What is Kubeflow Pipeline ( KFP)

 Yes, this is a single pipeline execution in Kubeflow Pipelines (KFP).

Let’s break down how it works:

How KFP Pipelines Work

In KFP, a "pipeline" is a single workflow run, composed of several "steps" (called components or ops).

Each component can be implemented as a Python function or container, and these are chained together to define data flow.

Your Pipeline Structure

In your provided code, the pipeline function calls:

process_data – handles data processing, outputs processed data.

ingest_data – takes the output from process_data and ingests it into the datastore.

Both steps are part of the same pipeline run/execution.

Execution Flow

When you trigger this pipeline (e.g., via the KFP UI or API), Kubeflow schedules and runs "process_data" first.

Once "process_data" finishes (and produces its output), "ingest_data" starts, using the output from the previous step.

Both steps are executed as part of a single pipeline run with the specified parameters.

The entire workflow (from processing to ingestion) is considered one pipeline execution.

In Summary

All steps inside a pipeline function are executed as a single pipeline run.

Each call to a component (like process_data and ingest_data) becomes an "operation" (step) in the pipeline’s Directed Acyclic Graph (DAG).

Their order and data passing is controlled by their arrangement (and dependencies, e.g., ingest_data uses the output of process_data).

Visual Representation (Simplified)

text

[process_data] ---> [ingest_data]

      (step 1)           (step 2)

   (both belong to the SAME pipeline run)

In summary:

Even though your pipeline calls two separate components, the whole process—from data processing to ingestion—is executed as one, single pipeline execution in KFP. All the steps defined in the pipeline function make up a single workflow.