Measure API response time inside your automated tests
In modern applications, performance matters just as much as correctness. Users expect fast pages and snappy APIs. Slow API responses can lead to poor user experience, longer page loads, and even timeouts in critical workflows such as checkout, login, or dashboard rendering.
The Check API Response Time step allows you to call an API endpoint directly within your test and measure how long it takes for the server to respond. This gives you objective performance data as part of your automation pack, rather than leaving it to occasional manual checks or separate performance tools.
By validating response times inside your end-to-end flows, you ensure that performance expectations are met consistently and that regressions are caught early.
Integrate performance checks into your workflows
Performance testing is often treated as a separate discipline. But for true confidence, it should be part of your core automation. With this step you can:
Call any API your application depends on
Measure how long it takes to receive a response
Assert that the response time is within an acceptable threshold
Validate that the endpoint still returns correct data
This means your tests are not just checking “did the function succeed?” but also “did it succeed quickly enough?”
You can use this in flows such as:
Before logging in, check authentication API latency
During checkout, ensure pricing API responds quickly
After a deployment, validate key services still perform within limits
On staging or production, monitor critical endpoints regularly
Understand real response times, not synthetic ones
Many performance tools simulate load or use synthetic tests. Those are valuable, but they don’t always reflect what users experience inside your actual application context.
By measuring response time inside your DoesQA flow, you get performance data in the same environment where your functional steps run. This means you can:
Include real authentication tokens
Pass real query parameters
Validate endpoint performance under realistic usage
Catch performance regressions tied to real user journeys
This helps bridge the gap between functional and performance testing without additional infrastructure.
Set meaningful thresholds
Simply measuring response time is useful, but asserting against expectations is more powerful. With this step you can:
Require APIs to respond within specific milliseconds
Fail tests when the endpoint is too slow
Combine this with conditional logic in your flow
Track performance trends over time
For example, you might assert that a search API responds within 500ms, or that a pricing API completes within 300ms. If performance degrades, your tests will surface a failure immediately.
Combine with other checks for deeper insight
The Check API Response Time step is not a standalone measure. It works with other validation steps inside your automation:
Validate the API returns correct content
Follow API calls with UI interactions
Use dynamic values inside the request
Assert on downstream page load speed
Run multiple endpoints in sequence
This gives you a rounded view of both functional correctness and performance health.
Catch performance regressions early
APIs evolve over time. New features, database changes, backend dependencies, or infrastructure changes can all impact response time.
By including response time checks in your automated packs, you will:
Detect regressions before they reach production
Provide confidence to developers and stakeholders
Avoid performance surprises during peak usage
Maintain a consistent user experience over time
Performance matters. And by measuring API latency inside the same platform you use for functional testing, you get a unified validation strategy that catches both correctness and speed issues in one place.