Firebase adds a new local emulator UI, payment processing extensions, and ML Model Management API

Firebase is a toolset provided by Google, functioning as a unified backend-as-a-service (BaaS) platform for mobile developers. In a nutshell, Firebase provides a fair few tools for in-code utilities like analytics, authentication, databases, configuration, push messaging, file storage, and more. The overall platform helps developers accomplish a lot of common tasks within their apps without needing to individually build their own solutions for these tasks. For instance, the Firebase Auth SDK makes it easy for developers to add a complete sign-in system with an accompanying UI to their apps. Recently, Firebase has added new tools and features, such as a new emulator UI, Stripe payment processing extension, an enhanced TensorFlow lite deployment, and more.

New emulator UI for local development

The Firebase Emulator suite was launched last year, and now, the Firebase team has launched a new local emulator UI in the beta release channel. This emulator UI will aid developers to easily and safely test new code without needing to wait on deployments or experiencing billing costs. You can also onboard new developers with just a few CLI commands that can create local instances of Firebase services quickly.

The Emulator Suite also now supports instant code reload of security rules.

Stripe payment processing extension

Firebase also offers Extensions, which are pre-packaged bundles of code that developers can use to automate common developer tasks. Now, Firebase has built two new Extensions in partnership with Stripe, which allows developers to quickly add and manage payments processing capabilities to their apps. The Send Invoices with Stripe Extension lets developers programmatically create and send branded customer invoices using the Stripe payments platform. The Run Subscription Payments with Stripe Extension can be used to create and sync subscriptions for web users with Stripe, as well as control access to subscription content via Firebase Authentication. With these extensions, you as a developer do not need to learn Stripe’s API or figure out how to integrate Stripe with Firebase — simply install these extensions and you should be ready to go.

Enhanced TensorFlow Lite deployment

Firebase has also introduced the ML Model Management API which allows developers to programmatically update and deploy ML models to TensorFlow Lite without needing to use the console. This is especially useful when there is a machine learning pipeline that automatically retrains models with new data since you can now upload the updated models to Firebase programmatically. This claims to reduce the initial app installation size, allow for A/B testing multiple models, evaluate performance, and update models without needing to republish the entire app.

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Since there have been no physical events in the past few months, Google has been hosting Firebase Live videos to inform and educate developers on various related topics. Google has also announced a lot of new features and improvements to Firebase over the year, including Early Access Programs API, Cloud Firestore for C++ and Unity, and Sign-in with Apple through Firebase Authentication.

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