If you want to quickly test your REST api from the command line, you can use curl. In this post I will present how to execute GET, POST, PUT, HEAD, DELETE HTTP Requests against a REST API. For the purpose of this blog post I will be using the REST api that supports www.bookmarks.dev. The API is documented with OpenAPI and available for testing in the browser at https://www.bookmarks.dev/api/docs/.

Basic time notions

Most web applications have to support different time-zones and properly handling time-zones is no way easy. To make matters worse, you have to make sure that timestamps are consistent across various programming languages (e.g. JavaScript on the front-end, Java in the middleware and MongoDB as the data repository). This post aims to explain the basic notions of absolute and relative time.

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.