There may be cases when your REST api provides responses that are very long, and we all know how important transfer speed and bandwidth still are on mobile devices/networks. I think this is the first performance optimization point one needs to address, when developing REST apis that support mobile apps. Guess what? Because responses are text, we can compress them. And with today’s power of smartphones and tablets uncompressing them on the client side should not be a big deal… So in this post I will present how you can SELECTIVELY compress your REST API responses, if you’ve built it in Java with Jersey, which is  the JAX-RS Reference Implementation (and more)… 

This blog post is dedicated to my colleague Seminda who has been experimenting with how to create simple and powerful web applications. Thank you for showing me your ideas and discussing improvements with me, Seminda.

I find many C# applications have much unnecessary code. This is especially true as the weight of the business logic of many applications are shifting from the backend to JavaScript code in the web pages. When the job of your application is to provide data to a front-end, it’s important to keep it slim.

In this article, I set out to simplify a standard MVC 4 API controller by generalizing the functionality, centralizing exception handling and adding extension methods to the DB set that is used to fetch my data.

In this post I will present how to build a simple reference data cache in Java EE, using singleton EJBs and Ehcache. The cache will reset itself after a given period of time, and can be cleared “manually” by calling a REST endpoint or a MBean method. This post actually builds on a previous post How to build and clear a reference data cache with singleton EJBs and MBeans; the only difference is that instead of the storing of the data in a ConcurrentHashMap<String, Object> I will be using an Ehcache cache, and the cache is able to renew itself by Ehcache means.

In this article we will see how to configure and integrate SpringMVC4, Spring Data JPA with Hibernate and SpringSecurity using JavaConfig.

1. Pom.xml

First let’s configure all the necessary dependencies in pom.xml

ORM has a simple, production-ready solution hiding in plain sight in the Java world. Let’s go through it in this post, alongside with the following topics:

• ORM / Hibernate in 2014 – the word on the street
• ORM is still the Vietnam of Computer Science
• ORM has 2 main goals only
• When does ORM make sense?
• A simple solution for the ORM problem
• A production-ready ORM Java-based alternative