Testing the Deployment
Learn how to invoke batch and online deployments.
Testing a batch endpoint
We will test the deployments in this lesson. Let’s start with batch deployment. We can pass the test data in a file. We will run the az ml batch-deployment invoke command to verify the test data against the deployment. It will pick up the endpoint’s default deployment if we don’t pass the deployment name. We will test against the batch-depl, which contains the iris MLflow model.
sepal_length,sepal_width,petal_length,petal_width 5.10E+00,3.50E+00,1.40E+00,2.00E-01 4.90E+00,3.00E+00,1.40E+00,2.00E-01 4.70E+00,3.20E+00,1.30E+00,2.00E-01 4.60E+00,3.10E+00,1.50E+00,2.00E-01 5.00E+00,3.60E+00,1.40E+00,2.00E-01
Running a batch job
We can visualize the results of the job in Azure Machine Learning studio. We can see the “Data” and “batchscoring” jobs.
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Batch deployment workflow in Azure Machine Learning studio
Click on the batchscoring job output, and the data will be accessed in the predictions.csv output log. This file contains the predicted values for the ...