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Android Developers: 3 latest new features in Android

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Many new updates happened for Android developers lately after Google I/O. Initially there was no restriction on some features but now they have updated them with some restrictions.

We have covered new features and the old features as well with new restrictions.

Here are the old features with new restrictions:

• Background Execution Limits

Whenever an app runs in the background, it consumes some of the device’s limited resources, like RAM. This can result in an impaired user experience, especially if the user is using a resource-intensive app, such as playing a game or watching a video.
To lower the chance of these problems, Android O places limitations on what apps can do while users aren’t directly interacting with them. Apps are restricted in two ways:

Background Service Limitations: When an app’s service is running in the background might consume device resources which may lead to bad user experience, to avoid these type of issues Android system applies a number of limitations on background services, this does not apply to foreground services, which are more noticeable to the user.
Broadcast Limitations: Apps targeted Android O can not use their manifest to register for implicit broadcasts. They can still register for these broadcasts at runtime, and they can use the manifest to register for explicit broadcasts targeted specifically at their app.

Note: The restrictions are applied by default applied to apps which are targeting Android O and in terms of other applications users can enable these restrictions from the Settings screen even if the app has not targeted Android O.

• Android Background Location Limits

Considering battery usage and user experience , background apps which are using Android locations APIs to fetch the user’s location will receive location updates less frequently when the app is being used in a device running Android O, developers who are using Fused Location Provider (FLP), Geofencing, GNSS Measurements, Location Manager, Wi-Fi Manager will get affected by this change.

• Notifications

  1. Notification Badges

    Notification Badges are the new way of notifying users regarding the new notifications arrived for a particular app, this will display badges on app icons in supported launchers which show notifications associated with one or more notification channels in an app, which the user has not yet dismissed or acted on.

  2. Notification Channels

    Using Notification channels developers can group their application’s notifications by category so that the user can apply few characteristics basing on the notification category. When you target Android O, you must implement one or more notification channels to display notifications to your users. If you don’t target Android O, your apps behave the same as they do on Android 7.0 when running on Android O devices.

Google says that the following characteristics can be applied to notification channels and that when the user assigns one of these, it will be applied channel- wide and they are as follows

  • Importance
  • Sound
  • Lights
  • Vibration
  • Show on lock screen
  • Override do not disturb

Here are some new features:

• New in UI and Styling

There are bunch of new features of UI and Styling are introduced in Android O and are as follows

1. Fonts

Android introduced fonts in XML through which we can use custom fonts as resources, You can add your custom font file in res/font/ folder to bundle fonts as resources and can access as a normal resource file and Android Support Library 26 introduce support for APIs to request fonts from a provider application instead of bundling files into your project which helps in reducing your application size
To use these font features on devices running Android API version 14 and higher, a developer needs to use the Support Library 26.

2. Auto Sizing Textviews

By using Support Library 26 Beta developers can now instruct to their app’s Textview to automatically increase or decrease the size to fit perfectly within the boundaries of the Textview.

3. Adaptive Icons

Adaptive icons can display app’s launcher icons in a variety of shapes across different devices for instance in Google Nexus the launcher icon might be in circular and in some Samsung device it might be squircle. Google says that with Android O, each device can provide a mask for the icon, which the OS can use to render all icons with the same shape. This will likely be embraced by OEMs(Original Equipment Manufacturer) who would like to have some unique looking home screens.

4. Autofill Framework

This framework will help the user by pre-filling the user information and user can save time as Filling out forms is a time-consuming and error-prone task. Users can easily get frustrated with apps that require these type of tasks. The Autofill Framework improves the user experience by providing the following benefits:

Less time spent in filling fields Autofill saves users from re-typing information.
Minimize user input errors Typing is prone to errors, especially on mobile devices. Removing the necessity of typing information also removes the errors that come with it.

• Picture in Picture Mode

In Android 7.0, Android TV users can now watch a video in a pinned window in a corner of the screen when navigating within or between apps whereas it was not available to other devices whereas from Android O Picture in Picture is available to all the devices, not just the Android TV.

• Kotlin For Android

Java is the mostly used programming language for the development of Android, When you run a Java application, the app is compiled into a set of instructions called Bytecode and runs in a virtual machine. Many alternative Languages has been introduced to also run on the JVM through which the resulting app looks the same for the JVM
JetBrains, known for IntelliJ IDEA (Android Studio is based on IntelliJ), has introduced the Kotlin language.Kotlin is a statically-typed programming language that runs on the JVM. It can also be compiled to JavaScript source code.

Why Kotlin For Android?

  • Interoperability with Java
  • Intuitive and easy to read
  • Good Android Studio Support
  • Safe to avoid entire classes of errors such as null pointer exceptions.
  • Less to write compared to Java
  • Safe to avoid entire classes of errors such as null pointer exceptions.
  • Versatile for building server-side applications, Android apps or frontend code running in the browser.

Stay tuned for more new updates on Android.

Check out these articles to catch the latest trends in mobile apps:

  1. 7 Important Points To Consider Before Developing A Mobile App
  2. The Clash of Clans: Kotlin Vs. Flutter
  3. Google for India September event 2019 key highlights
  4. Learn Ionic Framework From Scratch in Less Than 15 Minutes!
  5. AI in Mobile Development
  6. 10 Reasons to Learn Swift Programming Language
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What’s Next in Cloud Optimization? Can We Optimize Costs Without Sacrificing Performance?

Not too long ago, storing data meant dedicating an entire room to massive CPUs. Then came the era of personal computers, followed by external hard drives and USB sticks. Now, storage has become practically invisible, floating somewhere between data centers and, well, the clouds—probably the ones in the sky. Cloud computing continues to evolve, As cloud computing evolves, optimizing costs without sacrificing performance has become a real concern.  How can organizations truly future-proof their cloud strategy while reducing costs? Let’s explore new-age cloud optimization strategies in 2025 designed for maximum performance and cost efficiency.

Smarter Cloud Strategies: Cutting Costs While Boosting Performance

1. AI-Driven Cost Prediction and Auto-Optimization

When AI is doing everything else, why not let it take charge of cloud cost optimization too? Predictive analytics powered by AI can analyze usage trends and automatically scale resources before traffic spikes, preventing unnecessary over-provisioning. Cloud optimization tools like AWS Compute Optimizer and Google’s Active Assist are early versions of this trend.

  • How it Works: AI tools analyze real-time workload data and predict future cloud resource needs, automating provisioning and scaling decisions to minimize waste while maintaining performance.
  • Use case: Netflix optimizes cloud costs by using AI-driven auto-scaling to dynamically allocate resources based on streaming demand, reducing unnecessary expenditure while ensuring a smooth user experience.

2. Serverless and Function-as-a-Service (FaaS) Evolution

That seamless experience where everything just works the moment you need it—serverless computing is making cloud management feel exactly like that. Serverless computing eliminates idle resources, cutting down costs while boosting cloud performance. You only pay for the execution time of functions, making it a cost-effective cloud optimization technique.

  • How it works: Serverless computing platforms like AWS Lambda, Google Cloud Functions, and Azure Functions execute event-driven workloads, ensuring efficient cloud resource utilization while eliminating the need for constant infrastructure management.
  • Use case: Coca-Cola leveraged AWS Lambda for its vending machines, reducing backend infrastructure costs and improving operational efficiency by scaling automatically with demand. 

3. Decentralized Cloud Computing: Edge Computing for Cost Reduction

Why send all your data to the cloud when it can be processed right where it’s generated? Edge computing reduces data transfer costs and latency by handling workloads closer to the source. By distributing computing power across multiple edge nodes, companies can avoid expensive, centralized cloud processing and minimize data egress fees.

  • How it works: Companies deploy micro data centers and AI-powered edge devices to analyze data closer to the source, reducing dependency on cloud bandwidth and lowering operational costs.
  • Use case: Retail giant Walmart leverages edge computing to process in-store data locally, reducing latency in inventory management and enhancing customer experience while cutting cloud expenses.

4. Cloud Optimization with FinOps Culture

FinOps (Cloud Financial Operations) is a cloud cost management practice that enables organizations to optimize cloud costs while maintaining operational efficiency. By fostering collaboration between finance, operations, and engineering teams, FinOps ensures cloud investments align with business goals, improving ROI and reducing unnecessary expenses.

  • How it works: Companies implement FinOps platforms like Apptio Cloudability and CloudHealth to gain real-time insights, automate cost optimization, and enforce financial accountability across cloud operations.
  • Use case: Early adopters of FinOps were Adobe, which leveraged it to analyze cloud spending patterns and dynamically allocate resources, leading to significant cost savings while maintaining application performance. 

5. Storage Tiering with Intelligent Data Lifecycle Management

Not all data needs a VIP seat in high-performance storage. Intelligent data lifecycle management ensures frequently accessed data stays hot, while infrequently used data moves to cost-effective storage. Cloud-adjacent storage, where data is stored closer to compute resources but outside the primary cloud, is gaining traction as a cost-efficient alternative. By reducing egress fees and optimizing storage tiers, businesses can significantly cut expenses while maintaining performance.

  • How it’s being done: Companies use intelligent storage optimization tools like AWS S3 Intelligent-Tiering, Google Cloud Storage’s Autoclass, and cloud-adjacent storage solutions from providers like Equinix and Wasabi to reduce storage and data transfer costs.
  • Use case: Dropbox optimizes cloud storage costs by using multi-tiered storage systems, moving less-accessed files to cost-efficient storage while keeping frequently accessed data on high-speed servers. 

6. Quantum Cloud Computing: The Future-Proof Cost Gamechanger

Quantum computing sounds like sci-fi, but cloud providers like AWS Braket and Google Quantum AI are already offering early-stage access. While still evolving, quantum cloud computing has the potential to process vast datasets at lightning speed, dramatically cutting costs for complex computations. By solving problems that traditional computers take days or weeks to process, quantum computing reduces the need for excessive computing resources, slashing operational costs.

  • How it works: Cloud providers integrate quantum computing services with existing cloud infrastructure, allowing businesses to test and run quantum algorithms for complex problem-solving without massive upfront investments.
  • Use case: Daimler AG leverages quantum computing to optimize battery materials research, reducing R&D costs and accelerating EV development.

7. Sustainable Cloud Optimization: Green Computing Meets Cost Efficiency

Running workloads when renewable energy is at its peak isn’t just good for the planet—it’s good for your budget too. Sustainable cloud computing aligns operations with renewable energy cycles, reducing reliance on non-renewable sources and lowering overall operational costs.

  • How it works: Companies use carbon-aware cloud scheduling tools like Microsoft’s Emissions Impact Dashboard to track energy consumption and optimize workload placement based on sustainability goals.
  • Use case: Google Cloud shifts workloads to data centers powered by renewable energy during peak production hours, reducing carbon footprint and lowering energy expenses. 

The Next Frontier: Where Cloud Optimization is Headed

Cloud optimization in 2025 isn’t just about playing by the old rules. It’s about reimagining the game entirely. With AI-driven automation, serverless computing, edge computing, FinOps, quantum advancements, and sustainable cloud practices, businesses can achieve cost savings and high cloud performance like never before.

Organizations that embrace these innovations will not only optimize their cloud spend but also gain a competitive edge through improved efficiency, agility, and sustainability. The future of cloud computing in 2025 isn’t just about cost-cutting—it’s about making smarter, more strategic cloud investments.

At Mantra Labs, we specialize in AI-driven cloud solutions, helping businesses optimize cloud costs, improve performance, and stay ahead in an ever-evolving digital landscape. Let’s build a smarter, more cost-efficient cloud strategy together. Get in touch with us today!

Are you ready to make your cloud strategy smarter, cost-efficient, and future-ready with AI-driven, serverless, and sustainable innovations?

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