You train and publish a machine learning model. You need to run a pipeline that retrains the model based on a trigger from an external system. What should you configure?

The correct answer is C. Azure Logic App. Azure Logic Apps is the correct service for triggering an Azure Machine Learning pipeline retraining run based on an external system event. A published Azure ML pipeline exposes a REST endpoint that can be called programmatically. Logic Apps can receive HTTP requests or events…

Train and deploy models

Question

You train and publish a machine learning model. You need to run a pipeline that retrains the model based on a trigger from an external system. What should you configure?

Options

AAzure Data Catalog
BAzure Batch
CAzure Logic App

How the community answered

(48 responses)

A
8% (4)
B
21% (10)
C
71% (34)

Explanation

Azure Logic Apps is the correct service for triggering an Azure Machine Learning pipeline retraining run based on an external system event. A published Azure ML pipeline exposes a REST endpoint that can be called programmatically. Logic Apps can receive HTTP requests or events from virtually any external system (via hundreds of built-in connectors or webhook triggers) and then call the Azure ML pipeline's REST endpoint to initiate a retraining run. Azure Data Catalog is a metadata and data governance service with no pipeline-triggering capability. Azure Batch is a high-performance computing service for running large-scale parallel workloads and does not provide event-driven workflow orchestration to connect external triggers to ML pipelines.

Topics

#MLOps#Workflow Automation#External Triggers#Azure Logic Apps

Community Discussion

No community discussion yet for this question.

Full DP-100 Practice