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Metrics export using data collection rules

Platform metrics measure the performance of different aspects of your Azure resources. Platform telemetry data collection rules (DCRs) let you collect and export platform metrics from supported Azure resources. This article shows you how to create a DCR for metrics export.

Note

While you can use DCRs and diagnostic settings at the same time, you should disable any diagnostic settings for metrics when using DCRs to avoid duplicate data collection.

Compare to diagnostic settings

Before this feature, you could only export platform metrics by using diagnostic settings. Diagnostic settings are still required for resource types that don't yet support DCRs.

Platform telemetry DCRs provide several benefits over diagnostic settings:

DCR configuration enables exporting metrics with dimensions.
DCR configuration enables filtering based on metric name so you can export only the metrics that you need.
DCRs are more flexible and scalable than diagnostic settings. Use a single DCR with multiple resources, while a separate diagnostic setting is required for each resource.
End-to-end latency for DCRs is within three minutes, while diagnostic settings export latency is six to ten minutes.

Note

Use metrics export with DCRs for continuous export of metrics data as it's created. To query historical data that's already been collected, use the Data plane Metrics Batch API. See Data plane Metrics Batch API query versus Metrics export for a comparison of the two strategies.

Export destinations

Metrics can be exported to the following destinations.

Destination type	Details
Log Analytics workspaces	Exporting to Log Analytics workspaces can be across regions. The Log Analytics workspace and the DCR must be in the same region but resources that are being monitored can be in any region. Metrics sent to a log analytics workspace are stored in the `AzureMetricsV2` table.
Azure storage accounts	The storage account, the DCR, and the resources being monitored must all be in the same region.
Event Hubs	The Event Hubs, the DCR, and the resources being monitored must all be in the same region.

Note

Latency for exporting metrics is approximately 3 minutes. Allow up to 15 minutes for metrics to begin to appear in the destination after the initial setup.

Limitations

DCRs for metrics export have the following limitations:

Only one destination type can be specified per DCR. To send to multiple destinations, create multiple DCRs.
A maximum of 5 DCRs can be associated with a single Azure resource.
Metrics export with DCR doesn't support the export of hourly grain metrics.

Supported resources and regions

For the current list of supported resources and supported regions, see Metrics export supported resources and regions.

Create a data collection rule (DCR) for metrics export

This article describes how to create a data collection rule (DCR) for metrics export using the Azure portal, Azure CLI, PowerShell, API, or ARM templates.

Important

To send Platform Telemetry data to Storage Accounts or Event Hubs, the resource, data collection rule, and the destination Storage Account or the Event Hubs must all be in the same region.

Create a data collection rule using the Azure portal

On the Monitor menu in the Azure portal, select Data Collection Rules and then Create.
Select the link on the top of the page to use the new DCR creation experience.

👁 A screenshot showing the create data collection rule page.
On the Create Data Collection Rule page, enter a rule name, select a Subscription, Resource group, and Region for the DCR.
Select PlatformTelemetry for the Type of telemetry and Enable Managed Identity if you want to send metrics to a Storage Account or Event Hubs.

👁 A screenshot showing the basics tab of the create data collection rule page.
On the Resources page, select Add resources to add the resources you want to collect metrics from.
Select Next to move to the Collect and deliver tab.

👁 A screenshot showing the resources tab of the create data collection rule page.
Select Add new datasource.
The resource type of the resource specified in the previous step is automatically selected. Add more resource types if you want to use this rule to collect metrics from multiple resource types in the future. Select the Actions for a resource type if you want to remove some of the metrics collected for it. By default, all available metrics for the resource are collected.

👁 A screenshot showing the collect and deliver tab of the create data collection rule page.
Select Next Destinations to move to the Destinations tab.
Select Add destination and then the Destination type that you want to add. The required fields change based on the destination type you select.

Note

To send metrics to a Storage Account or Event Hubs, the resource generating the metrics, the DCR, and the Storage Account or Event Hub, must all be in the same region. To send metrics to a Log Analytics workspace, the DCR must be in the same region as the Log Analytics workspace. The resource generating the metrics can be in any region.

👁 A screenshot showing the destination tab of collect and deliver page.
Select Save , then select Review + create.

Create a data collection rule using Azure CLI

Create a JSON file containing the collection rule specification. For more information, see Data collection rule (DCR) structure for metrics export. For sample JSON files, see Sample Metrics Export JSON objects.

Important

The rule file has the same format as used for PowerShell and the REST API, however the file must not contain identity, the location, or kind. These parameters are specified in the az monitor data-collection rule create command.

The following Azure CLI example uses the az monitor data-collection rule create command.

subscriptionId="aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e"
resourceGroupName="myResourceGroup"
dataCollectionRuleName="myDataCollectionRule"
location="eastus"
ruleFile="./cli-dcr.json"

az account set --subscription "$subscriptionId"

az monitor data-collection rule create \
 --name "$dataCollectionRuleName" \
 --resource-group "$resourceGroupName" \
 --location "$location" \
 --kind PlatformTelemetry \
 --identity "{type:'SystemAssigned'}" \
 --rule-file "$ruleFile"

Note

Azure CLI commands use the Azure Resource Manager endpoint from the current CLI context, so management.azure.com doesn't need to be specified in the command syntax.
For storage account and Event Hubs destinations, you must enable managed identity for the DCR using --identity "{type:'SystemAssigned'}". Identity isn't required for Log Analytics workspaces.

Copy the id and the principalId of the DCR from the following output to use in assigning the role to create an association between the DCR and a resource.

Output:

"id": "/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/myResourceGroup/providers/Microsoft.Insights/dataCollectionRules/myDataCollectionRule",
"identity": {
 "principalId": "eeeeeeee-ffff-aaaa-5555-666666666666",
 "tenantId": "aaaabbbb-0000-cccc-1111-dddd2222eeee",
 "type": "systemAssigned"
},

Grant write permissions to the managed identity

The managed identity used by the DCR must have write permissions to the destination when the destination is a Storage Account or Event Hubs. To grant permissions for the rule's managed identity, assign the appropriate role to the entity.

The following table shows the roles required for each destination type:

Destination type	Role
Log Analytics workspace	not required
Azure storage account	`Storage Blob Data Contributor`
Event Hubs	`Azure Event Hubs Data Sender`

For more information on assigning roles, see Assign Azure roles to a managed identity.

To assign a role to a managed identity using CLI, use az role assignment create. For more information, see Role Assignments - Create.

Assign the appropriate role to the managed identity of the DCR. The following example assigns the Storage Blob Data Contributor role to the managed identity of the DCR for a storage account.

The following Azure CLI example uses the az role assignment create command.

subscriptionId="aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e"
resourceGroupName="myResourceGroup"
storageAccountName="myStorageAccount"
principalId="eeeeeeee-ffff-aaaa-5555-666666666666"
roleDefinitionName="Storage Blob Data Contributor"
scope="/subscriptions/$subscriptionId/resourceGroups/$resourceGroupName/providers/Microsoft.Storage/storageAccounts/$storageAccountName"

az account set --subscription "$subscriptionId"

az role assignment create \
 --assignee "$principalId" \
 --role "$roleDefinitionName" \
 --scope "$scope"

Create a data collection rule association

After you create the data collection rule, create a data collection rule association (DCRA) to associate the rule with the resource to be monitored. For more information, see Data Collection Rule Associations - Create.

The following example uses the az monitor data-collection rule association command group to create an association between a data collection rule and a Key Vault.

subscriptionId="aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e"
resourceGroupName="myResourceGroup"
associationName="myAssociation"
dataCollectionRuleName="myDataCollectionRule"
keyVaultName="myKeyVault"
dataCollectionRuleId="/subscriptions/$subscriptionId/resourceGroups/$resourceGroupName/providers/Microsoft.Insights/dataCollectionRules/$dataCollectionRuleName"
resourceUri="/subscriptions/$subscriptionId/resourceGroups/$resourceGroupName/providers/Microsoft.KeyVault/vaults/$keyVaultName"

az account set --subscription "$subscriptionId"

az monitor data-collection rule association create \
 --name "$associationName" \
 --rule-id "$dataCollectionRuleId" \
 --resource "$resourceUri"

Create a data collection rule using PowerShell

The following PowerShell example uses the New-AzDataCollectionRule cmdlet.

$subscriptionId = "aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e"
$resourceGroupName = "myResourceGroup"
$dataCollectionRuleName = "myDataCollectionRule"
$jsonFilePath = ".\dcr-storage-account.json"

Set-AzContext -Subscription $subscriptionId

$dataCollectionRuleParams = @{
 Name = $dataCollectionRuleName
 ResourceGroupName = $resourceGroupName
 JsonFilePath = $jsonFilePath
}

New-AzDataCollectionRule @dataCollectionRuleParams

Copy the id and the IdentityPrincipalId of the DCR from the following output to use in assigning the role to create an association between the DCR and a resource.

Output:

Id : /subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/myResourceGroup/providers/Microsoft.Insights/dataCollectionRules/myDataCollectionRule
IdentityPrincipalId : eeeeeeee-ffff-aaaa-5555-666666666666
IdentityTenantId : aaaabbbb-0000-cccc-1111-dddd2222eeee
IdentityType : systemAssigned
IdentityUserAssignedIdentity : {
 }

Grant write permissions to the managed identity

The following table shows the roles required for each destination type:

Destination type	Role
Log Analytics workspace	not required
Azure storage account	`Storage Blob Data Contributor`
Event Hubs	`Azure Event Hubs Data Sender`

For more information, see Assign Azure roles to a managed identity.

Assign the appropriate role to the managed identity of the DCR using New-AzRoleAssignment. The following example assigns the Azure Event Hubs Data Sender role to the managed identity of the DCR at the subscription level.

The following PowerShell example uses the New-AzRoleAssignment cmdlet.

$objectId = "eeeeeeee-ffff-aaaa-5555-666666666666"
$roleDefinitionName = "Azure Event Hubs Data Sender"
$subscriptionId = "aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e"
$scope = "/subscriptions/$subscriptionId"

Set-AzContext -Subscription $subscriptionId

$roleAssignmentParams = @{
 ObjectId = $objectId
 RoleDefinitionName = $roleDefinitionName
 Scope = $scope
}

New-AzRoleAssignment @roleAssignmentParams

Create a data collection rule association

After you create the data collection rule, create a data collection rule association (DCRA) to associate the rule with the resource to be monitored. Use New-AzDataCollectionRuleAssociation to create an association between a data collection rule and a resource. For more information, see New-AzDataCollectionRuleAssociation.

The following PowerShell example uses the New-AzDataCollectionRuleAssociation cmdlet to create an association between a data collection rule and a Key Vault.

$subscriptionId = "aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e"
$resourceGroupName = "myResourceGroup"
$associationName = "myDataCollectionRuleAssociation"
$keyVaultName = "myKeyVault"
$dataCollectionRuleName = "myDataCollectionRule"
$resourceUri = "/subscriptions/$subscriptionId/resourceGroups/$resourceGroupName/providers/Microsoft.KeyVault/vaults/$keyVaultName"
$dataCollectionRuleId = "/subscriptions/$subscriptionId/resourceGroups/$resourceGroupName/providers/Microsoft.Insights/dataCollectionRules/$dataCollectionRuleName"

Set-AzContext -Subscription $subscriptionId

$dataCollectionRuleAssociationParams = @{
 AssociationName = $associationName
 ResourceUri = $resourceUri
 DataCollectionRuleId = $dataCollectionRuleId
}

New-AzDataCollectionRuleAssociation @dataCollectionRuleAssociationParams

Creating a data collection rule for metrics requires the following steps:

Create the data collection rule.
Grant permissions for the rule's managed identity to write to the destination.
Create a data collection rule association.

Create the data collection rule

To create a DCR using the REST API, you must make an authenticated request using a bearer token. For more information on authenticating with Azure Monitor, see Authenticate Azure Monitor requests.

Use the following endpoint to create a data collection rule for metrics using the REST API. For more information, see Data Collection Rules - Create.

PUT https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Insights/dataCollectionRules/{dataCollectionRuleName}?api-version={apiVersion}
Authorization: Bearer {accessToken}
Content-Type: application/json

The payload is a JSON object that defines a collection rule. The payload is sent in the body of the request. For more information on the JSON structure, see Data collection rule (DCR) structure for metrics export. For sample DCR JSON objects, see Sample Metrics Export JSON objects.

Grant write permissions to the managed identity

The following table shows the roles required for each destination type:

Destination type	Role
Log Analytics workspace	not required
Azure storage account	`Storage Blob Data Contributor`
Event Hubs	`Azure Event Hubs Data Sender`

For more information, see Assign Azure roles to a managed identity.

To assign a role to a managed identity using REST, see Role Assignments - Create.

Create a data collection rule association

To create a DCRA using the REST API, use the following endpoint and payload:

PUT https://management.azure.com/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.Compute/virtualMachines/{virtualMachineName}/providers/Microsoft.Insights/dataCollectionRuleAssociations/{associationName}?api-version={apiVersion}
Authorization: Bearer {accessToken}
Content-Type: application/json

{
 "properties": {
 "description": "Association of platform telemetry DCR with VM myVirtualMachine",
 "dataCollectionRuleId": "/subscriptions/<subscriptionId>/resourceGroups/<resourceGroupName>/providers/Microsoft.Insights/dataCollectionRules/<dataCollectionRuleName>"
 }
}

Create a data collection rule using Bicep templates

Use the following template to create a DCR. For more information, see Microsoft.Insights dataCollectionRules.

@description('Specifies the name of the Data Collection Rule to create.')
param dataCollectionRuleName string

@description('Specifies the Log Analytics workspace.')
param workspaceId string

@description('Specifies the location in which to create the Data Collection Rule.')
param location string

resource dataCollectionRule 'Microsoft.Insights/dataCollectionRules@2024-03-11' = {
 name: dataCollectionRuleName
 kind: 'PlatformTelemetry'
 identity: {
 type: 'UserAssigned' | 'SystemAssigned'
 userAssignedIdentities: {
 type: 'string'
 }
 }
 location: location
 properties: {
 dataSources: {
 platformTelemetry: [
 {
 streams: [
 '<resourceType>:<metricName> | Metrics-Group-All'
 ]
 name: 'myPlatformTelemetryDataSource'
 }
 ]
 }
 destinations: {
 logAnalytics: [
 {
 workspaceResourceId: workspaceId
 name: 'myDestination'
 }
 ]
 }
 dataFlows: [
 {
 streams: [
 '<resourceType>:<metricName> | Metrics-Group-All'
 ]
 destinations: [
 'myDestination'
 ]
 }
 ]
 }
}

Parameters file

using './<template-name>.bicep'

param dataCollectionRuleName = 'myDataCollectionRule'

param workspaceId = '/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/myResourceGroup/providers/microsoft.operationalinsights/workspaces/myWorkspace'

param location = 'eastus'

Sample DCR template

@description('Specifies the name of the Data Collection Rule to create.')
param dataCollectionRuleName string

@description('Specifies the Log Analytics workspace.')
param workspaceId string

@description('Specifies the location in which to create the Data Collection Rule.')
param location string

resource dataCollectionRule 'Microsoft.Insights/dataCollectionRules@2024-03-11' = {
 name: dataCollectionRuleName
 location: location
 kind: 'PlatformTelemetry'
 identity: {
 type: 'SystemAssigned'
 }
 properties: {
 dataSources: {
 platformTelemetry: [
 {
 streams: [
 'Microsoft.Compute/virtualMachines:Metrics-Group-All'
 'Microsoft.Compute/virtualMachineScaleSets:Metrics-Group-All'
 'Microsoft.Cache/redis:Metrics-Group-All'
 'Microsoft.keyvault/vaults:Metrics-Group-All'
 ]
 name: 'myPlatformTelemetryDataSource'
 }
 ]
 }
 destinations: {
 logAnalytics: [
 {
 workspaceResourceId: workspaceId
 name: 'myDestination'
 }
 ]
 }
 dataFlows: [
 {
 streams: [
 'Microsoft.Compute/virtualMachines:Metrics-Group-All'
 'Microsoft.Compute/virtualMachineScaleSets:Metrics-Group-All'
 'Microsoft.Cache/redis:Metrics-Group-All'
 'Microsoft.keyvault/vaults:Metrics-Group-All'
 ]
 destinations: [
 'myDestination'
 ]
 }
 ]
 }
}

Create a data collection rule using ARM templates

Use the following template to create a DCR. For more information, see Microsoft.Insights dataCollectionRules.

{
 "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
 "contentVersion": "1.0.0.0",
 "parameters": {
 "dataCollectionRuleName": {
 "type": "string",
 "metadata": {
 "description": "Specifies the name of the Data Collection Rule to create."
 }
 },
 "workspaceId": {
 "type": "string",
 "metadata": {
 "description": "Specifies the Log Analytics workspace."
 }
 },
 "location": {
 "type": "string",
 "metadata": {
 "description": "Specifies the location in which to create the Data Collection Rule."
 }
 }
 },
 "resources": [
 {
 "type": "Microsoft.Insights/dataCollectionRules",
 "name": "[parameters('dataCollectionRuleName')]",
 "kind": "PlatformTelemetry",
 "identity": {
 "type": "UserAssigned" | "SystemAssigned",
 "userAssignedIdentities": {
 "type": "string"
 }
 },
 "location": "[parameters('location')]",
 "apiVersion": "2024-03-11",
 "properties": {
 "dataSources": {
 "platformTelemetry": [
 {
 "streams": [
 "<resourceType>:<metricName> | Metrics-Group-All"
 ],
 "name": "myPlatformTelemetryDataSource"
 }
 ]
 },
 "destinations": {
 "logAnalytics": [
 {
 "workspaceResourceId": "[parameters('workspaceId')]",
 "name": "myDestination"
 }
 ]
 },
 "dataFlows": [
 {
 "streams": [
 "<resourceType>:<metricName> | Metrics-Group-All"
 ],
 "destinations": [
 "myDestination"
 ]
 }
 ]
 }
 }
 ]
}

Parameters file

{
 "$schema": "https://schema.management.azure.com/schemas/2015-01-01/deploymentParameters.json#",
 "contentVersion": "1.0.0.0",
 "parameters": {
 "dataCollectionRuleName": {
 "value": "myDataCollectionRule"
 },
 "workspaceId": {
 "value": "/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/myResourceGroup/providers/microsoft.operationalinsights/workspaces/myWorkspace"
 },
 "location": {
 "value": "eastus"
 }
 }
}

Sample DCR template

{
 "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
 "contentVersion": "1.0.0.0",
 "resources": [
 {
 "type": "Microsoft.Insights/dataCollectionRules",
 "apiVersion": "2024-03-11",
 "name": "[parameters('dataCollectionRuleName')]",
 "location": "[parameters('location')]",
 "kind": "PlatformTelemetry",
 "identity": {
 "type": "SystemAssigned"
 },
 "properties": {
 "dataSources": {
 "platformTelemetry": [
 {
 "streams": [
 "Microsoft.Compute/virtualMachines:Metrics-Group-All",
 "Microsoft.Compute/virtualMachineScaleSets:Metrics-Group-All",
 "Microsoft.Cache/redis:Metrics-Group-All",
 "Microsoft.keyvault/vaults:Metrics-Group-All"
 ],
 "name": "myPlatformTelemetryDataSource"
 }
 ]
 },
 "destinations": {
 "logAnalytics": [
 {
 "workspaceResourceId": "[parameters('workspaceId')]",
 "name": "myDestination"
 }
 ]
 },
 "dataFlows": [
 {
 "streams": [
 "Microsoft.Compute/virtualMachines:Metrics-Group-All",
 "Microsoft.Compute/virtualMachineScaleSets:Metrics-Group-All",
 "Microsoft.Cache/redis:Metrics-Group-All",
 "Microsoft.keyvault/vaults:Metrics-Group-All"
 ],
 "destinations": [
 "myDestination"
 ]
 }
 ]
 }
 }
 ]
}

Variable	Example value	Purpose
host	management.azure.com	Implicit ARM endpoint
subscriptionId	aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e	User input
resourceGroupName	myResourceGroup	User input
dataCollectionRuleName	myDataCollectionRule	User input
associationName	myAssociation	User input
location	eastus	User input
workspaceName	myWorkspace	User input
keyVaultName	myKeyVault	User input
storageAccountName	myStorageAccount	User input
monitoredResourceName	myKeyVault	User input
apiVersion	2024-03-11	Reference

Verify data collection

After creating the DCR, allow up to 30 minutes for the first platform metrics data to appear in the Log Analytics workspace. Once data starts flowing, the latency for a platform metric time series flowing to a Log Analytics workspace, storage account, or Event Hubs is approximately three minutes, depending on the resource type.

Exported data

The following examples show the data exported to each destination.

Log Analytics workspace

Data exported to a Log Analytics workspace is stored in the AzureMetricsV2 table in the Log Analytics workspace in the following format:

Column	Type	Description
Average	real	Average value collected during in the time range.
_BilledSize	real	The record size in bytes
Count	real	Number of samples collected during the time range.
Dimension	dynamic	Associated dimension of the metric in JSON format.
_IsBillable	string	Specifies whether ingesting the data is billable. When _IsBillable is `false` ingestion isn't billed to your Azure account
Maximum	real	Maximum value collected during in the time range.
MetricCategory	string	Category name of the metric.
MetricName	string	Display name of the metric.
MetricResourceType	string	Resource type of the Azure resource reporting the metric.
Minimum	real	Minimum value collected during in the time range.
_ResourceId	string	A unique identifier for the resource that the record is associated with
SourceSystem	string	The type of agent the event was collected by. For example, `OpsManager` for Windows agent, either direct connect or Operations Manager, `Linux` for all Linux agents, or `Azure` for Azure Diagnostics
_SubscriptionId	string	A unique identifier for the subscription that the record is associated with
TenantId	string	The Log Analytics workspace ID
TimeGenerated	datetime	Timestamp (UTC) when the record was generated.
TimeGrain	string	Time grain of the metric.
Total	real	Sum of all of the values in the time range.
Type	string	The name of the table
UnitName	string	Unit of the metric.

For example:

👁 A screenshot of a log analytics query of the AzureMetricsV2 table.

Storage accounts

The following example shows data exported to a storage account:

{
 "Average": "31.5",
 "Count": "2",
 "Maximum": "52",
 "Minimum": "11",
 "Total": "63",
 "resourceId": "/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourcegroups/rg-dcrs/providers/microsoft.keyvault/vaults/dcr-vault",
 "time": "2024-08-20T14:13:00.0000000Z",
 "unit": "MilliSeconds",
 "metricName": "ServiceApiLatency",
 "timeGrain": "PT1M",
 "dimension": {
 "ActivityName": "vaultget",
 "ActivityType": "vault",
 "StatusCode": "200",
 "StatusCodeClass": "2xx"
 }
}

Event Hubs

The following example shows a metric exported to Event Hubs.

{
 "Average": "1",
 "Count": "1",
 "Maximum": "1",
 "Minimum": "1",
 "Total": "1",
 "resourceId": "/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourcegroups/rg-dcrs/providers/microsoft.keyvault/vaults/dcr-vault",
 "time": "2024-08-22T13:43:00.0000000Z",
 "unit": "Count",
 "metricName": "ServiceApiHit",
 "timeGrain": "PT1M",
 "dimension": {
 "ActivityName": "keycreate",
 "ActivityType": "key"
 },
 "EventProcessedUtcTime": "2024-08-22T13:49:17.1233030Z",
 "PartitionId": 0,
 "EventEnqueuedUtcTime": "2024-08-22T13:46:04.5570000Z"
}

Verify and troubleshoot data collection

Once you install the DCR, it may take several minutes for the changes to take effect and data to be collected with the updated DCR. If you don't see any data being collected, use the DCR monitoring features, which include metrics and logs to help troubleshooting.

DCR metrics are collected automatically for all DCRs, and you can analyze them using metrics explorer like the platform metrics for other Azure resources. Enable DCR error logs to get detailed error information when data processing isn't successful.

Check metrics such as Logs Ingestion Bytes per Min and Logs Rows Received per Min to ensure that the data is reaching Azure Monitor. If not, then check your data source to ensure that it's sending data as expected.
Check Logs Rows Dropped per Min to see if any rows are being dropped. This may not indicate an error since the rows could be dropped by a transformation. If the rows dropped is the same as Logs Rows Dropped per Min though, then no data gets ingested in the workspace. Examine the Logs Transformation Errors per Min to see if there are any transformation errors.
Check Logs Transformation Errors per Min to determine if there are any errors from transformations applied to the incoming data. This could be due to changes in the data structure or the transformation itself.
Check the DCRLogErrors table for any ingestion errors that may have been logged. This can provide additional detail in identifying the root cause of the issue.

URL: https://learn.microsoft.com/en-us/azure/azure-monitor/data-collection/metrics-export-create