Loops are a basic paradigm in imperative programming languages. In functional languages you also need to loop, but you do it differently. Here, I present how I prefer to implement loops in a functional style using Kotlin. To check, if this is a good idea at all, I do some benchmarks against imperative variants and good old Haskell.Continue reading
Sodium is an implementation of Functional Reactive programming (FRP) with some nice features. One of these is the support of transactions in the GUI layer. I had quite some discussions with my colleagues on what this actually means and if such a transaction concept is useful or not. In this article I sum up my current insights and opinions about transactions in Sodium.
When we began a new project recently the team thought about using Kotlin over Java to implement the backend. The project lead had issues with this because there was no clear information on how Kotlin would be supported by tools like Sonar and Jacoco. Since these tools deliver important information about code quality and potential issues we decided to spend some time on evaluating how these tools would collaborate with Kotlin.
Functional reactive programming (FRP) is a variant of reactive programming for the development of user interfaces based on the functional paradigm and a strict set of basic operators. In contrast to reactive frameworks, such as RxJs, using FRP enables a developer to define a pure area in her code in which some error classes, typical for event-based architectures, do not occur. Sodium is an FRP-framework, which is independent of a specific GUI-framwork and supports several different programming languages. Here, we describe how to use Sodium together with Angular.
Deploying a Docker container on Azure ‘Web App for Containers’ can be done fairly easy. In this blog post, I will provide a step by step guide to get you started. Some basic knowledge of Azure and Docker definitely helps. But why should you care in the first place? You will get:
- a managed runtime (for a single image)
- scaling to multiple instances
- a simple deployment model
- easy integration with App Insights (Azure’s Monitoring system for Web Apps)
- use any Azure SaaS like CosmosDB, MSSQL, …
In No more Ifs I wrote a little bit about the new Optional class in Java 8. It enables the developer to work with optional values without a complex nested structure of if-then-else expressions. A colleague of mine, being a big fan of Kotlin, dropped a hint that using Kotlin, it would be much easier. He could even prove it. 🙂
Java 8 introduced with
Optional a functional datatype that enables the developer to work with optional values without nested if-statements. This can simplify your code a lot.
Inspired by my article The lightweightness of microservices – Comparing Spring Boot, WildFly Swarm, and Haskell Snap, a colleague of mine implemented the same Web service using the Go programming language. You can find his code here: Bitbucket-repo. To compare his implementations with the other ones, I integrated it into the main project (GitHub-repo) and measured it. Here are the results. 🙂
A microservice is an autonomous sub application for a strictly defined and preferably small domain. An application built from microservices is scalable, resilient, and flexible. At least, if the services and their infrastructure are well designed. One requirement on the used frameworks to achieve scalability and resilience is that they are lightweight. Lightweightness comes in different flavors. Microservices should be stopped and started fastly, and should consume few resources. The development and maintenance of microservices should be easy.
For this reason, in the Java world, Spring Boot is currently recommended as best choice regarding these requirements. Traditional Java EE application servers are too heavyweight, because they are not developed as basis for single services but as platform for running different applications simultaneously. Thus, they must be bloated.
Being a curious person I used some of my spare time in the last Christmas holidays to actually measure the lightweightness. First I chose Spring Boot and WildFly as “competitors”. I added WildFly Swarm which provides similar features as Spring Boot but is based on WildFly. Then looking at the requirements I decided to include a framework with a real small startup time in comparison to Java-based frameworks and chose Snap based an Haskell. For every framework I built a minimal micro service, wrapped it into a Docker container, and measured its weight.