AI-300 ML Model Lifecycle And Operations Practice Question
A team uses Azure Machine Learning to track experiments. You need to ensure that every run is associated with a specific git commit hash to ensure reproducibility. Where should this be configured?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Within the 'experiment.start_logging()' call using the 'tags' parameter.
The 'run_configuration' or the 'Environment' object can be used to inject metadata, but standard practice is to use the 'tags' or 'properties' dictionary during the 'start_logging' or 'init' call.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
In the 'workspace.json' file.
Why it's wrong here
This is for workspace connection details.
- ✗
By modifying the compute cluster configuration.
Why it's wrong here
Compute clusters are for execution, not metadata.
- ✓
Within the 'experiment.start_logging()' call using the 'tags' parameter.
Why this is correct
This is the standard way to attach metadata to a run.
- ✗
Inside the 'conda_dependencies.yml' file.
Why it's wrong here
This is for library dependencies.
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Last reviewed August 2026 · checked against the official Microsoft exam blueprint
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