Vega UI Fluidity Guide

Vega Open Beta Knowledge Base
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When it comes to building high-quality TV apps, UI fluidity is a critical factor that directly impacts user experience. A smooth and responsive user interface makes your app feel polished, fast, and easy to use. Users are sensitive to performance issues—slow load times, stuttering animations, and unresponsive UI elements can quickly lead to frustration and user drop off from the app.

This article provides a guide to UI fluidity—from understanding why it’s important to how to measure it and ultimately achieve self-certification for app performance on Vega device. Following these guidelines, will allow developers to help app meet the UI fluidity performance targets for Vega device.

Introduction on Why UI Fluidity Matters

UI fluidity refers to how smooth and responsive your app’s interface feels during use. It includes factors such as:

  • Smoothness of Animations: Transitions, fades, and other visual effects should occur without noticeable stuttering or lag.
  • User Input Responsiveness: User interactions through RCU key presses should be immediately reflected on the screen.
  • Load Time: How quickly the app components appear after the user initiates an action.

A fluid UI is key to improving user engagement, reducing bounce rates, and boosting user satisfaction. Conversely, poor UI fluidity can result in frustrated users who might abandon your app in favor of smoother alternatives. The fluidity calculations are done based on the assumption that the UI rendering is performed at 60fps which means that a new frame will be rendered every ~16ms. This translates to how quickly the rendering operations need to be performed during transitions while the user is navigating through the app.

The Vega device is built with a very fast and performant device operating system in order for the applications to meet the UI fluidity performance targets.

Measuring UI Fluidity

To evaluate UI fluidity, developers need to focus on fluidity KPI measurement on Vega device. On Vega device the fluidity measurement is provided as a percentage value which takes into account the dropped frames. The key parameters that would impact dropped frame numbers would be rate at which the UI frames are rendered, the responsiveness of the app to user input and smoothness of the animations.

This value is measured while performing UI scrolling actions within the app. Vega SDK provides the necessary tools for developers to measure this KPI value as described below.

How to Measure: Use built-in Vega Studio performance tools (KPI Visualizer) to measure FPS during interactions (e.g., scrolling, animations). The KPI Visualizer will calculate UI Fluidity as a percentage using the above KPI traces. The target for Vega apps on UI Fluidity KPI is set to 99%.

:light_bulb: For more details on the Fluidity KPI for Vega apps refer to the documentation here.

Self-Certification: Steps to Achieve UI Fluidity Standards

Achieving self-certification means validating that your app meets the required targets for UI fluidity before submitting it for external review or app store publishing. Here’s a step-by-step guide to help you through the process:

1. Prepare Your App for Testing

  • Build for Production: Ensure your app is optimized and ready for testing (e.g., no debug versions, assets properly compressed). Install the app on the device for testing. Also it is advisable to complete any initial setup screens inside your app to make sure that the app loads the UI home page on relaunching (complete any consent management and login workflows).
  • Set Test Objectives: Define what you aim to achieve with each test (e.g., confirming a 60 FPS target for animation smoothness).
  • Identify Test Scenarios: Outline the key user interactions and transitions to test (e.g., opening the app, scrolling lists, navigating between screens). This can be achieved by creating test scripts specific to your application UI to drive the interaction. Vega SDK uses Appium driver to inject the key presses in order to achieve UI interaction. Next section describes how to generate App level UI script for testing fluidity.

2. Create Test Scenario script:

The preferred mechanism for UI fluidity measurement is to generate your own custom test script.

You can generate your own test scenario script using the command available in Vega Studio extension of VS Code by launching command (shift + command ⌘ + p for Mac or Shift + Ctrl + P for Linux) and then enter Kepler: Generate test scenario template.

:light_bulb: For more details on how to generate and customize test scenario script refer to the tech docs.

Update the test scenario script:

After following the steps in the link above and creating the test scenario script you need to update the prep() method in the script to add a wait to make sure app has loaded completely and send any key presses on the app launch to get to the UI component page where you want to run the UI fluidity test. e.g. if the app UX requires waiting for 10s to make sure that the app UI home page is loaded completely and you need to enter.

Also update the run() method to send the navigation key presses to simulate UI interaction. This test scenario script will be used by perf tool to run in every iteration.

def prep(self) -> None:
    if supportAppiumOptions:
        self.__driver = webdriver.Remote(
            appium_url,
            options=AppiumOptions().load_capabilities(self.__capabilities)
        )
    else:
        self.__driver = webdriver.Remote(appium_url, self.__capabilities)
    """ Code for preparation stage.

    For D-pad key send test case, we do not define preparation step
    as the D-pad key are sent to Home page of the VegaVideoApp.
    """
    # wait 10 seconds for app to warm up
    logger.info("Waiting for application to warm up for 10 seconds")
    time.sleep(10)
    return

def run(self) -> None:
    """ Code to send D-Pad keys.

    KPI (e.g. UI Fluidity/Background memory) will be measured during
    run stage code run.

    For D-Pad key send sample test, following interactions will
    be performed:
    1. Send "Down" key for 5 times
    2. Send "Up" key for 4 times
    3. Send "Right" key for 4 times
    4. Send "Left" key for 4 times.
    """
    for _ in range(5):
        self._press_dpad("108", TestRunner._PRESS_DELAY)

    for _ in range(4):
        self._press_dpad("103", TestRunner._PRESS_DELAY)

    for _ in range(4):
        self._press_dpad("106", TestRunner._PRESS_DELAY)

    for _ in range(4):
        self._press_dpad("105", TestRunner._PRESS_DELAY)

3. Run KPI visualizer with your generated test scenario script

Vega SDK provides the CLI tools for running performance KPI measurement which can be invoked as below:

bash-3.2$ perf kpi-visualizer --kpi ui-fluidity --iteration 10 --test-scenario <location of your test scenario script> --app-name <your app ID>

NOTE: Add the location of your test scenario script and appID (package name) in the command above. Also note that you can adjust the iterations to suit your testing needs. For better results it is advisable to run more than 20 iterations for fluidity measurements to make sure that there is low standard deviation.

Running KPI Visualizer for UI Fluidity with Vega Studio extension in VS Code:

You can execute the UI fluidity test from Vega Studio extension in VS Code using shift + command ⌘ + p for Mac or Shift + Ctrl + P for Linux. Then select the KPI to run test for and the test scenario script created in the previous step. It is useful to use the mechanism to run UI fluidity tests during development as it allows you to make use of the Vega Studio extension to analyze the results and find out root cause causing fluidity measurements to drop. The main requirement of running KPI Visualizer in Vega Studio extension is that you need to do it from your Vega project of the app.

4. Analyze and Optimize

  • Review Test Results: Check your test data against the defined benchmarks. If Fluidity % is below the target threshold of 99%, it’s time for optimization.
  • Optimize for Performance:
    • Reduce unnecessary overdraws and optimize images/assets.
    • Use efficient UI rendering techniques like Lazy Loading for content-heavy screens.
    • Optimize animations and transitions by limiting complex effects or using hardware acceleration where possible.
    • Identify janky frames.

:light_bulb: For more information and help on how to analyze results and improve UI rendering performance refer to the tech docs.

5. Final Check and Certification

  • Re-test After Optimization: Re-run your performance tests to verify that the changes have improved fluidity and met the target benchmarks.
  • Certify Your App: Once the app meets the performance benchmarks for UI Fluidity %, you can consider this version of the app as “UI Fluidity Ready.”
  • Document the Results: Record your testing process and results for reference. This documentation can be helpful when seeking feedback from app store or external reviewers.

Best Practices for UI Fluidity Optimization

To improve and maintain smooth UI performance, consider the following best practices:

  • Efficient Image Management: Compress images and assets to minimize load times. Use modern formats like WebP for images and vector graphics (SVG) when possible.
  • Optimize Animations: Avoid overcomplicating animations with too many moving parts. Prefer vector-based animations over bitmap-based ones for better rendering performance.
  • Prioritize Critical UI Elements: Ensure that critical UI elements (buttons, navigation bars, etc.) are loaded and rendered first to provide instant feedback to the user.
  • Offload Heavy Tasks: Use background processing for heavy tasks like data fetching or complex calculations to avoid UI stutter.
  • Use Lazy Loading: Load only the parts of the app that are necessary when they are needed, reducing initial load times and improving user experience.

:light_bulb: For more information and references on App performance best practices refer to the tech docs.

Last updated: Mar 10, 2026

Tooling and Help Guides for Performant App Development