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?
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, significantly improving performance for large datasets and reducing the risk of timeouts. Option A is incorrect because splitting the dataset into multiple flows does not address the root cause and adds administrative complexity. Option B is incorrect because increasing the timeout does not make the flow run faster; it merely extends the allowed duration, but the flow may still be slow and could hit other limits. Option D is incorrect because using a premium connector provides access to more APIs or higher limits but does not inherently speed up loop iterations; performance gains come from parallelism.
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 adds overhead.
- ✗
Increase the flow timeout setting to 1 hour.
Why it's wrong here
Timeout increase doesn't improve speed.
- ✓
Enable concurrency control on the 'Apply to each' loop.
Why this is correct
Concurrency allows parallel processing of items.
- ✗
Use a premium connector for the data source.
Why it's wrong here
Premium connectors don't inherently improve performance.
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