- 🐣 Starter guide
- 🐔 Production guide
- 🦜 LLMOps guide
- 😸 Set up a project repository
- ⛓️ Build a pipeline
- Use pipeline/step parameters
- Step output typing and annotation
- Control caching behavior
- Specify pip or apt requirements
- Schedule a pipeline
- Deleting a pipeline
- Trigger a pipeline from another
- Run pipelines asynchronously
- Control execution order of steps
- Using a custom step invocation ID
- Name your pipeline runs
- Use failure/success hooks
- Hyperparameter tuning
- Version pipelines
- Access secrets in a step
- Fetching pipelines
- Get past pipeline/step runs
- 📃 Use configuration files
- 🐳 Customize Docker builds
- Docker settings on a pipeline
- Docker settings on a step
- Specify pip dependencies and apt packages
- Use your own Dockerfiles
- Which files are built into the image
- Reuse Docker builds to speed up Docker build times
- Use code repositories to automate Docker build reuse
- Build the pipeline without running
- Define where an image is built
- 🚜 Train with GPUs
- 🌲 Control logging
- 🗄️ Handle Data/Artifacts
- 📊 Visualizing artifacts
- 🪆 Use the Model Control Plane
- 📈 Track metrics and metadata
- 👨🎤 Popular integrations
- 🔌 Connect services (AWS, GCP, Azure, K8s etc)
- ⚒️ Manage stacks
- 🐍 Configure Python environments
- 🔌 Connect to a server
- 🔐 Interact with secrets
- 🐞 Debug and solve issues
- 📜 Overview
- 🔋 Orchestrators
- 🏪 Artifact Stores
- 🐳 Container Registries
- 🧪 Data Validators
- 📈 Experiment Trackers
- 🏃♀️ Model Deployers
- 👣 Step Operators
- ❗ Alerters
- 🖼️ Image Builders
- 🏷️ Annotators
- 📓 Model Registries
- 📊 Feature Stores