DP-700 Monitor and Optimize an Analytics Solution Practice Question
When a Spark notebook job finishes, what is the best practice for managing the underlying compute cluster resources?
⚠ Common exam trap
Candidates often suggest manually stopping the cluster or deleting the notebook. They overlook the built-in 'automatic termination' feature, which is the most efficient and standard best practice for resource management.
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
✓
Configure automatic termination for idle sessions
Proper cluster management is vital to avoid unnecessary costs. In Fabric, dynamic allocation and efficient session management ensure that resources are released as soon as they are idle. Keeping a cluster running unnecessarily consumes capacity units, which directly impacts your budget and availability for other concurrent workloads that may need those same resources to function properly.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Keep the cluster running for 24 hours
Why it's wrong here
Keeping a cluster running when idle is wasteful. It unnecessarily consumes capacity units without performing useful work, leading to higher costs and reducing the amount of compute available for other active jobs that may require that capacity to execute their tasks.
- ✓
Configure automatic termination for idle sessions
Why this is correct
Automatic termination ensures that compute resources are released back to the capacity as soon as a session becomes idle. This is a best practice for cost efficiency, preventing 'compute leakage' and ensuring that your capacity is always available for active, high-priority workloads.
- ✗
Manually restart the cluster every hour
Why it's wrong here
Manually restarting clusters is inefficient and introduces unnecessary downtime. It disrupts ongoing operations and adds operational overhead without providing any benefit, as modern managed Spark environments in Fabric are designed to handle resource scaling and cleanup automatically.
- ✗
Increase the cluster size to max nodes
Why it's wrong here
Increasing cluster size without a valid workload requirement significantly increases costs. Larger clusters consume more capacity units, and unless the job specifically requires the extra compute power for parallel processing, it is an inefficient use of resources that negatively impacts your budget.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This DP-700 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-700 exam.