Automated Performance Testing of a Video SDK: CPU and Memory Monitoring from UI Automation to Front‑End Visualization

After a business feature matures, performance metrics such as CPU and memory become critical because high consumption directly degrades user experience; for SDKs, excessive usage can cause lag and rapid memory growth.

The team responsible for a video SDK emphasizes strict CPU and memory limits, especially since video playback can quickly consume hundreds of megabytes of memory, prompting the design of an automated testing workflow.

Step 1 – UI Automation: Using Appium’s API, a suite of test cases representing various application scenarios is executed; each case triggers the SDK, records the resulting CPU and memory consumption, and stores the measurements in a database.

Step 2 – Data Query: Once all cases finish, backend services expose APIs (controller‑model pattern) to retrieve the collected CPU and memory data, enabling front‑end components to request specific metrics.

Step 3 – Front‑End Display: The front‑end consumes these APIs and renders the data as line charts, showing CPU and memory trends over time for different SDK versions, allowing engineers to spot spikes or steady behavior.

The three‑step pipeline—UI automation, backend data handling, and front‑end visualization—provides clear insight into SDK performance, helping determine whether the SDK meets product stability requirements.

Some sensitive information is omitted, but the approach demonstrates how to build lightweight automation tools that improve testing quality and efficiency.

Finally, the article notes that Qtest, a professional testing team under 360, leads web platform testing automation and efficiency initiatives.