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  • Flyte
  • User guide
  • Tutorials
  • Integrations
  • Deployment guide
  • API reference
  • Community
  • Flyte
  • GitHub
  • Slack
  • Flyte

User guide

  • Introduction to Flyte
  • Quickstart guide
  • Getting started with workflow development
    • Installing development tools
    • Creating a Flyte project
    • Flyte project components
    • Running a workflow locally
  • Basics
    • Hello, World!
    • Tasks
    • Workflows
    • Launch plans
    • Imperative workflows
    • Documenting workflows
    • Shell tasks
    • Named outputs
  • Data Types and IO
    • FlyteFile
    • FlyteDirectory
    • StructuredDataset
    • Dataclass
    • Pydantic BaseModel
    • Accessing attributes in workflows
    • PyTorch type
    • Enum type
    • Pickle type
    • TensorFlow types
  • Advanced composition
    • Conditionals
    • Chaining Flyte entities
    • Subworkflows
    • Dynamic workflows
    • Map tasks
    • Nested parallelization
    • Eager workflows
    • Decorating tasks
    • Decorating workflows
    • Intratask checkpoints
    • Waiting for external inputs
  • Customizing dependencies
    • ImageSpec
    • Raw containers
    • Multiple images in a workflow
  • Development lifecycle
    • Private images
    • Caching
    • Cache serializing
    • Decks
    • Failure node
    • Creating a new project
    • Running tasks
    • Running workflows
    • Running launch plans
    • Inspecting executions
    • Debugging executions
    • Migrating from Airflow to Flyte
  • Testing
    • Mocking tasks
  • Productionize
    • Customizing task resources
    • Reference tasks
    • Reference launch plans
    • Notifications
    • Schedules
    • Configuring logging links in the UI
    • Configuring access to GPUs
    • Spot instances
    • Secrets
    • Workflow labels and annotations
  • Extending Flyte
    • Custom types
    • Prebuilt container task plugins
    • User container task plugins
    • Backend plugins
    • Container interface
  • Flyte agents
    • Testing agents in a local Python environment
    • Enabling agents in your Flyte deployment
    • Developing agents
    • Testing agents in a local development cluster
    • Deploying agents to the Flyte sandbox
    • Implementing the agent metadata service
    • How Secret Works in Agent
  • Environment setup
  • Flyte fundamentals
    • Tasks, workflows and launch plans
    • Registering workflows
    • Running and scheduling workflows
    • Running and developing workflows in Jupyter notebooks
    • Visualizing task input and output
    • Optimizing tasks
    • Extending Flyte

Glossary

  • Main concepts
    • Tasks
    • Workflows
    • Nodes
    • Launch plans
    • Schedules
    • Registration
    • Executions
    • Understanding the State Transition in a Workflow
    • Timeline of a workflow execution
    • Understand How Flyte Handles Data
    • How to Use Flyte UI
    • What is Data Catalog?
    • Versions
    • Understand the Lifecycle of a Flyte Workflow
  • Control Plane
    • Projects
    • Domains
    • FlyteAdmin
    • FlyteConsole
    • Dynamic Job Spec
  • Component Architecture
    • FlytePropeller Architecture
    • Flyte Native Scheduler Architecture

Ecosystem

  • flytekit-java
  • pterodactyl
  • latch sdk
  • User guide
  • Control Plane

Control Plane#

  • Projects
  • Domains
  • FlyteAdmin
  • FlyteConsole
  • Dynamic Job Spec

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