Overview
Optimizing Power Automate performance ensures that flows run efficiently, reduce execution time, and minimize failures. By following best practices, you can enhance speed, reliability, and scalability.
1️⃣ Optimize Triggers for Efficiency
🔹 Avoid Trigger Overuse – Use specific conditions to prevent unnecessary flow executions.
🔹 Filter in the Trigger (Not in the Flow) – Use trigger conditions instead of applying filters later.
🔹 Use Polling Triggers Sparingly – Avoid using frequent scheduled triggers; use event-based triggers where possible.
Example:
Instead of: Running a flow every 5 minutes to check for new SharePoint items
Do this: Use the “When an item is created” trigger to run only when needed
2️⃣ Use Filter Queries Instead of “Apply to Each” Loops
🔹 Use OData Filters in connectors like SharePoint, Dataverse, and SQL to retrieve only the necessary data.
🔹 Avoid fetching all records and then filtering within Power Automate.
Example (SharePoint Filter Query):
Instead of: Retrieving all list items and filtering in a condition
Do this: Use an OData filter in “Get Items”
Status eq 'Approved'
🔹 This reduces the number of records retrieved and improves performance.
3️⃣ Reduce “Apply to Each” Loops
🔹 Avoid unnecessary iterations by using array functions like union(), filter(), and select().
🔹 Use Parallelism – Enable concurrency settings to process multiple loop items simultaneously.
Example:
Instead of: Iterating through 1,000 SharePoint records
Do this: Use “Select” to extract specific values into an array for processing.
4️⃣ Optimize Data Operations
🔹 Use “Select” & “Filter Array” Instead of looping over data manually.
🔹 Use “Compose” Action for calculations instead of variables when possible (faster execution).
🔹 Use Batch Processing (for SQL, Dataverse, SharePoint) to update records in bulk instead of one by one.
Example:
Use “Filter Array” instead of looping through records with a condition.
5️⃣ Limit the Number of Actions in a Flow
🔹 Too many actions increase execution time. Optimize by combining steps where possible.
🔹 Use OneDrive/SharePoint Automate Functions instead of multiple actions (e.g., renaming files).
Example:
Use “Append to String Variable” instead of multiple “Set Variable” actions in loops.
6️⃣ Optimize API Calls & External Integrations
🔹 Minimize Unnecessary API Calls – Avoid fetching more data than required.
🔹 Use “Delay” Action Sparingly – API rate limits may cause failures if too many requests are sent in a short time.
🔹 Enable Retry Policy – Set appropriate retry intervals for API failures.
Example (HTTP Request Optimization):
Use the “Expand Query” Parameter in Dataverse API to fetch related records in one call.
7️⃣ Use Parallelism for Faster Execution
🔹 Enable concurrency settings in “Apply to Each” for parallel execution.
🔹 For actions like approvals, sending emails, and HTTP requests, enable parallel processing.
Example:
Enable Parallelism in “Apply to Each” to process multiple items simultaneously.
8️⃣ Minimize Flow Runs to Save Resources
🔹 Use trigger conditions to prevent flows from running unnecessarily.
🔹 Combine multiple conditions into a single step instead of using multiple conditional checks.
🔹 Terminate flow early if conditions are not met.
Example (Trigger Condition for Approval Flow):
Only trigger if “Status” = “Pending”
@equals(triggerBody()?['Status'], 'Pending')
9️⃣ Manage Large Datasets Efficiently
🔹 Use Pagination when retrieving large datasets (Dataverse, SharePoint, SQL).
🔹 Limit Row Fetching – Set row limits in “Get Items” or “List Records” actions.
🔹 Use “Skip” & “Top” Parameters to handle large datasets in batches.
Example:
Enable Pagination in SharePoint “Get Items” to fetch more than 100 records.