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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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User experience monitoring with Datadog Synthetic browser tests
Gabriel-James Safar · 2019-04-16 · via Datadog | The Monitor blog
Gabriel-James Safar

Gabriel-James Safar

To understand how your application is performing for your users, you have to put yourself in their shoes. All too often, that means manually QAing the availability and functionality of your application, and then hoping that your users don’t stumble onto any issues that you’ve missed.

Datadog’s new automated browser tests enable you to automate your user experience monitoring and ensure that your users can complete actions like signing up for a new account or adding items to a cart. Anyone on your team can record and automate multistep browser tests in minutes. Once you create a test, Datadog uses machine learning to detect changes to your application and automatically update your tests accordingly. With the addition of browser tests to the Datadog platform, you can monitor user experience alongside metrics, distributed traces, and logs from your applications and infrastructure.

Create tests in minutes with the Web Recorder

Popular browser testing tools like Selenium have reduced the manual effort involved in QAing new features and key functionality. But implementing and maintaining those tests can be time-consuming, between learning a new test framework, setting up test infrastructure, and updating broken tests every time you make changes to your UI.

Datadog Synthetic browser tests are simple to implement: anyone on your team can set up a test in minutes, without any knowledge of specialized frameworks or even coding skills. Using the browser test UI in Datadog Synthetic Monitoring, open up your website or application and start recording. As you interact with your application, Datadog automatically records the actions as a series of discrete steps, which you can then edit or build on. You can also add assertions, such as verifying that a user sees a welcome message upon signup.

Fully hosted browser tests

Choosing hosted locations for automated browser tests in the Datadog Synthetic Monitoring UI

When you record a test, you can select how often and on which devices you want it to run, and choose from several global locations. You’ll be able to see data from your test runs immediately, without setting up and configuring your own testing infrastructure. However, if you want to monitor internal-facing applications or CI environments that aren’t publicly accessible, you can easily set up up private location workers to run Datadog Synthetic tests.

Automate your UX testing with Datadog’s intelligent, adaptive browser tests.

For each executed test run, you can see the test status, the end-to-end duration of the test, and a waterfall visualization of the duration of each step. For every step and assertion, Datadog automatically generates a screenshot from your application, so you can see exactly what your users are seeing.

Waterfall visualization and UI screenshots for each step in an executed browser test

Self-maintaining browser tests

Automated browser tests have traditionally been notoriously brittle, often breaking as a result of even minor UI changes. To eliminate false alarms caused by flaky tests, AI-powered Datadog Synthetic browser tests mimic human decision-making processes and intelligently adjust in response to application changes.

For instance, when a button in your web app is moved or the identifier of an element changes, a Datadog Synthetic browser test infers how to carry out the existing test in the updated UI. If all the steps and assertions in the test can be completed successfully, Datadog updates the stored identification mechanism and test definition to reflect the changes on the page. Ultimately, these self-maintaining browser tests allow teams to spend less time fixing tests and instead focus on building new features.

End-to-end visibility for troubleshooting

Datadog browser tests automatically display context for troubleshooting

When a browser test fails because of frontend or backend issues in your application, Datadog provides the context you need to troubleshoot the issue quickly. Screenshots from the test show you what your users are seeing (did a key element disappear from the page due to a JavaScript bug, or did the page return a 503 due to server issues?). Datadog Synthetic Monitoring is tightly integrated with the rest of the platform, so you have access to end-to-end context for troubleshooting, from application logs and distributed request traces to infrastructure metrics.

Record your first browser test

Following the acquisition of Madumbo, a browser testing company that I co-founded in 2017, the entire Madumbo team has been hard at work to incorporate our technology into Datadog. We are thrilled to add browser tests to the Datadog platform. To learn more, visit our documentation, or click on the Synthetic Monitoring tab inside the Datadog app to record your first browser test. If you aren’t using Datadog yet, you can sign up for a 14-day free trial today.