Explanation

Explanation pages help you understand how the plugin works and the reasoning behind its design. Read these when you want to build a mental model of the system rather than accomplish a specific task.

• Concepts: Core ideas behind the plugin, how Kedro and Azure ML fit together, and key features.
• Architecture Overview: How the plugin translates Kedro pipelines into Azure ML pipeline jobs, the two execution contexts, and the compilation process.
• Data Flow Between Steps: How data moves between pipeline steps during remote execution, the three dataset paths, and how the runner rewires paths at runtime.
• Hook Lifecycle in Remote Execution: How the full Kedro hook lifecycle is preserved in remote steps, the bootstrap sequence, and kedro-mlflow coordination.