To evaluate the impact of memory management in Rust, I implemented a short benchmark in Rust and Kotlin. You can find all the details here and here. Measurements showed that Rust is roughly a factor of 10 faster than Kotlin, most probably caused by better handling of memory garbage. Being a big fan of Haskell, I was curious to see how the grand old lady of functional programming would compete against these two. So, I implemented the benchmark, did some measurements, and was surprised.Continue reading
This article is a follow-up to this previous article about bounded loops. Bounded loops are cool because they always terminate and usually it is pretty easy to estimate the computational time. But as every computer scientist, who had to understand the halting problem, knows, there is a big class of algorithms which are harder. These are known as the class of μ-recursive functions. Here, unbounded loops exists which can run forever. I will introduce how IMHO unbounded loops can be implemented in Kotlin in a functional way. And, of course, I could not resist and did some measurements…Continue reading
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
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.
For simple web sites a static web site generator is often sufficient. Jekyll is such a well know generator. In our company we use JBake, because of its good integration in the Java infrastructure. More information on that is found here: Integration of JBake in Maven – Static Websites.
In my nonbusiness life, I like to play with Haskell. This is why I used Hakyll for a small personal web site. I wanted it to be responsive and choose to use Foundation. To do some styling of the Foundation classes I needed to use SASS and embed it into Hakyll. It took me about two hours to put everything together. To save this time in the future, I extracted a small template with everything in it.