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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - 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Monitor Azure Government with Datadog
Ari Shahar, Mallory Mooney · 2021-11-10 · via Datadog | The Monitor blog
Ari Shahar

Ari Shahar

Mallory Mooney

Mallory Mooney

Azure Government is a dedicated cloud for public sector organizations that want to leverage Azure’s suite of services in their highly regulated environments. As these organizations migrate their applications to Azure Government, they need to ensure that they can maintain visibility into the status and health of their entire infrastructure. We’re excited to announce that we’ve partnered with Azure to enable you to collect low-latency metrics from all of your workloads and Azure services hosted on Azure Government.

Complete visibility into your Azure Government environment

Datadog’s Azure integration lets you monitor critical services in your environment, such as Azure Load Balancer and Azure Functions, so you have full visibility into the health and performance of your infrastructure resources. You can set up the integration via the Azure CLI or Azure portal, which provides a seamless onboarding experience for installing the Datadog Agent on your hosts and setting up platform log collection.

Full-stack Azure monitoring

Once you’ve configured the Azure integration, you can visualize key data using Datadog’s out-of-the-box integration dashboards and create alerts to automatically notify you of problems as soon as they happen. And, with more than 1,000 integrations with other technologies, such as MongoDB and Kafka, Datadog enables you to detect issues in workload performance at each layer of your stack and drill down to specific resources to determine the root cause of an issue.

For example, you can monitor resource utilization across containers within a specific AKS cluster in order to find which ones have higher CPU usage.

Use the Container Map to quickly visualize resource-saturated containers in an AKS cluster.
View Azure containers with the container map
Use the Container Map to quickly visualize resource-saturated containers in an AKS cluster.

You can then drill down to a problematic container to view resource utilization and running processes, so you can determine if a particular workload is consuming too many resources and should be refactored. And, when you collect logs from your AKS cluster, you can correlate them with process activity to get more context for an issue and troubleshoot in real time.

Datadog also collects data from Azure services to automatically generate additional metrics, giving you an exhaustive view of your entire Azure infrastructure as soon as you enable the integration. For example, you can use the generated azure.vm.count metric to view the count and status of all of your environment’s virtual machines.

Group your VMs by status to quickly find problematic machines.
View the status of all of your Azure virtual machines
Group your VMs by status to quickly find problematic machines.

You can use this metric to create an alert that automatically notifies you of unexpected status changes for your Azure VMs, such as provision or allocation failures. These types of failures can be caused by a cluster requesting an incompatible VM or resource constraints that prevent the allocation of a new VM. Triggered alerts include relevant VM tags and logs, so you can find the root cause of a failure and resolve the issue more quickly.

Better inventory management

Taking inventory of available resources in distributed cloud environments can be complicated, but Datadog gives you a better view of what is running in your Azure Government accounts. This enables you to plan and monitor activities that are critical to keeping your services running, such as scheduled maintenance or system version updates.

For instance, end-of-life software, outdated, or misconfigured infrastructure can create vulnerabilities in your environment. It’s important that infrastructure resources run on up-to-date software and hardware and are configured with the appropriate security controls. Datadog makes it easy to tag your Azure Government resources with metadata such as hardware version, operating system, availability zone, and cluster, so you can find outdated hosts and search for newly configured resources to ensure they follow compliance policies.

Keep track of all of infrastructure resources in your Azure Government environment.
View resources in your Azure Government environment
Keep track of all of infrastructure resources in your Azure Government environment.

Start monitoring your Azure Government environment

Datadog provides a unified view of your entire Azure ecosystem, including any services running in an Azure Government environment. Check out our documentation to learn more about setting up your Azure services. Or, you can sign up for a free trial to get started.