Java EE 8 REST Clients, JSON and Mobile App

Learn about Reactive REST Clients in a Microservice, How to use the new JSON Binding API and Enterprise Functionality for Mobile App from video reports
27 September 2017   1706

Java 8 EE was released recently. It's about time to get up to speed with important APIs. Learn about key Java EE 8 APIs and how to connect your mobile applications to a Java EE backend with three video reports. 

Reactive REST Clients in a Microservices Landscape with David Delabassee. When designing microservices exchanges, REST is clearly the most popular approach, i.e. the de-facto standard. JAX-RS API hides all the low-level details behind RESTful calls. Complexity really starts to arise when multiple remote services need to be consumed in highly efficient manner. During this technical session, you will learn in details different solutions and best practices to efficiently consume REST services. This includes: 

- Synchronous Vs. Asynchronous
- Jersey Reactive Client API
- Popular Reactive libraries (e.g. RxJava)
- JAX-RS 2.1 Client API

How to use the new JSON Binding API with Dmitry Kornilov. JSON support is an important part of Java EE. This session provides a deep dive into JSON-P and JSON-B APIs explains how they are connected and can be used together. You will learn about new JSON-P features such as JSON Patch, JSON Pointer, and JSON Merge Patch as well as JSON-B features such as default and customized mapping, adapters, and serializers.

Enterprise Functionality for Mobile Apps with Johan Vos. Today an increasing number of companies and organizations are facing demands from their users (customers, partners, employees, and end-users) to make their enterprise functionality available via mobile apps. While many concepts that are used on the web also apply to mobile apps, the users of those apps typically expect more than just a website. In this session, you will learn how you can reuse your existing investments in enterprise code and infrastructure, and easily add a mobile channel. You will learn how the Oracle Cloud provides a great platform for bridging the gap between your enterprise code and the mobile apps your users are asking for.

Google to Release Cloud Inference API

Cloud Inference API can be used for real time big data analysis 
20 September 2018   95

Google introduced an alpha version of the service for time series analysis. It processes information about events at the time - clicks, requests, activations of IoT devices, and so on. The Cloud Inference API analyzes these data in real time, finds correlations and makes predictions based on it.

Cloud Inference API
Cloud Inference API 

Service features:

  • A simple tree-like query language that allows you to specify your own time markers.
  • Online processing of incoming data with minimal delay. Therefore, Google recommends using the API in interactive user applications.
  • Ability to process data arrays of different volumes (up to trillions of records) and work under high load (up to hundreds of thousands of requests per second).
  • Full integration with Google Cloud Storage, which provides access to the same data in different services of the platform.
  • More information about the work of the tool can be found in the documentation.

Google noted that the service will be useful for a wide range of industries. Retailers can analyze the impact of pedestrian traffic on the level of sales conversion, content providers - the popularity of materials to provide better personal recommendations.

Now the Cloud Inference API is already being used by Snap to analyze the data received through the Snapchat application.

Google Cloud is developing a number of cloud services. At the end of August 2018, the company updated the tools for converting speech to text and vice versa. Cloud Text-to-Speech received support for several new languages ​​and voices, and Cloud Speech-to-Text - recognition of several speakers, language and the ability to highlight important words