PL-900 Practice Question: Demonstrate the capabilities of Power Automate
A Power Automate flow uses an 'Apply to each' loop to iterate over a large dataset. The flow is running slowly and sometimes times out. Which approach should the administrator recommend to improve performance?
⚠ Common exam trap
PL-900 often tests the misconception that increasing timeout or splitting flows solves performance issues; candidates may pick 'increase timeout' because it sounds like a quick fix, but the real solution is enabling concurrency to parallelize the loop.
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' loop.
Enabling concurrency control on the 'Apply to each' loop allows multiple iterations to run in parallel, dramatically reducing the total execution time for large datasets. By default, the loop runs sequentially, so each iteration waits for the previous one to finish. Setting concurrency (e.g., 10 or 20) lets Power Automate process multiple items simultaneously, improving throughput and reducing timeout risk.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Split the dataset into multiple flows.
Why it's wrong here
Splitting into multiple flows multiplies trigger overhead and connector calls without reducing total iterations, so timeouts persist. It is tempting because parallel flows appear to divide the workload. The real gain comes from enabling concurrency on the loop or filtering the source query, which cuts the number of iterations.
- ✗
Increase the flow timeout setting to 1 hour.
Why it's wrong here
Raising the timeout only postpones the failure; the loop still processes the same volume serially, so runs remain slow and eventually exceed any limit. It is tempting because timeout errors name the setting directly. Enabling loop concurrency or reducing items retrieved addresses the actual serial iteration bottleneck.
- ✓
Enable concurrency control on the 'Apply to each' loop.
Why this is correct
Enabling concurrency control lets the 'Apply to each' loop run multiple iterations in parallel rather than sequentially, directly addressing the slow runtime and timeout constraint. Power Automate processes iterations simultaneously up to the configured degree, cutting total duration for large datasets. This is the supported performance setting for loop-heavy flows.
- ✗
Use a premium connector for the data source.
Why it's wrong here
A premium connector changes licensing and available actions, not the per-iteration latency that causes the timeout; the loop still executes sequentially. It is tempting because premium connectors often expose batch operations. The fix is enabling concurrency on 'Apply to each' or filtering the source query to return fewer records.
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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 PL-900 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 PL-900 exam.