Key takeaways
Synthetic browser tests are one of the most powerful tools in your observability stack. When they reflect real user flows and backend interactions, these tests help teams to:
This article covers Best Practice #1 in the Getting Synthetics Right Series: Design with Purpose.
This best practice is about intentionally designing each synthetic test for clarity, measurability, and business value. Start by mapping short, critical user journeys that reflect the flows most important to your customers and your business. The key is to build journeys from authentic user interactions like clicks, form fills, and menu selections.
While it can be tempting to use shortcuts by directly calling a final URL, this approach bypasses the actual user experience. By simulating the full clickstream, your tests ensure that critical components like search bars and navigation menus are working as expected, not just that the final page loads.
Once you have your steps, group them into synthetic transactions so you can measure metrics like duration, requests, and size for each business-critical workflow. Finally, design your tests to invoke key backend services so that passive monitoring tools like RUM and APM continue to receive meaningful data, even during low-traffic periods.
We’ll dive into each of these steps in detail, below.
Poorly structured synthetic tests can create noise, break for unrelated reasons, and leave you guessing about the root cause of a failure. By designing with purpose, you:
This approach turns synthetic monitoring from simple uptime checks into a powerful, always-on signal for both frontend and backend health.
Sit with a user or product manager to understand common and critical clickstreams. Document these clickstreams or record the session using a tool like Webex to map actual user behavior. Remember: the goal is to capture and understand the critical user journeys, not everything a user might do (we have RUM for that).
Examples of CUJs by industry:
| Industry | Example Critical User Journey |
|---|---|
| Retail | Homepage → Search for product → Add to cart → Checkout |
| Finance | Login → View accounts → Transfer funds |
| Healthcare | Login → View test results → Message provider |
| SaaS / B2B | Login → Load dashboard → Create report |
| Travel | Search flights → Select option → Book and pay |
With this understanding, you can build your synthetic test and take advantage of Splunk Observability Cloud’s out-of-the-box support for importing from the Chrome Recorder to capture interactions directly from your browser and import them into Splunk. These short flows are built from steps that make up individual interactions like clicking a link, entering data, or selecting a value from a drop-down menu.
Once your test is live, Splunk captures a real-time video of the transaction execution and provides a filmstrip view with screenshots at 100ms, 500ms, or 1-second intervals. See this in action:
Next, organize your steps into synthetic transactions. Each transaction represents a business-critical user flow, such as login or checkout.
This is a key part of designing with purpose. Instead of creating a single, massive test for an entire end-to-end workflow (like searching, adding to cart, and checking out), you should break it into separate, focused transactions. This allows you to isolate, test, and monitor each critical part of the user journey more effectively.
By combining both perspectives, you can pinpoint whether an issue is isolated to a specific page or is caused by the cumulative steps in a workflow. Multiple transactions in a test let you measure separate workflows without losing context.
Synthetic browser tests are interval based and run 24×7×365, so it does not matter if real users are actively interacting with your front end. This active monitoring approach means your critical user journeys are tested continuously, providing coverage even when user activity is low or nonexistent.
When configured correctly, synthetics allow you to detect issues impacting these journeys in real time. This enables proactive response so your teams can start investigating and remediating problems before customers report them.
Once an issue is detected, responders can confirm it by reviewing the filmstrip from the synthetic run. The next step is to identify the root cause and assess the impact, if any, to real users.
Splunk ties this all together with deep links from synthetic runs directly into related RUM sessions and APM traces. This lets you follow the full journey from detection to impact assessment to root cause, in real-time, without losing context.
Designing with purpose means building synthetic tests that are short, structured, and aligned to your most critical user journeys. By capturing realistic steps, grouping them into meaningful transactions, and integrating them with your passive monitoring tools, you create a feedback loop that is proactive, precise, and actionable.
If your synthetics setup can tell you what is broken, how it impacts users, and where to start fixing it (all before your first support ticket arrives) you have turned it into one of the most valuable assets in your observability stack.
Next step: Take one critical user journey in your environment and apply this approach. Use Splunk Synthetic Monitoring to record it, define transactions, and connect it to RUM and APM for end-to-end visibility. You can try it yourself right now with this free trial of Splunk Observability Cloud.
Say goodbye to blind spots, guesswork, and swivel-chair monitoring. With Splunk Observability Cloud and AI Assistant, correlate all your metrics, logs, and traces automatically and in one place.
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