version for review

Author: bwren

articles/azure-monitor/best-practices-multicloud.md

@@ -2,91 +2,74 @@
 title: Multicloud monitoring with Azure Monitor
 description: Guidance and recommendations for using Azure Monitor to monitor resources and applications in other clouds.
 ms.topic: conceptual
-ms.date: 10/18/2021
+ms.date: 01/23/2023
 ms.reviewer: bwren
 
 ---
 
 # Multicloud monitoring with Azure Monitor
-Most customer environments include in multiple clouds. In addition to Azure, you may have applications and other resources in Amazon Web Services (AWS) and Google Cloud Platform (GCP)
-
-In addition to monitoring services and application in Azure, Azure Monitor can provide complete monitoring for your resources and applications running in other clouds. This article describes features of Azure Monitor that allow you to provide complete monitoring across your AWS and GCP environments.
-
-
-## Azure Arc
-Azure Arc simplifies governance and management by delivering a consistent multi-cloud management platform. 
+In addition to monitoring services and application in Azure, Azure Monitor can provide complete monitoring for your resources and applications running in other clouds including Amazon Web Services (AWS) and Google Cloud Platform (GCP). This article describes features of Azure Monitor that allow you to provide complete monitoring across your AWS and GCP environments.
 
 ## Virtual machines
 Using [Azure Arc-enabled servers](../azure-arc/servers/overview.md), [VM insights](vm/vminsights-overview.md) in Azure Monitor provides a consistent experience between both Azure virtual machines and your AWS EC2 or GCP VM instances. You can view your hybrid machines right alongside your Azure machines and onboard them using identical methods. This includes using standard Azure constructs such as Azure Policy and applying tags.
 
-- [Overview of Azure Arc-enabled servers](../azure-arc/servers/overview.md)
-- [Plan and deploy Azure Arc-enabled servers](../azure-arc/servers/plan-at-scale-deployment.md)
-
-The Azure Monitor agent installed by VM insights collects data from the client operating system of virtual machines regardless of their location. Use the same [data collection rules](essentials/data-collection-rule-overview.md) that define your data collection across all of the virtual machines across your different cloud environments.
+The [Azure Monitor agent](agents/agents-overview.md) installed by VM insights collects telemetry from the client operating system of virtual machines regardless of their location. Use the same [data collection rules](essentials/data-collection-rule-overview.md) that define your data collection across all of the virtual machines across your different cloud environments.
 
-- [Azure Monitor Agent overview](agents/agents-overview.md)
+- [Plan and deploy Azure Arc-enabled servers](../azure-arc/servers/plan-at-scale-deployment.md)
 - [Manage Azure Monitor Agent](agents/azure-monitor-agent-manage.md)
-- [Collect events and performance counters from virtual machines with Azure Monitor Agent](agents/data-collection-rule-azure-monitor-agent.md)
+- [Enable VM insights overview](vm/vminsights-enable-overview.md)
 
+If you use Defender for Cloud for cloud security management and threat detection, then you can use auto provisioning to automate the deployment of the Azure Arc agent to your AWS EC2 and GCP VM instances.
 
+- [Connect your AWS accounts to Microsoft Defender for Cloud](../defender-for-cloud/quickstart-onboard-aws.md)
+- [Connect your GCP projects to Microsoft Defender for Cloud](../defender-for-cloud/quickstart-onboard-gcp.md)
 
-## Kubernetes
+## Containers
 Using [Azure Arc-enabled Kubernetes](../azure-arc/servers/overview.md), [Container insights](containers/container-insights-overview.md) in Azure Monitor provides a consistent experience between both [Azure Kubernetes Service (AKS)](../aks/intro-kubernetes.md) and Kubernetes clusters in your AWS EC2 or GCP VM instances. You can view your hybrid clusters right alongside your Azure machines and onboard them using identical methods. This includes using standard Azure constructs such as Azure Policy and applying tags.
 
-- [Overview of Azure Arc-enabled Kubernetes?](../azure-arc/kubernetes/overview.md)
-- [Connect an existing Kubernetes cluster to Azure Arc](../azure-arc/kubernetes/quickstart-connect-cluster.md)
-
-The Azure Monitor agent installed by Container insights collects data from the client operating system of virtual machines regardless of their location. 
+The [Azure Monitor agent](agents/agents-overview.md) installed by Container insights collects telemetry from the client operating system of virtual machines regardless of their location. Use the same analysis tools on Container insights to monitor clusters across your different cloud environments.
 
+- [Connect an existing Kubernetes cluster to Azure Arc](../azure-arc/kubernetes/quickstart-connect-cluster.md)
 - [Azure Monitor Container Insights for Azure Arc-enabled Kubernetes clusters](containers/container-insights-enable-arc-enabled-clusters.md)
 - [Monitoring Azure Kubernetes Service (AKS) with Azure Monitor](../aks/monitor-aks.md)
 
 ## Applications
-A feature of Azure Monitor, Application Insights is an extensible Application Performance Management (APM) service for developers and DevOps professionals, which provides telemetry insights and information, in order to better understand how applications are performing and to identify areas for optimization.
+Application Insights in Azure Monitor is an extensible Application Performance Management (APM) service that provides telemetry insights and information in order to better understand how applications are performing and to identify areas for optimization. [Instrumentation methods](/app/app-insights-overview.md?tabs=net#how-do-i-instrument-an-application) are available for many languages and any platform, including ap[plications running in AWS and GCP.
 
+In addition to analysis tools in Application insights, use Azure Monitor features such as [Log Analytics](logs/log-analytics-overview.md) and [workbooks](visualize/workbooks-overview.md) to correlate the usage and performance data collected by Application Insights with configuration and performance data across the Azure resources that support the app. 
 
-
-### Microsoft Defender for Cloud
-If you are using Defender for Cloud, you can connect your AWS account and GCP projects, and automate the deployment of the Azure Arc agent to your AWS EC2 and GCP VM instances.
-
-- [Connect your AWS accounts to Microsoft Defender for Cloud](../defender-for-cloud/quickstart-onboard-aws.md)
-- [Connect your GCP projects to Microsoft Defender for Cloud](../defender-for-cloud/quickstart-onboard-gcp.md)
+- If you use [Grafana](https://grafana.com/grafana/) for visualization of monitoring data across your different clouds. use the [Azure Monitor data source](https://grafana.com/docs/grafana/latest/datasources/azure-monitor/) to include application log and metric data in your dashboards.
+- If you use [Data Dog](https://www.datadoghq.com/), use [Azure integrations](https://www.datadoghq.com/blog/azure-monitoring-enhancements/) to include application log and metric data in your Data Dog UI.
 
 
+## Audit
+In addition to monitoring the health of your cloud resources, you can consolidate auditing data from your AWS and GCP clouds into your Log Analytics workspace so that you can consolidate your analysis and reporting. This is best performed by Azure Sentinel which uses the same workspace as Azure Monitor and provides additional features for collecting and analyzing security and auditing data.
 
+Use the following methods to ingest AWS service log data into Microsoft Sentinel.
 
+- [Microsoft Sentinel connector](../sentinel/connect-aws.md)
+- [Azure function](https://github.com/andedevsecops/AWS-CloudTrail-AzFunc)
+- [AWS Lambda function](https://github.com/andedevsecops/aws-data-connector-az-sentinel)
 
-## Infrastructure
 
-You can use a plugin to get events stored in GCP Cloud Storage, and then ingest into a Log Analytics workspace.
+Use the following methods to use a plugin to collect events, including pub/sub events, stored in GCP Cloud Storage, and then ingest into Log Analytics.
 
 - [Google Cloud Storage Input Plugin](https://www.elastic.co/guide/en/logstash/current/plugins-inputs-google_cloud_storage.html)
-- [Azure Sentinel Data connector for Google Cloud Platform](https://github.com/andedevsecops/azure-sentinel-gcp-data-connector)
-- [Azure Log Analytics output plugin for Logstash](https://github.com/Azure/Azure-Sentinel/tree/master/DataConnectors/microsoft-logstash-output-azure-loganalytics)
-
-
-### Audit
-Connect Microsoft Sentinel to Amazon Web Services to ingest AWS service log data.
-
-- [Connect Microsoft Sentinel to Amazon Web Services to ingest AWS service log data](../sentinel/connect-aws.md)
-- [Azure native Data connector to ingest AWS CloudTrail Logs](https://github.com/andedevsecops/AWS-CloudTrail-AzFunc)
-- [AWS Lambda Function to import CloudTrail Logs to Azure Sentinel](https://github.com/andedevsecops/aws-data-connector-az-sentinel)
-
-You can use a plugin to get pub/sub events stored in GCP Cloud Storage, and then ingest into Log Analytics.
-
+- [GCP Cloud Functions](https://github.com/andedevsecops/azure-sentinel-gcp-data-connector)
 - [Google_pubsub input plugin](https://www.elastic.co/guide/en/logstash/current/plugins-inputs-google_pubsub.html#plugins-inputs-google_pubsub)
 - [Azure Log Analytics output plugin for Logstash](https://github.com/Azure/Azure-Sentinel/tree/master/DataConnectors/microsoft-logstash-output-azure-loganalytics)
 
 
 ## Custom data sources
+Use the following methods to collect data from your cloud resources that doesn't fit into standard collection methods.
 
-To send custom log data from any REST API client.
+- Send custom log data from any REST API client with the [Logs Ingestion API in Azure Monitor](logs/logs-ingestion-api-overview.md)
+- Use Logstash to collect data and the [Azure Log Analytics output plugin for Logstash](https://github.com/Azure/Azure-Sentinel/tree/master/DataConnectors/microsoft-logstash-output-azure-loganalytics) to ingest it into a Log Analytics workspace.
 
-- [Logs Ingestion API in Azure Monitor](logs/logs-ingestion-api-overview.md)
+## Automation
+[Azure Automation](automation/overview.md) delivers cloud-based automation, operating system updates, and configuration services that supports consistent management across your Azure and non-Azure environments. It includes process automation, configuration management, update management, shared capabilities, and heterogeneous features. [Hybrid Runbook Worker](automation/automation-hybrid-runbook-worker.md) enables automation runbooks to run directly on the non-Azure virtual machines  against resources in the environment to manage those local resources.
 
-Alternatively, use Logstash to collect and the Logstash plugin to ingest data.
-
-- [Azure Log Analytics output plugin for Logstash](https://github.com/Azure/Azure-Sentinel/tree/master/DataConnectors/microsoft-logstash-output-azure-loganalytics)
+Through [Arc-enabled servers](azure-arc/servers/overview.md), Azure Automation provides a consistent deployment and management experience for your non-Azure machines. It enables integration with the Automation service using the VM extension framework to deploy the Hybrid Runbook Worker role, and simplify onboarding to Update Management and Change Tracking and Inventory.
 
 ## Next steps