Hi Jaume Amores,
Thanks for the question.
If you want to access the job that is currently running your pipeline, Azure ML doesn’t provide a direct “get current job” command during execution. However, you can still access the job information in a couple of easy ways.
1. Use environment variables inside the job When a job is running, Azure ML automatically injects variables like the run ID and job name. For example, in Python you can get them like this:
import os
print(os.getenv("AZUREML_RUN_ID"))
print(os.getenv("AZUREML_JOB_NAME"))
You can then use these values to query more job details using the MLClient.
2. Use the Azure ML SDK to fetch job details If you know the job name or run ID, you can retrieve full information:
job = ml_client.jobs.get(job_name)
print(job.status)
3. Check the portal You can always open Azure ML Studio → Jobs to see the run that executed your pipeline, including logs, outputs, and metadata.
Hope this helps! Let me know if you need any further assistance.
Thankyou!