DP-700 Implement and Manage an Analytics Solution Practice Question
An organization is using the 'Fabric Capacity Metrics' app to monitor their F64 capacity. They see a high 'Background rejection' rate. What does this indicator typically mean for the analytics solution?
⚠ Common exam trap
Candidates often confuse 'Background rejection' with 'Interactive throttling', failing to realize that background rejections specifically target automated tasks when the capacity's smoothing window is completely exhausted.
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
✓
Scheduled jobs and refreshes are being throttled due to capacity exhaustion.
Background rejection occurs when the capacity has exhausted its available units and the 'smoothing' window for background tasks (like scheduled refreshes or notebook jobs) is full. Unlike interactive tasks, which may experience latency, background tasks are rejected if they cannot be accommodated within the capacity's future limits. Monitoring this metric is vital for right-sizing the capacity for automated workloads.
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 firewall is blocking requests from unauthorized IP addresses.
Why it's wrong here
Rejection in the context of the Capacity Metrics app refers to resource exhaustion rather than network security or firewall rules. While 'rejection' sounds like a security event, it is actually a throttling mechanism used by Fabric to protect the stability of the compute environment. Network blocks would be handled at the gateway or tenant level, not reported as background compute rejection.
- ✓
Scheduled jobs and refreshes are being throttled due to capacity exhaustion.
Why this is correct
Background rejection is the specific metric that tracks when non-interactive tasks, such as scheduled Power BI refreshes or Data Factory pipelines, are stopped because the capacity is over-utilized. Fabric uses smoothing to spread load, but if the long-term usage exceeds the SKU's limits, it starts rejecting new background requests. This signifies a need to optimize code or scale the capacity.
- ✗
The OneLake storage limit has been exceeded for the tenant.
Why it's wrong here
Capacity metrics track compute usage (CUs), whereas storage is a separate metric that does not usually result in 'rejection' of notebook tasks in this manner. OneLake storage is generally scalable and does not throttle background processing based on the amount of data stored. Rejection is strictly a compute-bound event related to the F-SKU or P-SKU limitations.
- ✗
User login attempts to the Fabric portal are failing.
Why it's wrong here
User authentication is managed by Microsoft Entra ID and is not reflected as 'Background rejection' in the Fabric Capacity Metrics app. This metric specifically relates to the execution of items like notebooks, pipelines, and semantic models. Authentication failures would be found in the sign-in logs of the Azure portal rather than the compute performance dashboards.
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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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