DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are monitoring an Azure Data Factory pipeline that runs daily to load data from an on-premises SQL Server to Azure Synapse Analytics. The pipeline has been failing intermittently with timeout errors. You need to configure alerts to notify the team when the pipeline fails. What is the most efficient way to achieve this?
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
✓
Create an alert rule in Azure Monitor using the 'Pipeline failed runs' metric.
The most efficient way to alert on pipeline failures is to create an alert rule in Azure Monitor using the 'Pipeline failed runs' metric (Option C). This metric is specific to Data Factory and allows direct alerting without additional logging setup. Option A is inefficient because it requires enabling diagnostic settings and creating a log search alert, adding latency and cost. Option B, Azure Service Health alerts, only notify about Azure service health issues, not pipeline failures. Option D, Microsoft Defender XDR, is a security solution unrelated to pipeline monitoring.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable diagnostic settings to send pipeline logs to a Log Analytics workspace and create a log search alert.
Why it's wrong here
Enabling diagnostic settings to Log Analytics and creating a log search alert, whilst functional for detecting failures, is not the most efficient approach for simple pipeline failure notifications. This method involves more setup and query creation than necessary for a basic status alert. It is, however, highly valuable for complex scenarios requiring deep analysis, custom error pattern detection, or correlating events across multiple Azure Data Factory runs and other resources, providing comprehensive insights and auditing capabilities.
- ✗
Use Azure Service Health alerts to notify when Data Factory is unhealthy.
Why it's wrong here
Service Health alerts are for Azure platform issues, not specific pipeline failures.
- ✓
Create an alert rule in Azure Monitor using the 'Pipeline failed runs' metric.
Why this is correct
Azure Data Factory exposes pipeline run metrics in Azure Monitor, allowing direct alert creation based on failures.
- ✗
Configure Microsoft Defender XDR to monitor pipeline activities.
Why it's wrong here
Microsoft Defender XDR is for security threat detection, not pipeline operational failures.
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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JA
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.