Performance regression testing

Performance testing in the blink of an eye

Risk mitigation
Performance issues at business-critical moments can affect revenue, customer satisfaction, and brand reputation.
Comply with service SLAs
Check that each release meets your contractual performance obligations.
Audit trail verification
Prevent crashes and bugs when under heavy load, and fault recovery features.

About automated performance regression testing

App performance issues don’t usually spring up out of the blue. Instead, they creep in little by little as new features are added. QA Wolf provides performance regression testing that lets teams see how code changes impact the performance of individual components or whole systems each time they run their test suite.

How it's done

Performance benchmarks as test cases

Our QA engineers will work with you to set benchmarks that become test case assertions. If the product misses its benchmark during a test run, the test will fail.
Page and component rendering times
Crud completion times
Filtering, sorting, and searching
API response times
And more!
slider that depicts traffic volume. One person on the left side, many people on the right.

Infinitely scaleable, infinitely configurable traffic

Our test-run infrastructure scales infinitely so we can point as much traffic as you want (or can handle) from anywhere on any device.

Pass/fail results in your CI/CD

Comment QA Wolf posts in github. Depicts number of tests run, number passed, number of bugs introduced separated into blocking and non-blocking
Our integrated github PR comment
Any performance issues will be filed as bug reports. You can even have our tests block a non-performant release from going to production.

Release apps fast

Holistic performance improvements takes holistic testing from the component level to the page level, front-end and back-end, across browsers and across third-party systems. QA Wolf builds, runs, and maintains performance tests for all of it.

Core performance

Page & component load times

Assert how fast media, complex components, and other assets should render under varying conditions.
stopwatch over a UI component
graph showing a traffic spike

Traffic spikes

Test system responsiveness during sudden jumps in load.

Sustained load testing

See how ongoing concurrent loads impact front-end and back-end systems over time.

The true user experience

Dealing with large data sets

Make sure that filtering, sorting, searching, creating, adding, and deleting thousands of database entries at a time is just as fast as a single item.
UI that surfaces when bandwidth is low

Low-bandwidth "lite" experiences

Assert that users on slow or unreliable networks see the “data-saving” version — and that it’s also fully regression tested.

Mobile & desktop performance

Compare performance across Chrome, Firefox, and Safari at different breakpoints
logos for chrome, firefox, safari

Back-end performance

Database loads

Use parallel test runs to simulate heavy loads on database operations, either through the UI or a direct API call.
gauge over a block of code

Server and API stress tests

Identify capacity limits and potential points of failure.

Resiliency and recovery

Test recovery time during unexpected server outages and network disruptions.


The number of possible test cases we can write and run is too long to list, but you can generally think about them in two categories:

Client-side performance tests. These are measuring the rendering time of individual components or whole pages and how long communication with the server takes. For example, asserting that a data table re-sorts in less than 100 ms.

Load and stress tests. These are usually server-side tests to see how back-end systems behave when multiple clients act on it concurrently and for prolonged periods of time. For example, assert that 5,000 users can initiate a video stream simultaneously without an impact on the user experience.

In both cases, our QA engineers work with you to design test cases and traffic patterns that you want to observe. As with all of our tests, we run them, investigate the failures, repair broken tests, and file bug reports. If you have a specific test case in mind, schedule a call and let’s discuss it.

Our parallelization infrastructure spins up a separate docker instance for each “user” and orchestrates their activity. The traffic can be programmed to complete a workflow, or a single action, depending on the test. The traffic can be generated from any geo location, on any browser, and in any volume — mix and match if you want to replicate your real world userbase.

As long as it’s measurable we can make an assertion and pass or fail a test accordingly. The most common metrics we test come from the Web Vitals Initiative, including Time to First Byte (TTFB), First Contentful Paint (FCP), and Total Blocking Time (TBT).

Definitely, we support seamless integrations with GitHub and GitLab, ensuring our testing services mesh perfectly with your continuous integration and deployment workflows. We can also work closely with your team to customize for any other SCM provider.

Yes we do. The Playwright framework can emulate more than 100 desktop and mobile devices so we can test your web application across any breakpoints that you use.

Add performance testing to your QA process

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