Optimize Your Azure Environment with Performance Insights from Datadog

Datadog is a unified observability and security platform that provides organizations with full-stack observability into metrics, logs and traces.

In the featured video learn how the platform can give you insights into the performance and health of Azure technologies like Azure OpenAI, Azure Functions, Azure DevOps, Azure SQL Database and more so that you can keep your Azure environment in tip top shape.

Datadog is a leading cloud-scale monitoring and observability platform that provides unified visibility into applications, infrastructure, logs, metrics, traces, and user experiences.

Founded in 2010, Datadog helps development, operations, and security teams detect issues faster, collaborate effectively, and deliver reliable software at scale. With support for hybrid, multi-cloud, and on-premises environments—including deep integration with Microsoft Azure—Datadog is widely adopted by organizations building modern applications.

Azure DevOps, Microsoft’s comprehensive DevOps platform, empowers teams to plan, develop, test, and deploy software efficiently through tools like Azure Repos (version control), Azure Pipelines (CI/CD), Azure Boards (work tracking), and Azure Test Plans. As organizations increasingly rely on Azure DevOps for continuous integration and continuous deployment (CI/CD), gaining real-time insights into pipeline performance, build health, and deployment outcomes becomes essential to maintain velocity and reliability.

The integration between Datadog and Azure DevOps bridges these worlds, bringing observability directly into DevOps workflows. Announced in late 2019 and continuously enhanced, this partnership allows teams to monitor Azure DevOps activities alongside the rest of their stack in one unified platform.

Key Features of the Datadog-Azure DevOps Integration

Datadog’s integration with Azure DevOps leverages service hooks (webhooks) to send events and derive metrics automatically. Once set up—typically by installing the integration tile in Datadog and configuring service hooks in Azure DevOps projects—data flows in real time.

Core capabilities include:

• CI/CD Pipeline Visibility — Track builds, stages, jobs, releases, and pipelines end-to-end. View success/failure rates, durations, execution histories, and trends. Identify the slowest or most failure-prone pipelines, stages, or jobs to optimize throughput and reliability.
• Event and Metric Generation — Datadog ingests events for code pushes, pull requests, merges, work item updates, builds, releases, and more. It automatically derives metrics like build duration, commit frequency, work item completion time, and failure rates—tagged with Azure DevOps metadata for easy filtering and analysis.
• Real-Time Correlation and Troubleshooting — Correlate Azure DevOps events with infrastructure metrics, application traces, logs, and performance data from the rest of your environment. For example, see how a failed deployment impacts application latency or error rates across services.
• Deployment Gates with Datadog Monitors — Use Datadog alerts and monitors as automated gates in Azure Pipelines. Define health criteria (e.g., error rates below a threshold, no critical incidents) to automatically approve or halt releases—preventing bad deployments from reaching production and reducing downtime risk.
• Dashboards and Insights — Out-of-the-box dashboards visualize Azure DevOps workflows, including build/release trends and correlations with other Azure resources. Teams can customize views to include metrics from Azure services, containers, databases, or third-party tools.
• Synthetic Testing in Pipelines — Through extensions like the Datadog Continuous Testing task (available in the Visual Studio Marketplace), run browser or API Synthetic tests directly in Azure Pipelines. Validate end-to-end functionality before promotion, with results and artifacts feeding back into Datadog for trend analysis.
• Log Collection — Forward Azure DevOps pipeline logs to Datadog for centralized search, parsing, and correlation with other telemetry.

Setup is straightforward: Enable CI Visibility in Datadog for your Azure DevOps organization/projects, install relevant extensions (e.g., Datadog CI Visibility or Service Hooks), and create service hook subscriptions for desired event types. Datadog supports various account regions (US, EU, etc.) and integrates seamlessly with Microsoft Entra ID for authentication.

Real-World Benefits and Impact

Teams using this integration gain proactive insights into DevOps efficiency—spotting bottlenecks in pipelines, measuring DORA metrics (deployment frequency, lead time, change failure rate), and improving overall developer productivity. For instance, engineering leaders can track build times and failure patterns to refine processes, while SREs correlate pipeline issues with production incidents for faster root-cause analysis.

In high-velocity environments, the ability to gate deployments on Datadog-detected anomalies adds a safety net, aligning with shift-left observability practices. Organizations running large-scale Azure workloads particularly benefit from combining Azure-native metrics (via Datadog’s Azure integration) with Azure DevOps data in a single pane of glass.

Datadog’s broader partnership with Microsoft—including native provisioning in the Azure Marketplace and seamless log/metric forwarding from Azure services—further strengthens the ecosystem. This makes it easier for Azure-centric teams to adopt full-stack observability without managing multiple tools.

In summary, the Datadog-Azure DevOps integration transforms raw pipeline data into actionable intelligence, helping teams ship faster, more reliably, and with greater confidence. Whether you’re optimizing CI/CD performance, preventing faulty releases, or unifying observability across your cloud estate, this combination delivers powerful visibility for modern software delivery.