16 April 2026
Android 17 has reached beta 4, the last scheduled beta of this release cycle, a critical milestone for app compatibility and platform stability. Whether you're fine-tuning your app's user experience, ensuring smooth edge-to-edge rendering, or leveraging the newest APIs, Beta 4 provides the near-final environment you need to be testing with.
If you develop an Android SDK, library, tool, or game engine, it's critical to prepare any necessary updates now to prevent your downstream app and game developers from being blocked by compatibility issues and allow them to target the latest SDK features. Please let your downstream developers know if updates are needed to fully support Android 17.
Testing involves installing your production app or a test app making use of your library or engine using Google Play or other means onto a device or emulator running Android 17 Beta 4. Work through all your app's flows and look for functional or UI issues. Each release of Android contains platform changes that improve privacy, security, and overall user experience; review the app impacting behavior changes for apps running on and targeting Android 17 to focus your testing, including the following:
Android is introducing app memory limits based on the device's total RAM to create a more stable and deterministic environment for your applications and Android users. In Android 17, limits are set conservatively to establish system baselines, targeting extreme memory leaks and other outliers before they trigger system-wide instability resulting in UI stuttering, higher battery drain, and apps being killed. While we anticipate minimal impact on the vast majority of app sessions, we recommend the following memory best practices, including establishing a baseline for memory.
In the current implementation, getDescription in ApplicationExitInfo will contain the string "MemoryLimiter" if your app was impacted. You can also use trigger-based profiling with TRIGGER_TYPE_ANOMALY to get heap dumps that are collected when the memory limit is hit.
To help you find memory leaks, Android Studio Panda adds LeakCanary integration directly in the Android Studio Profiler as a dedicated task, contextualized within the IDE and fully integrated with your source code.
A lighter memory footprint translates directly to smoother performance, longer battery life, and a premium experience across all form factors. Let’s build a faster, more reliable future for the Android ecosystem together!
Android introduces an on-device anomaly detection service that monitors for resource-intensive behaviors and potential compatibility regressions. Integrated with ProfilingManager, this service allows your app to receive profiling artifacts triggered by specific system-detected events.
Use the TRIGGER_TYPE_ANOMALY trigger to detect system performance issues such as excessive binder calls and excessive memory usage. When an app breaches OS-defined memory limits, the anomaly trigger allows developers to receive app-specific heap dumps to help identify and fix memory issues. Additionally, for excessive binder spam, the anomaly trigger provides a stack sampling profile on binder transactions.
This API callback occurs prior to any system imposed enforcements. For example, it can help developers collect debug data before the app is terminated by the system due exceeding memory limits. To understand how to use the trigger check out our documentation on trigger based profiling.
val profilingManager = applicationContext.getSystemService(ProfilingManager::class.java)
val triggers = ArrayList<ProfilingTrigger>()
triggers.add(ProfilingTrigger.Builder(
ProfilingTrigger.TRIGGER_TYPE_ANOMALY))
val mainExecutor: Executor = Executors.newSingleThreadExecutor()
val resultCallback = Consumer<ProfilingResult> { profilingResult ->
if (profilingResult.errorCode != ProfilingResult.ERROR_NONE) {
// upload profile result to server for further analysis
setupProfileUploadWorker(profilingResult.resultFilePath)
}
}
profilingManager.registerForAllProfilingResults(mainExecutor, resultCallback)
profilingManager.addProfilingTriggers(triggers)
Android Keystore added support for the NIST-standardized ML-DSA (Module-Lattice-Based Digital Signature Algorithm). On supported devices, you can generate ML-DSA keys and use them to produce quantum-safe signatures, entirely in the device’s secure hardware. Android Keystore exposes the ML-DSA-65 and ML-DSA-87 algorithm variants through the standard Java Cryptographic Architecture APIs: KeyPairGenerator, KeyFactory, and Signature. For further details, see our developer documentation.
KeyPairGenerator generator = KeyPairGenerator.getInstance(
“ML-DSA-65”, "AndroidKeyStore");
generator.initialize(
new KeyGenParameterSpec.Builder(
“my-key-alias”,
KeyProperties.PURPOSE_SIGN | KeyProperties.PURPOSE_VERIFY)
.build());
KeyPair keyPair = generator.generateKeyPair();
You can enroll any supported Pixel device to get this and future Android Beta updates over-the-air. If you don’t have a Pixel device, you can use the 64-bit system images with the Android Emulator in Android Studio.
If you are currently in the Android Beta program, you will be offered an over-the-air update to Beta 4. Continue to report issues and submit feature requests on the feedback page. The earlier we get your feedback, the more we can include in our work on the final release.
For the best development experience with Android 17, we recommend that you use the latest preview of Android Studio (Panda). Once you’re set up, here are some of the things you should do:
We’ll update the preview/beta system images and SDK regularly throughout the Android 17 release cycle. Once you’ve installed a beta build, you’ll automatically get future updates over-the-air for all later previews and Betas. For complete information, visit the Android 17 developer site.
Your feedback remains our most valuable asset. Whether you’re an early adopter on the Canary channel or an app developer testing on Beta 4, consider joining our communities and filing feedback. We’re listening.