mckornfield · Jul 20, 2026 · Jul 20, 2026
@@ -1,73 +1,56 @@
 ---
-title: "v0.2.0 - 2026-06-25"
+title: "v0.3.0"
 description: ""
 ---
-NeMo Platform v0.2.0 expands the local-first OSS distribution with plugin
-workflows for fine-tuning, synthetic data generation, and model auditing. It
-also improves Docker-backed local workflows, SDK resources, and NAT-based agent
-container tooling.
+NeMo Platform v0.3.0 expands the OSS distribution beyond local setup with
+self-managed Kubernetes and Helm documentation, while continuing to support
+the local-first Python package, CLI, SDK, Studio, and plugin workflows.
 
 ## Highlights
 
-- **Fine-tuning.** Customizer is available through the plugin architecture,
-  with Docker-backed Unsloth jobs, NeMo Automodel configuration support, vLLM
-  adapter support, and updated tutorials.
-- **Local model serving.** vLLM deployment in Docker supports local
-  model-serving workflows for OSS development and testing.
-- **Synthetic data generation.** Safe Synthesizer is available as a local
-  plugin for privacy-preserving synthetic data generation workflows.
-- **Model auditing.** Auditor adds local garak-backed audit configuration,
-  target management, SDK resources, and documentation.
-- **Agent containers.** `nemo agents` includes commands for rendering,
-  building, and publishing agent containers.
-- **Plugin platform.** Platform capabilities can ship as plugins while still
-  using platform APIs, SDK resources, local services, and workspace scoping.
+- **Self-managed Kubernetes.** The docs now cover Helm-based deployment to
+  user-managed Kubernetes clusters, including local Kind workflows and
+  cluster prerequisites.
+- **Agent deployment docs.** Agent container deployment guidance covers local
+  and Kubernetes paths and clarifies how SDK, CLI, and REST callers resolve
+  default model placeholders.
+- **Versioned compatibility.** Requirements and support-matrix pages describe
+  the 0.3.0 release instead of the previous local-only scope.
+- **Generated reference docs.** The configuration reference remains generated
+  from platform config models and renders as regular Fern MDX.
 
 ## What's included
 
-### Platform and Plugins
+### Platform
 
-- Plugin packaging for platform capabilities distributed outside the core
-  package.
-- Docker support for source-install local platform workflows.
-- SDK and API support for plugin-provided resources.
+- Local source-install workflows with `make bootstrap`, `nemo setup`, and
+  `nemo services run`.
+- Self-managed Helm/Kubernetes documentation for users deploying the platform
+  outside the local developer process.
 - Source-install auth and OIDC bootstrap guidance for users who enable RBAC
   locally.
 
-### Fine-tune Models
-
-- Customizer migration to the plugin architecture.
-- Docker-backed Unsloth SFT jobs.
-- NeMo Automodel and Unsloth backend support for fine-tuning workflows.
-- vLLM adapter support for serving trained adapters.
-- Updated Customizer documentation and examples.
-
-### Models and Inference
-
-- vLLM deployment in Docker for local model-serving workflows.
-- Local model-deployment documentation for the OSS quickstart and SDK usage.
-- Continued Inference Gateway support for provider registration, virtual
-  models, and OpenAI-compatible routing.
-
 ### Agents
 
-- `nemo agents` container subcommands for rendering, building, and publishing
-  agent containers.
-- Continued NAT-based agent workflow support from the 0.1 line.
+- NAT-based agent workflow support through `nemo agents`.
+- Agent container rendering, building, publishing, and deployment guidance.
+- SDK and CLI examples that use the configured default model for agent
+  registration.
 
-### Safe Synthesizer
+### Models and Inference
 
-- Safe Synthesizer packaged as a platform plugin.
-- Local execution support for Safe Synthesizer workflows.
-- Documentation and tutorials for data synthesis, PII replacement,
-  evaluation, jobs, host-local development, and differential privacy.
+- Inference Gateway support for provider registration, virtual models, and
+  OpenAI-compatible routing.
+- Local and provider-backed model workflows for CLI, SDK, Studio, and agents.
 
-### Auditor
+### Plugins
 
-- Auditor plugin APIs for audit configs and targets.
-- Local garak-backed auditing workflows.
-- SDK resources and documentation for configuring audits and reviewing
-  results.
+- First-party plugin workflows continue from the previous release line,
+  including Agents, Customizer, Safe Synthesizer, Auditor, Guardrails,
+  Evaluator, Anonymizer, Data Designer, Switchyard middleware, and
+  Deployments.
+- Plugin docs cover runtime service, CLI, job, controller, inference
+  middleware, and coding-agent skill surfaces.
 
 ## Install
 
@@ -84,39 +67,41 @@ nemo setup
 See [Setup](/documentation/get-started) for prerequisites and provider
 configuration.
 
-## Upgrade from v0.1.x
+For self-managed Kubernetes, start with
+[Install NeMo Platform Helm Chart](/documentation/self-managed-deployment/setup/helm/install).
+
+## Upgrade from v0.2.x
 
 From an existing local checkout:
 
 ```bash
-git fetch --tags
-git checkout v0.2.0
+git fetch
+git checkout main
 make bootstrap
 source .venv/bin/activate
 nemo setup
 ```
 
-If the `v0.2.0` tag is not available from GitHub yet, use the fresh checkout
-flow above and return to the release tag after it is published.
-
 After setup, restart local services before using CLI, SDK, Studio, or plugin
 workflows against the upgraded checkout.
 
 ## Compatibility
 
 - Python 3.11-3.14
-- macOS and Linux for the OSS local install path
-- Docker for Docker-backed platform, job, and vLLM model-serving workflows
+- macOS and Linux for local CLI, SDK, Studio, and hosted-provider workflows
+- Linux x86_64 for local NVIDIA GPU workloads
+- Self-managed Kubernetes clusters deployed with Helm
+- Docker for Docker-backed platform, job, and local model-serving workflows
 - NVIDIA GPU access for local training, model serving, and GPU-backed
   synthetic data workflows
 - Node 22.18.0+ for Studio assets
-- Platform API `0.2.0` and `nemo-platform` Python SDK `0.2.0`
+- Platform API and `nemo-platform` Python SDK `0.3.0`
 
 ## Current constraints
 
-- **Local-first OSS scope.** v0.2.0 improves local Docker-backed workflows. It
-  is not a managed cluster or scale-out enterprise release.
-- **Docker model serving.** v0.2.0 includes vLLM deployment in Docker. Docker
+- **Self-managed scope.** v0.3.0 documents local setup and user-managed
+  Kubernetes deployment. It is not a managed hosted-service release.
+- **Docker model serving.** v0.3.0 includes vLLM deployment in Docker. Docker
   deployment for NIM is not included in this release.
 - **Customizer Docker support.** Docker-backed Customizer jobs target GPU
   Linux environments. ARM64 images and NeMo Automodel Docker execution are not
@@ -126,7 +111,7 @@ workflows against the upgraded checkout.
   role bindings for your deployment mode before relying on them for multi-user
   access control.
 - **Skill Evaluation.** Skill Evaluation workflows are not included in
-  v0.2.0.
+  v0.3.0.
 
 ## Links
 

@@ -4,5 +4,6 @@ description: ""
 ---
 Check out the latest release notes for NeMo Platform.
 
-- [Release 0.2.0](/documentation/reference/release-notes/current-release)
+- [Release 0.3.0](/documentation/reference/release-notes/current-release)
+- [Release 0.2.0](/documentation/reference/release-notes/release-0-2-0)
 - [Release 0.1.0](/documentation/reference/release-notes/release-0-1-0)
@@ -0,0 +1,135 @@
+---
+title: "v0.2.0 - 2026-06-25"
+description: ""
+---
+NeMo Platform v0.2.0 expands the local-first OSS distribution with plugin
+workflows for fine-tuning, synthetic data generation, and model auditing. It
+also improves Docker-backed local workflows, SDK resources, and NAT-based agent
+container tooling.
+
+## Highlights
+
+- **Fine-tuning.** Customizer is available through the plugin architecture,
+  with Docker-backed Unsloth jobs, NeMo Automodel configuration support, vLLM
+  adapter support, and updated tutorials.
+- **Local model serving.** vLLM deployment in Docker supports local
+  model-serving workflows for OSS development and testing.
+- **Synthetic data generation.** Safe Synthesizer is available as a local
+  plugin for privacy-preserving synthetic data generation workflows.
+- **Model auditing.** Auditor adds local garak-backed audit configuration,
+  target management, SDK resources, and documentation.
+- **Agent containers.** `nemo agents` includes commands for rendering,
+  building, and publishing agent containers.
+- **Plugin platform.** Platform capabilities can ship as plugins while still
+  using platform APIs, SDK resources, local services, and workspace scoping.
+
+## What's included
+
+### Platform and Plugins
+
+- Plugin packaging for platform capabilities distributed outside the core
+  package.
+- Docker support for source-install local platform workflows.
+- SDK and API support for plugin-provided resources.
+- Source-install auth and OIDC bootstrap guidance for users who enable RBAC
+  locally.
+
+### Fine-tune Models
+
+- Customizer migration to the plugin architecture.
+- Docker-backed Unsloth SFT jobs.
+- NeMo Automodel and Unsloth backend support for fine-tuning workflows.
+- vLLM adapter support for serving trained adapters.
+- Updated Customizer documentation and examples.
+
+### Models and Inference
+
+- vLLM deployment in Docker for local model-serving workflows.
+- Local model-deployment documentation for the OSS quickstart and SDK usage.
+- Continued Inference Gateway support for provider registration, virtual
+  models, and OpenAI-compatible routing.
+
+### Agents
+
+- `nemo agents` container subcommands for rendering, building, and publishing
+  agent containers.
+- Continued NAT-based agent workflow support from the 0.1 line.
+
+### Safe Synthesizer
+
+- Safe Synthesizer packaged as a platform plugin.
+- Local execution support for Safe Synthesizer workflows.
+- Documentation and tutorials for data synthesis, PII replacement,
+  evaluation, jobs, host-local development, and differential privacy.
+
+### Auditor
+
+- Auditor plugin APIs for audit configs and targets.
+- Local garak-backed auditing workflows.
+- SDK resources and documentation for configuring audits and reviewing
+  results.
+
+## Install
+
+For a fresh local checkout:
+
+```bash
+git clone https://github.com/NVIDIA-NeMo/nemo-platform.git
+cd nemo-platform
+make bootstrap
+source .venv/bin/activate
+nemo setup
+```
+
+See [Setup](/documentation/get-started) for prerequisites and provider
+configuration.
+
+## Upgrade from v0.1.x
+
+From an existing local checkout:
+
+```bash
+git fetch --tags
+git checkout v0.2.0
+make bootstrap
+source .venv/bin/activate
+nemo setup
+```
+
+If the `v0.2.0` tag is not available from GitHub yet, use the fresh checkout
+flow above and return to the release tag after it is published.
+
+After setup, restart local services before using CLI, SDK, Studio, or plugin
+workflows against the upgraded checkout.
+
+## Compatibility
+
+- Python 3.11-3.14
+- macOS and Linux for the OSS local install path
+- Docker for Docker-backed platform, job, and vLLM model-serving workflows
+- NVIDIA GPU access for local training, model serving, and GPU-backed
+  synthetic data workflows
+- Node 22.18.0+ for Studio assets
+- Platform API `0.2.0` and `nemo-platform` Python SDK `0.2.0`
+
+## Current constraints
+
+- **Local-first OSS scope.** v0.2.0 improves local Docker-backed workflows. It
+  is not a managed cluster or scale-out enterprise release.
+- **Docker model serving.** v0.2.0 includes vLLM deployment in Docker. Docker
+  deployment for NIM is not included in this release.
+- **Customizer Docker support.** Docker-backed Customizer jobs target GPU
+  Linux environments. ARM64 images and NeMo Automodel Docker execution are not
+  part of this release.
+- **Auth and RBAC.** Source-install auth and OIDC setups require the bootstrap
+  IAM seed step described in [Setup](/documentation/get-started). Validate
+  role bindings for your deployment mode before relying on them for multi-user
+  access control.
+- **Skill Evaluation.** Skill Evaluation workflows are not included in
+  v0.2.0.
+
+## Links
+
+- Repository: [https://github.com/NVIDIA-NeMo/nemo-platform](https://github.com/NVIDIA-NeMo/nemo-platform)
+- Issues: [https://github.com/NVIDIA-NeMo/nemo-platform/issues](https://github.com/NVIDIA-NeMo/nemo-platform/issues)
+- NeMo Agent Toolkit: [https://docs.nvidia.com/nemo/agent-toolkit/latest/](https://docs.nvidia.com/nemo/agent-toolkit/latest/)
@@ -4,7 +4,7 @@ description: ""
 ---
 <a id="agents-plugins"></a>
 
-NeMo Platform 0.2.0 is extended through Python plugins and
+NeMo Platform 0.3.0 is extended through Python plugins and
 coding-agent skills. Plugins add runtime capabilities to the local platform.
 Skills teach your coding agent how to operate those capabilities on your behalf.
 
@@ -112,5 +112,6 @@ build the policy bundle rather than serve an unguarded endpoint. See
 [Plugin Authorization](/documentation/access-control/authorization/plugin-authorization)
 for the full pattern.
 
-Keep plugins local-first for OSS 0.2.0: avoid requiring a cluster,
-container runtime, or external control plane for the documented launch path.
+Keep plugins usable from the local OSS setup path: avoid requiring a cluster,
+container runtime, or external control plane unless that plugin explicitly
+documents a self-managed Kubernetes workflow.
@@ -24,20 +24,20 @@ At a high level, the fine-tuning workflow consists of the following steps:
 
 ## Container Images
 
-Fine-tuning jobs run in container images published to NVIDIA NGC. For NeMo Platform `0.2.0`, the fine-tuning images are:
+Fine-tuning jobs run in container images published to NVIDIA NGC. Use the image tag that matches your NeMo Platform release:
 
 | Image | Purpose |
 |-------|---------|
-| `nvcr.io/nvidia/nemo-platform/nmp-customizer-tasks:0.2.0` | Shared CPU task steps (file I/O, model entity, model spec) for all customization backends |
-| `nvcr.io/nvidia/nemo-platform/nmp-automodel-training:0.2.0` | Automodel GPU training step |
-| `nvcr.io/nvidia/nemo-platform/nmp-unsloth-training:0.2.0` | Unsloth GPU training step |
+| `nvcr.io/nvidia/nemo-platform/nmp-customizer-tasks:<image-tag>` | Shared CPU task steps (file I/O, model entity, model spec) for all customization backends |
+| `nvcr.io/nvidia/nemo-platform/nmp-automodel-training:<image-tag>` | Automodel GPU training step |
+| `nvcr.io/nvidia/nemo-platform/nmp-unsloth-training:<image-tag>` | Unsloth GPU training step |
 
 These public images can be pulled directly from `nvcr.io`:
 
 ```bash
-docker pull nvcr.io/nvidia/nemo-platform/nmp-customizer-tasks:0.2.0
-docker pull nvcr.io/nvidia/nemo-platform/nmp-automodel-training:0.2.0
-docker pull nvcr.io/nvidia/nemo-platform/nmp-unsloth-training:0.2.0
+docker pull nvcr.io/nvidia/nemo-platform/nmp-customizer-tasks:<image-tag>
+docker pull nvcr.io/nvidia/nemo-platform/nmp-automodel-training:<image-tag>
+docker pull nvcr.io/nvidia/nemo-platform/nmp-unsloth-training:<image-tag>
 ```
 
 Most users do not need to pull these images manually. NeMo Platform resolves them from the configured platform image registry and tag. Pull or mirror them when you are operating a self-managed deployment, preloading an air-gapped environment, or validating registry access. If your environment requires authenticated registry pulls, authenticate to `nvcr.io` with an NGC API key before pulling or mirroring the images.

@@ -599,8 +599,6 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "(ft-deploy-full-weight-model)=\n",
-        "\n",
         "### 8. Deploy Fine-Tuned Model\n",
         "\n",
         "After training completes, deploy using the Deployment Management Service:"

@@ -467,8 +467,6 @@ Monitor the relationship between training and validation loss curves:
 
 **Note:** Training metrics measure optimization progress, not final model quality. Always evaluate the deployed model on your specific use case.
 
-(ft-deploy-full-weight-model)=
-
 ### 8. Deploy Fine-Tuned Model
 
 After training completes, deploy using the Deployment Management Service: