLM workloads
on NVCF. It reads the target function and model from the request's `model`
field, routes chat completions, Responses, and embeddings to the matching model
backend, and applies per-model token rate limits.

When cache-aware routing is enabled, the gateway can keep multi-turn requests on
the same backend for better cache locality.

## Single-Mode MIG

NVCF can detect GPUs configured with the single MIG strategy and expose each MIG
profile as an NVCF instance type. Workloads can target an isolated GPU slice
instead of a full GPU, improving capacity use on supported nodes.

## Control-Plane Observability

Control-plane observability is configured through one Helmfile configuration
block. NVCF can export Prometheus-compatible metrics, control-plane logs, and
optional OpenTelemetry Protocol (OTLP) traces to an existing observability
backend, including in air-gapped environments.

## Upgrade Notes

For an existing 0.5.x deployment, follow the
[0.5.0 to 0.6.0 Upgrade](/nvcf/0-5-0-to-0-6-0-upgrade) procedure. It covers the
required migration stops, full stack sync, and GPU cluster re-registration
steps.

Customers with GPU clusters running NVIDIA Cluster Agent (NVCA) versions older
than 2.51.0 must upgrade those clusters to NVCA 2.51.0 before moving to NVCA
3.x. NVCA 2.51.0 includes fixes for workload lifecycle management and GPU
capacity accounting. Skipping this version can cause incorrect GPU resource
accounting, untracked workload pods, or capacity mismatches between the GPU
cluster and the control plane.

| Current NVCA version | Action |
| --- | --- |
| 2.50.5 or older | Upgrade to 2.51.0 first, verify cluster health, then upgrade to 3.0 or later. |
| 2.51.0 | Upgrade directly to 3.0 or later. |

Check the current NVCA version:

```bash
kubectl get nvcfbackend -n nvca-operator
```

The `VERSION` column shows the deployed NVCA version.

Upgrade the NVCA operator to 2.51.0 before continuing to 3.x:

```bash
helm upgrade nvca-operator -n nvca-operator \
  --reuse-values \
  --wait \
  "${CHART_URL}" \
  --username='$oauthtoken' \
  --password="$(helm get values -n nvca-operator nvca-operator -o json | jq -r '.ngcConfig.serviceKey')" \
  --set helmManaged.nvcaVersion="2.51.0"
```

After the upgrade, verify that the cluster is healthy before proceeding:

```bash
kubectl get nvcfbackend -n nvca-operator
# Verify VERSION shows 2.51.0 and HEALTH shows healthy.
```