# Recipes Step-by-step guides that take you from a standing start to a working result. Each recipe is self-contained with prerequisites, runnable commands, and verification steps. Recipes are organized two ways: by **tier** (how much infrastructure you run) and by **topic** (what task you are doing). New users should start with the tier ladder below; the [default path is T0 — Dev](tier-0-dev/README.md), which runs the full training lifecycle loop on one laptop with zero cloud and zero Kubernetes. > [!NOTE] > Only the cloud tiers (**T2+**) and the topic recipes under [Training](#training) and [Data Collection](#data-collection) assume deployed Azure infrastructure. [T0 — Dev](tier-0-dev/README.md) and the storage-only [T1 — Lab](tier-1-lab/README.md) do not. If a recipe needs cloud resources, complete the [Quickstart](../getting-started/quickstart.md) first. For the canonical tier definitions, see the [tier model](../design/tier-model.md). ## 🪜 Pick a Tier Each tier states the minimum infrastructure it assumes. Start at the default (T0) and graduate only when a real constraint forces it. | T# | Recipe | Minimum infrastructure | Status | |----|------------------------------------------------|---------------------------------------------------|-----------------| | T0 | [T0 — Dev](tier-0-dev/README.md) | One laptop + one robot. ROS 2 + Docker. No cloud. | Default | | T1 | [T1 — Lab](tier-1-lab/README.md) | T0 + one Azure Blob storage account. | Authored | | T2 | [T2 — Pilot](tier-2-pilot/README.md) | AzureML + storage + registry + MLflow. No k8s. | Recommended | | T3 | [T3 — Production](tier-3-production/README.md) | T2 + single-site local k3s + FluxCD. No Arc. | Advanced (stub) | | T4 | [T4 — Scale](tier-4-scale/README.md) | Multi-site Arc + AKS/Flux + gating. | Advanced (stub) | | T5 | [T5 — Operate](tier-5-operate/README.md) | T4 + IoT Operations + Fabric RTI (roadmap). | Roadmap (stub) | ## 🗂️ Topic Recipes by Tier The existing topic recipes assume the tier shown below. They are unchanged by the tier ladder. This table only classifies them. | Topic recipe | Assumes tier | Minimum infrastructure | |---------------------------------------------------------------------------------------|--------------|----------------------------------------------------| | [Configuring Edge Data Recording](data-collection/configuring-edge-data-recording.md) | T0 — Dev | Jetson / robot, ROS 2. No cloud. | | [Preparing Datasets for Training](data-collection/preparing-datasets-for-training.md) | T0–T1 | Local for T0; Azure CLI + Blob for cloud datasets. | | [Your First LeRobot Training Job](training/your-first-lerobot-training-job.md) | T2 — Pilot | Deployed infrastructure, OSMO running. | | [Your First RL Training Job](training/your-first-rl-training-job.md) | T2 — Pilot | Deployed infrastructure, OSMO running. | | [End-to-End LeRobot Pipeline](training/end-to-end-lerobot-pipeline.md) | T2 — Pilot | Deployed infrastructure, OSMO running. | ## 🚀 Pick a Recipe | Goal | Recipe | Time | |-----------------------------------------------|---------------------------------------------------------------------------------------|--------| | Train an RL policy | [Your First RL Training Job](training/your-first-rl-training-job.md) | 30 min | | Train a LeRobot policy | [Your First LeRobot Training Job](training/your-first-lerobot-training-job.md) | 30 min | | Run the full train → eval → register pipeline | [End-to-End LeRobot Pipeline](training/end-to-end-lerobot-pipeline.md) | 60 min | | Configure edge recording | [Configuring Edge Data Recording](data-collection/configuring-edge-data-recording.md) | 20 min | | Prepare a dataset for training | [Preparing Datasets for Training](data-collection/preparing-datasets-for-training.md) | 30 min | ## 📖 Recipe Catalog ### Training | Recipe | Description | Prerequisites | |--------------------------------------------------------------------------------|--------------------------------------------------------|----------------------------------------------| | [Your First RL Training Job](training/your-first-rl-training-job.md) | Submit an Isaac Lab RL training job on OSMO with SKRL | Deployed infrastructure, OSMO running | | [Your First LeRobot Training Job](training/your-first-lerobot-training-job.md) | Submit a LeRobot behavioral cloning job on OSMO | Deployed infrastructure, HuggingFace dataset | | [End-to-End LeRobot Pipeline](training/end-to-end-lerobot-pipeline.md) | Orchestrate train → evaluate → register in one command | Completed basic LeRobot recipe | ### Data Collection | Recipe | Description | Prerequisites | |---------------------------------------------------------------------------------------|---------------------------------------------------------------------|-------------------------| | [Configuring Edge Data Recording](data-collection/configuring-edge-data-recording.md) | Set up ROS 2 edge recording on Jetson with chunking and compression | Jetson device, ROS 2 | | [Preparing Datasets for Training](data-collection/preparing-datasets-for-training.md) | Download, inspect, and validate datasets for LeRobot training | Python 3.12+, Azure CLI | ## 🔗 Related Documentation - [Tier model (canonical reference)](../design/tier-model.md): tier IDs, boundaries, and vocabulary - [Getting Started](../getting-started/README.md): infrastructure deployment and first training job - [Training Guide](../training/README.md): reference documentation for RL and IL workflows - [Data Pipeline](../data-pipeline/README.md): edge recording configuration reference - [Scripts Reference](../reference/scripts.md): CLI parameter tables for all submission scripts *🤖 Crafted with precision by ✨Copilot following brilliant human instruction, then carefully refined by our team of discerning human reviewers.*