It’s hard to believe that Fireabse has grown from a backend and service Baas to a full life cycle App development platform in just two years. Since then, we’ve been very humble about what the developer community has said about Firebase. Firebase now has 1.2 million applications using it every month.
No matter how strong we grow, our mission remains the same: to help mobile application teams succeed in all phases of application development, from application construction to application quality improvement and business growth.
Having such a large developer community is a great honor and a great responsibility. Thank you developers for believing in Firbase. It’s really exciting to hear about developers building applications using Firebase. Your success is why we’re excited to go to work every day.
Today, we’re announcing some improvements to Firebase, so let’s take a look:
Introduce ML Kit to Firebase and release the public test version
We are pleased to announce the introduction of ML Kit to Firbase. This makes it easier for mobile developers to use machine learning. ML Kit is an SDK available on Firebase. Whether your app is Android or iOS, whether you are new to machine learning or a professional developer, ML Kit can provide powerful machine learning capabilities for your app.
ML Kit provides some common apis, such as text recognition, face detection, scanning bar codes, tagging images, and identifying landmarks. These apis are available both in the cloud and offline. You need to refer to which function of the API to call. Even if there is no network connection, the API on the device can quickly process the data, while the API of the base Cloud can take advantage of the machine learning function in the Google Cloud Platform to improve the accuracy of recognition. You can use advanced features such as data models in TensorFlow Lite or custom data models. ML Kit takes care of hosting services, allowing you to focus more on building applications.
These five apis are just the first step in ML Kit. We will release more apis in the future. If you would like to be an early adopter of ML Kit, please fill out the registration form to join the early adopter list.
Whether you’re building Android or iOS apps, you can use machine learning to improve the user experience. With ML Kit, we wanted to make it easy for developers at all levels of experience to get started.
Improve performance monitoring capabilities
In Google I/O last year, we released a test version of performance monitoring to help you better understand your application’s performance and make it perform better. Since then, we’ve seen a lot more. Some of the largest applications in the world (e.g. Flipkart, Ola and Swiggy) are already using performance monitoring. And we generate 100 billion performance metrics every day to help developers improve the quality of their applications and the user experience.
Now that the performance monitoring SDK has been tested, we are releasing the official version. After publishing, you should see the following changes in the console:
First, you’ll see a summary of application problems at the top of the row monitor dashboard. The profile makes it easy to understand any performance issues that occur with your application, as well as recommendations for Firebase-related performance issues.
Second, you can easily see which interface in your application is having problems, and performance monitors can identify rendering problems and tell your application how many frames per screen are missing so you can quickly fix them. If you have a reference in the Play store, you don’t need to write any more code to immediately get detailed information about the problem in your app. You can get started quickly with our documentation.
Better analytics and access management
With Google Analytics for Firebase, you can see the analysis results for each reference. Last year, we added the ability to try and view data, and it added StreamView and DebugView reports. Now, you’ll notice that we’ve added real-time cards to our Google Analytics reports to give you a better idea of what features your users are using in your app.
The analysis results were updated twice by adding project-level reports and filters. Project-level reports allow you to see the status of all the applications in your project to get a fuller picture of the application business, while filters allow you to more precisely segment the data to get the key data information. These updates will be rolled out in the coming weeks.
Our other update to the Firebase console today is improved identity and access management. This makes it easy to invite others to collaborate on your project and control what they have access to. Everything is done in the Firebase console.
Extend Firebase Test Lab to iOS
In Firebase, building products that work on Android and iOS is very important. That’s why we’re extending Firebase Test Lab to iOS.
Test Lab provides you with both physical and virtual facilities that you can run to simulate real-world usage scenarios. With the addition of iOS Test Lab, Firebase can help you quickly debug your app to its optimum state.
The iOS Test Lab will launch in the next few months. If you want to be an early tester, you can sign up this way.
This is just the beginning
Firebase has undergone an extraordinary transformation so far, and we believe this is just the beginning. Through deep integration with the Google Cloud Platform, the goal is to make it easy for you to use Google’s vast base of services. We’re also very excited about the possibilities that machine learning can give developers. Firebase Predictions and ML Kit are just the first two steps and we hope we can do more.