DP-700 Monitor and Optimize an Analytics Solution Practice Question
You are analyzing a performance bottleneck using the 'Timepoint Detail' page in the Fabric Capacity Metrics app. Which THREE pieces of information can you find here to help identify the specific cause of a capacity overage? (Select THREE)
⚠ Common exam trap
Candidates mistakenly assume the Timepoint Detail page displays aggregated trends over days or weeks, missing its true purpose as a highly granular 30-second window view.
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
✓
The name of the operation and the item that triggered it.
The Timepoint Detail page is the most granular view in the Capacity Metrics app. It allows you to see exactly what was happening during a specific 30-second window when the capacity was under load. This detail is essential for identifying 'noisy neighbors' or specific jobs that are consuming more than their fair share of resources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The name of the operation and the item that triggered it.
Why this is correct
Knowing the specific operation (e.g., 'Execute Notebook' or 'SQL Query') and the item (the specific notebook or report name) is crucial for identifying which workload is responsible for a spike in CU usage. This allows you to target your optimization efforts on the most impactful items.
- ✓
The amount of 'Base' and 'Burst' CUs consumed by each operation.
Why this is correct
Fabric distinguishes between base CU usage and burst usage. Seeing this breakdown helps you understand if an operation is consistently heavy or if it just had a short-lived peak. This distinction is important for understanding how smoothing will affect the capacity's health over the longer 24-hour window.
- ✓
The user ID of the person who initiated the operation.
Why this is correct
Identifying the user who triggered a resource-intensive task allows for better communication and governance. You can work with the user to optimize their query or reschedule their job to a less busy time, which is a key part of managing a shared analytics environment effectively.
- ✗
The physical IP address of the Spark executor nodes.
Why it's wrong here
The Capacity Metrics app is a high-level management tool and does not provide low-level networking or infrastructure details like individual IP addresses of compute nodes. Such information is abstracted away by the Fabric platform and is generally not relevant for capacity-level performance tuning or cost management.
- ✗
The SQL execution plan for every query in the timepoint.
Why it's wrong here
The Capacity Metrics app shows that a SQL query ran and how many CUs it used, but it does not store or display the full execution plans. To see execution plans, you must use the SQL Analytics Endpoint's own management views or the Query Insights feature within the workspace.
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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
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