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articles/azure-monitor/agents/azure-monitor-agent-manage.md

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@@ -373,8 +373,7 @@ The AgentSettings DCR currently supports configuring the following parameters:
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| Parameter | Description | Valid values |
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| --------- | ----------- | ----------- |
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| `DiscQuotaInMb` | Defines the amount of disk space used by the Azure Monitor Agent log files and cache. | 1,000-50,000 (or 1-50 GB) |
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| `MaxDiskQuotaInMB` | Defines the amount of disk space used by the Azure Monitor Agent log files and cache. | 1000-50000 (in MB) |
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| `TimeReceivedForForwardedEvents` | Changes WEF column in the Sentinel WEF table to use TimeReceived instead of TimeGenerated data | 0 or 1 |
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### Setting up AgentSettings DCR
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[Install AMA](#installation-options) on your VM.
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1. **Create a DCR via template deployment:**
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1. **Create a DCR:**
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The following example changes the maximum amount of disk space used by AMA cache to 5 GB.
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This example sets the maximum amount of disk space used by AMA cache to 5000 MB.
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```json
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{
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}
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```
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> [!NOTE]
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> You can use the Get DataCollectionRule API to get the DCR payload you created with this template.
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1. **Associate DCR with your machine:**
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1. **Associate the DCR with your machine:**
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This can be done with a template or by using the [Create API](/rest/api/monitor/data-collection-rule-associations/create) with the following details:
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* **AssociationName:** agentSettings
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* **ResourceUri:** Full ARM ID of the VM
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* **api-version:** 2023-03-11 (Old API version is also fine)
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* **Body:**
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```json
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{
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"properties": {
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"dataCollectionRuleId": “Full ARM ID for agent setting DCR”
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}
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}
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```
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Use these ARM template and parameter files:
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**ARM template file**
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```json
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{
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"$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
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"contentVersion": "1.0.0.0",
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"parameters": {
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"vmName": {
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"type": "string",
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"metadata": {
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"description": "The name of the virtual machine."
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}
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},
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"associationName": {
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"type": "string",
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"metadata": {
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"description": "The name of the association."
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}
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},
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"dataCollectionRuleId": {
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"type": "string",
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"metadata": {
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"description": "The resource ID of the data collection rule."
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}
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}
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},
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"resources": [
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{
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"type": "Microsoft.Insights/dataCollectionRuleAssociations",
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"apiVersion": "2021-09-01-preview",
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"scope": "[format('Microsoft.Compute/virtualMachines/{0}', parameters('vmName'))]",
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"name": "[parameters('associationName')]",
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"properties": {
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"description": "Association of data collection rule. Deleting this association will break the data collection for this virtual machine.",
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"dataCollectionRuleId": "[parameters('dataCollectionRuleId')]"
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}
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}
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]
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}
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```
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**Parameter file**
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```json
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{
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"$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentParameters.json#",
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"contentVersion": "1.0.0.0",
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"parameters": {
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"vmName": {
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"value": "my-azure-vm"
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},
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"associationName": {
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"value": "my-windows-vm-my-dcr"
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},
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"dataCollectionRuleId": {
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"value": "/subscriptions/00000000-0000-0000-0000-000000000000/resourcegroups/my-resource-group/providers/microsoft.insights/datacollectionrules/my-dcr"
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}
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}
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}
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```
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1. **Activate the settings:**
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articles/azure-monitor/autoscale/autoscale-predictive.md

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## Enable using an Azure Resource Manager template
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1. Retrieve the virtual machine scale set resource ID and resource group of your virtual machine scale set. For example: /subscriptions/e954e48d-abcd-abcd-abcd-3e0353cb45ae/resourceGroups/patest2/providers/Microsoft.Compute/virtualMachineScaleSets/patest2
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1. Retrieve the virtual machine scale set resource ID and resource group of your virtual machine scale set. For example: /subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/patest2/providers/Microsoft.Compute/virtualMachineScaleSets/patest2
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1. Update the *autoscale_only_parameters* file with the virtual machine scale set resource ID and any autoscale setting parameters.
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PS G:\works\kusto_onboard\test_arm_template> new-azurermresourcegroupdeployment -name binzAutoScaleDeploy -resourcegroupname cpatest2 -templatefile autoscale_only.json -templateparameterfile autoscale_only_parameters.json
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```
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:::image type="content" source="media/autoscale-predictive/powershell-template-7.png" alt-text="Screenshot that shows PowerShell command output from the preceding command when you run Azure Resource Manager templates to deploy predictive autoscale.":::
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```powershell
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PS C:\works\autoscale\predictive_autoscale\arm_template> new-azurermresourcegroupdeployment -name binzAutoScaleDeploy - resourcegroupname patest2 -templatefile autoscale_only_binz.json -templateparameterfile autoscale_only_parameters_binz.json
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DeploymentName : binzAutoScaleDeploy
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ResourceGroupName : patest2
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ProvisioningState : Succeeded
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Timestamp : 3/30/2021 10:11:02 PM
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Mode : Incremental
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TemplateLink
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Parameters :
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Name Type Value
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================ ============================= ====================
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targetVmssResourceld String /subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/patest2/providers/Microsoft.Compute/virtualMachineScaleSets/patest2
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location String East US
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minimumCapacity Int 1
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maximumCapacity Int 4
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defaultCapacity Int 4
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metricThresholdToScaleOut Int 50
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metricTimeWindowForScaleOut String PT5M
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metricThresholdToScaleln Int 30
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metricTimeWindowForScaleln String PT5M
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changeCountScaleOut Int 1
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changeCountScaleln Int 1
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predictiveAutoscaleMode String Enabled
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Outputs :
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Name Type Value
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================ ============================== ====================
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targetVmssResourceld String /subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/patest2/providers/Microsoft.Compute/virtualMachineScaleSets/patest2
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settingLocation String East US
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predictiveAutoscaleMode String Enabled
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DeloymentDebugLoglevel :
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PS C:\works\autoscale\predictive_autoscale\arm_template>
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```
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**autoscale_only.json**
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```json
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"contentVersion": "1.0.0.0",
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"parameters": {
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"targetVmssResourceId": {
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"value": "/subscriptions/e954e48d-b252-b252-b252-3e0353cb45ae/resourceGroups/patest2/providers/Microsoft.Compute/virtualMachineScaleSets/patest2"
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"value": "/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/patest2/providers/Microsoft.Compute/virtualMachineScaleSets/patest2"
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},
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"location": {
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"value": "East US"
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articles/azure-monitor/best-practices-logs.md

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## Reliability
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[Reliability](/azure/well-architected/resiliency/overview) refers to the ability of a system to recover from failures and continue to function. Instead of trying to prevent failures altogether in the cloud, the goal is to minimize the effects of a single failing component. Use the following information to minimize failure of your Log Analytics workspaces and to protect the data they collect.
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[Reliability](/azure/well-architected/resiliency/overview) refers to the ability of a system to recover from failures and continue to function. The goal is to minimize the effects of a single failing component. Use the following information to minimize failure of your Log Analytics workspaces and to protect the data they collect.
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This video provides an overview of reliability and resilience options available for Log Analytics workspaces:
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> [!VIDEO https://www.youtube.com/embed/CYspm1Yevx8?cc_load_policy=1&cc_lang_pref=auto]
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[!INCLUDE [waf-logs-reliability](includes/waf-logs-reliability.md)]
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articles/azure-monitor/essentials/create-diagnostic-settings.md

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services: azure-monitor
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ms.topic: how-to
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ms.custom: devx-track-azurecli, devx-track-azurepowershell
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ms.date: 10/19/2023
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ms.date: 08/11/2024
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ms.reviewer: lualderm
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---
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Every effort is made to ensure all log data is sent correctly to your destinations, however it's not possible to guarantee 100% data transfer of logs between endpoints. Retries and other mechanisms are in place to work around these issues and attempt to ensure log data arrives at the endpoint.
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### Inactive resources
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When a resource is inactive and exporting zero-value metrics, the diagnostic settings export mechanism backs off incrementally to avoid unnecessary costs of exporting and storing zero values. The back-off may lead to a delay in the export of the next non-zero value.
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When a resource is inactive for one hour, the export mechanism backs off to 15 minutes. This means that there is a potential latency of up to 15 minutes for the next nonzero value to be exported. The maximum backoff time of two hours is reached after seven days of inactivity. Once the resource starts exporting nonzero values, the export mechanism reverts to the original export latency of three minutes.
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This behavior only applies to exported metrics and doesn't affect metrics-based alerts or autosacle.
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## Next steps
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- [Review how to work with diagnostic settings in Azure Monitor](./diagnostic-settings.md)

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