PL-900 Practice Question: Demonstrate the capabilities of Power Automate
A Power Automate flow uses the 'Apply to each' action to process items from a SharePoint list. The flow is running slowly. What is the most effective way to improve performance?
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
✓
Enable concurrency control on the 'Apply to each' action.
Enabling concurrency control on the 'Apply to each' action allows multiple iterations to run in parallel, significantly reducing total processing time. Option A adds a condition inside the loop, which does not improve performance and may even add overhead. Option B replaces the loop with a 'Do until' loop, which still processes items sequentially. Option D reduces the number of items, which is not always feasible and does not improve the flow's efficiency when processing large lists.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add a 'Condition' action inside the loop.
Why it's wrong here
A Condition inside the loop adds a branch evaluation per item, increasing work rather than reducing it, so performance does not improve. It is tempting because filtering items feels like it avoids processing, and would be correct if the condition sat before the loop to exclude items from iteration entirely.
- ✗
Use a 'Do until' loop instead.
Why it's wrong here
'Do until' repeats until a condition is met and offers no concurrency or batching advantage over 'Apply to each', so it does not speed up list processing. It is tempting because both are loops, and 'Do until' would be correct when the number of iterations is unknown and depends on a runtime condition.
- ✓
Enable concurrency control on the 'Apply to each' action.
Why this is correct
Concurrency control lets the 'Apply to each' action process multiple SharePoint items in parallel rather than sequentially, directly cutting total runtime. This addresses the stem's slow-flow constraint by raising throughput without altering the loop's logic.
- ✗
Reduce the number of items in the list.
Why it's wrong here
Reducing list items changes the data, not the flow's execution; the stem asks how to improve the flow's performance, and deleting records is a data-management action outside the flow design. It is tempting because fewer items means less work, and would be correct if the list genuinely held obsolete records.
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