Automating Power Platform Performance Monitoring using PowerShell

Power Platform performance monitoring helps in identifying slow apps, inefficient flows, and resource bottlenecks. Automating this process using PowerShell ensures proactive detection and resolution of performance issues.

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Step 1: Prerequisites

1.1 Install Required PowerShell Modules

Ensure the required modules are installed:

Install-Module -Name Microsoft.PowerApps.Administration.PowerShell -Force
Install-Module -Name Microsoft.PowerApps.PowerShell -Force

1.2 Authenticate to Power Platform

Add-PowerAppsAccount

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Step 2: Monitoring Performance Metrics

2.1 Retrieve Power Apps Performance Data

Get a list of Power Apps and their performance metrics:

Get-AdminPowerApp | Select-Object DisplayName, AppId, EnvironmentName, CreatedTime

Check slow-running apps (apps taking longer than 2 seconds to load):

Get-AdminPowerAppPerformance -EnvironmentName "your-env-id" | Where-Object { $_.AvgLoadTime -gt 2 } | 
Select-Object AppName, AvgLoadTime, UserCount

2.2 Retrieve Flow Performance Data

Identify flows with high execution times:

Get-AdminFlowRun -EnvironmentName "your-env-id" | Where-Object { $_.Duration -gt 5000 } | 
Select-Object FlowName, Status, Duration, StartTime

(Duration is in milliseconds)

2.3 Check Dataverse Query Performance

Identify slow Dataverse queries:

Get-CrmEntityPerformance -EnvironmentName "your-env-id" | 
Where-Object { $_.AverageResponseTime -gt 500 } |
Select-Object EntityName, AverageResponseTime, RequestCount

(Average response time is in milliseconds)

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Step 3: Automating Performance Monitoring

3.1 Create a Scheduled PowerShell Script

Save the following script as Monitor-PowerPlatform.ps1:

$envName = "your-env-id"

# Authenticate
Add-PowerAppsAccount

# Retrieve slow Power Apps
$slowApps = Get-AdminPowerAppPerformance -EnvironmentName $envName | Where-Object { $_.AvgLoadTime -gt 2 }
$slowApps | Export-Csv -Path "C:\Logs\SlowApps.csv" -NoTypeInformation

# Retrieve slow Power Automate Flows
$slowFlows = Get-AdminFlowRun -EnvironmentName $envName | Where-Object { $_.Duration -gt 5000 }
$slowFlows | Export-Csv -Path "C:\Logs\SlowFlows.csv" -NoTypeInformation

# Retrieve slow Dataverse queries
$slowQueries = Get-CrmEntityPerformance -EnvironmentName $envName | Where-Object { $_.AverageResponseTime -gt 500 }
$slowQueries | Export-Csv -Path "C:\Logs\SlowQueries.csv" -NoTypeInformation

Write-Host "Performance data exported to C:\Logs\"

3.2 Schedule the Script to Run Daily

To automate execution, create a Windows Task Scheduler job:

1. Open Task Scheduler
2. Click Create Basic Task
3. Set a Trigger (Daily at 12 AM)
4. Set Action → Start a Program
5. Browse for powershell.exe
6. Add arguments: -File "C:\Scripts\Monitor-PowerPlatform.ps1"
7. Click Finish

This ensures the script runs daily and exports performance logs automatically.

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Step 4: Sending Performance Reports via Email

Modify the script to send reports via email:

$SMTPServer = "smtp.office365.com"
$SMTPPort = "587"
$EmailFrom = "your-email@domain.com"
$EmailTo = "admin@domain.com"
$Subject = "Power Platform Performance Report"
$Body = "Attached are the latest Power Platform performance logs."
$Username = "your-email@domain.com"
$Password = "your-email-password"

$securePassword = ConvertTo-SecureString $Password -AsPlainText -Force
$cred = New-Object System.Management.Automation.PSCredential ($Username, $securePassword)

$attachments = @("C:\Logs\SlowApps.csv", "C:\Logs\SlowFlows.csv", "C:\Logs\SlowQueries.csv")

Send-MailMessage -To $EmailTo -From $EmailFrom -Subject $Subject -Body $Body -SmtpServer $SMTPServer -Port $SMTPPort -Credential $cred -UseSsl -Attachments $attachments

This sends performance logs to administrators automatically.

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Step 5: Analyzing Logs with Power BI

To visualize performance trends, load CSV logs into Power BI:

1. Open Power BI Desktop
2. Click Get Data → CSV
3. Load SlowApps.csv, SlowFlows.csv, SlowQueries.csv
4. Create charts for trends in:
   • App load times
   • Flow execution duration
   • Dataverse response times

Power BI helps track performance over time and identify recurring issues.