Core concepts

An LLM-optimized bundle of this entire section is available at section.md. This single file contains all pages in this section, optimized for AI coding agent context.

Now that you’ve completed the Quickstart, let’s explore Flyte’s core concepts through working examples.

By the end of this section, you’ll understand:

  • TaskEnvironment: The container configuration that defines where and how your code runs
  • Tasks: Python functions that execute remotely in containers
  • Runs and Actions: How Flyte tracks and manages your executions
  • Apps: Long-running services for APIs, dashboards, and inference endpoints

Each concept is introduced with a practical example you can run yourself.

How Flyte works

When you run code with Flyte, here’s what happens:

  1. You define a TaskEnvironment that specifies the container image and resources
  2. You decorate Python functions with @env.task to create tasks
  3. When you execute a task, Flyte creates a run that tracks the execution
  4. Each task execution within a run is an action

Let’s explore each of these in detail.