docs(docs): add getting-started hub and quickstart tutorial (#369)

- create docs/getting-started/README.md hub page with navigation table
- create docs/getting-started/quickstart.md with 8-step deployment path
- use full-public networking and Access Keys for simplest onboarding path

📝 - Generated by Copilot

Co-authored-by: Bill Berry <wbery@microsoft.com>

Author: WilliamBerryiii

docs/getting-started/README.md

@@ -0,0 +1,53 @@
+---
+title: Getting Started
+description: Entry point for deploying the Azure NVIDIA Robotics Reference Architecture
+author: Microsoft Robotics-AI Team
+ms.date: 2026-02-22
+ms.topic: overview
+keywords:
+  - getting-started
+  - quickstart
+  - deployment
+  - onboarding
+---
+
+Deploy the Azure NVIDIA Robotics Reference Architecture and submit your first training job. This hub guides you through setup, deployment, and verification.
+
+## 🚀 Guides
+
+| Guide | Description |
+| --- | --- |
+| [Quickstart](quickstart.md) | 8-step path from clone to first training job |
+| Architecture Overview (coming soon) | System topology, components, and data flow |
+| Glossary (coming soon) | Term definitions for Azure, NVIDIA, and OSMO |
+
+## ⏱️ Time and Cost
+
+| Item | Estimate |
+| --- | --- |
+| Total deployment time | ~1.5-2 hours |
+| Quick validation cost | ~$25-50 |
+| GPU VM rate | ~$3.06/hour (A100) |
+
+> [!NOTE]
+> Run `terraform destroy` when finished to stop incurring costs. See [Cost Considerations](../contributing/cost-considerations.md) for detailed estimates.
+
+## 📋 Prerequisites Summary
+
+| Tool | Version |
+| --- | --- |
+| Terraform | ≥1.9.8 |
+| Azure CLI | ≥2.65.0 |
+| kubectl | ≥1.31 |
+| Helm | ≥3.16 |
+| Python | ≥3.11 |
+
+Azure subscription with Contributor + User Access Administrator roles, GPU quota for `Standard_NC24ads_A100_v4`, and an NVIDIA NGC account are required. See [Prerequisites](../contributing/prerequisites.md) for full details.
+
+## 📚 Related Documentation
+
+| Resource | Description |
+| --- | --- |
+| [Contributing Guide](../contributing/README.md) | Development workflow and code standards |
+| [Deployment Guide](../../deploy/README.md) | Detailed deployment reference |
+| [Cost Considerations](../contributing/cost-considerations.md) | Pricing breakdown and optimization |

docs/getting-started/quickstart.md

@@ -0,0 +1,184 @@
+---
+title: "Quickstart: Clone to First Training Job"
+description: Deploy infrastructure and submit your first robotics training job in 8 steps
+author: Microsoft Robotics-AI Team
+ms.date: 2026-02-22
+ms.topic: tutorial
+keywords:
+  - quickstart
+  - deployment
+  - training
+  - tutorial
+---
+
+Deploy the full Azure NVIDIA Robotics stack and submit a training job in ~1.5-2 hours. This guide uses full-public networking and Access Keys authentication for the simplest path.
+
+> [!NOTE]
+> This guide expands on the [Getting Started hub](README.md).
+
+## Prerequisites
+
+| Requirement | Details |
+| --- | --- |
+| Azure subscription | Contributor + User Access Administrator roles |
+| GPU quota | `Standard_NC24ads_A100_v4` in target region |
+| NVIDIA NGC account | Sign up at <https://ngc.nvidia.com/> for API key |
+| Development environment | Devcontainer (recommended) or local tools |
+
+See [Prerequisites](../contributing/prerequisites.md) for installation commands and version requirements.
+
+## Step 1: Clone and Set Up Environment
+
+Clone the repository and initialize the development environment.
+
+```bash
+git clone https://github.com/Azure-Samples/azure-nvidia-robotics-reference-architecture.git
+cd azure-nvidia-robotics-reference-architecture
+```
+
+Use the devcontainer (recommended) or run local setup:
+
+```bash
+./setup-dev.sh
+```
+
+## Step 2: Configure Azure Subscription
+
+Authenticate with Azure and register required resource providers.
+
+```bash
+source deploy/000-prerequisites/az-sub-init.sh
+bash deploy/000-prerequisites/register-azure-providers.sh
+```
+
+Verify your subscription:
+
+```bash
+az account show --query "{name:name, id:id}" -o table
+```
+
+## Step 3: Configure Terraform Variables
+
+Create a Terraform variables file for the full-public deployment path. From the repository root:
+
+```bash
+cd deploy/001-iac
+cp terraform.tfvars.example terraform.tfvars
+```
+
+Edit `terraform.tfvars` with these values:
+
+```hcl
+project_name = "robotics"
+environment  = "dev"
+location     = "eastus"
+gpu_vm_size  = "Standard_NC24ads_A100_v4"
+
+enable_azure_ml    = true
+enable_osmo        = true
+enable_vpn_gateway = false
+enable_private_dns = false
+```
+
+> [!TIP]
+> For private networking, set `enable_vpn_gateway = true` and `enable_private_dns = true`. See the [Infrastructure Guide](../../deploy/001-iac/README.md) for details.
+
+## Step 4: Deploy Infrastructure
+
+Initialize and apply the Terraform configuration. This step takes ~30-40 minutes.
+
+```bash
+terraform init
+terraform plan -out=tfplan
+terraform apply tfplan
+```
+
+Verify deployment:
+
+```bash
+terraform output
+```
+
+Connect to the AKS cluster:
+
+```bash
+az aks get-credentials \
+  --resource-group "$(terraform output -raw resource_group_name)" \
+  --name "$(terraform output -raw aks_cluster_name)"
+```
+
+## Step 5: Configure AKS Cluster
+
+Deploy GPU Operator, KAI Scheduler, and the AzureML extension. From the repository root:
+
+```bash
+cd deploy/002-setup
+bash 01-deploy-robotics-charts.sh
+bash 02-deploy-azureml-extension.sh
+```
+
+Verify GPU operator pods:
+
+```bash
+kubectl get pods -n gpu-operator
+```
+
+## Step 6: Deploy OSMO Components
+
+Deploy the OSMO control plane and backend using Access Keys authentication.
+
+```bash
+bash 03-deploy-osmo-control-plane.sh
+bash 04-deploy-osmo-backend.sh --use-access-keys
+```
+
+Verify OSMO pods:
+
+```bash
+kubectl get pods -n osmo-control-plane
+```
+
+## Step 7: Submit First Training Job
+
+Navigate to the scripts directory and submit a training job. From the repository root:
+
+```bash
+cd scripts
+bash submit-osmo-training.sh
+```
+
+Scripts auto-detect configuration from Terraform outputs. Override values with CLI arguments or environment variables as needed. See [Scripts](../../scripts/README.md) for all submission options.
+
+## Step 8: Verify Results
+
+Confirm the training job is running:
+
+```bash
+kubectl get pods -n osmo-control-plane --watch
+```
+
+Check OSMO training status through the OSMO web UI or query pod logs:
+
+```bash
+kubectl logs -n osmo-control-plane -l app=osmo-training --tail=50
+```
+
+## Cleanup
+
+Destroy all infrastructure when finished to stop incurring costs. From the repository root:
+
+```bash
+cd deploy/001-iac
+terraform destroy
+```
+
+See [Cost Considerations](../contributing/cost-considerations.md) for detailed pricing.
+
+## Next Steps
+
+| Resource | Description |
+| --- | --- |
+| [LeRobot Inference](../lerobot-inference.md) | Run inference with trained LeRobot models |
+| [MLflow Integration](../mlflow-integration.md) | Track experiments with MLflow |
+| [Deployment Guide](../../deploy/README.md) | Full deployment reference and options |
+| [Contributing Guide](../contributing/README.md) | Development workflow and code standards |