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DP-203 Practice Question: Which THREE metrics from Azure Monitor should be…
Which THREE metrics from Azure Monitor should be used to diagnose performance bottlenecks in an Azure Data Factory pipeline?
⚠ Common exam trap
Watch out — candidates often confuse storage-level metrics (like Blob Capacity) or data warehouse metrics (like DWU Used) with pipeline-specific performance indicators, but the question explicitly asks for metrics that diagnose bottlenecks in the pipeline execution itself, not in downstream storage or compute services.
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
✓
Pipeline Succeeded Rerun Count
Pipeline Succeeded Rerun Count (A) is correct because a high number of reruns indicates that the pipeline is repeatedly failing and retrying, which directly points to a performance bottleneck such as resource contention or throttling. This metric helps identify pipelines that are not completing successfully on the first attempt, signaling underlying issues that degrade throughput.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Pipeline Succeeded Rerun Count
Why this is correct
High rerun count indicates failures and potential bottlenecks.
- ✗
Blob Capacity
Why it's wrong here
Storage metric, not pipeline performance.
- ✓
Activity Duration
Why this is correct
Directly measures execution time of each activity.
- ✗
SQL Pool DWU Used
Why it's wrong here
Metric for Synapse SQL pool, not ADF.
- ✓
Data Integration Unit (DIU) Consumption
Why this is correct
Indicates if copy activity is resource constrained.
Go deeper
Related to this question
Learn chapter
Introduction to Azure Data Engineering
Key term
Data Transformation Pipelines
Data transformation pipelines are automated sequences of steps that take raw data from a source, clean and reshape it into a usable format, and then load it into a destination for analysis or storage.
Key term
Azure Data Factory
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-203 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-203 exam.