Because everyone should use Hexagonal architecture…​ except when they shouldn’t.

One of the great features of Kotlin is its interoperability with Java code. This allows you to easily call 'traditional' Java code from your Kotlin code, but it also helps you the other way around: calling Kotlin code from Java.

Sometimes, a little extra work is needed to make some shiny Kotlin feature work with Java code. For example, Kotlin supports default parameter values, which are not supported in Java. In this case, the @JvmOverloads annotation can be used to generate overloads for functions that contain parameters with default values. This annotation does not only work on functions, but can also be applied on constructors. In this post I will explain how to use this feature on the primary constructor, as it might be confusing where to place the annotation.

If you’ve been working with Spring Security for a while, it should come as no surprise that from time to time, they deprecate the old, and guide you towards the new. In 5.7.x such a change involves the often used WebSecurityConfigurerAdapter.

And while there are blog posts, release notes, and even an instruction video to highlight the required changes, in the end you will have to change your code. But what all those sources so far have failed to cover, is that there’s now also an easier way to migrate your code, using OpenRewrite.

Wasm is secure through sandboxing and capability based design. What does this mean for networking? And why has networking taken so long to be supported by WASI?

We’re making an API to collect cats. We’ll be using ZIO 2.0, and Caliban

Renovate can automate your dependency updates, similar to what you might have seen with Dependabot. But where Dependabot requires a community maintained project to run on GitLab.com, Renovate integrates nicely with GitLab.com through official support.

In this blogpost we will walk through setting up Renovate for use on GitLab.com.

In a previous post we learned about the macros SV, SVI and SVD that return a string representation of variables with their name and value. Groovy 4 also added the NP and NPL macros that we can use to inspect variables. Instead of returning a GString instance these macros return a NamedValue instance or a list of NamedValue value instances. The NamedValue class is a simple class with a property name, containing the name of the variable, and property val with the value of the variable. The macro NP can be used when we have a single variable and result is a single NamedValue instance. An the macro NVL can be used with multiple variables. The result is a list of NamedValue instances where each instance represent a variable passed as argument to NVL.

Groovy 4 added some built-in macros that we can use in our code. A macro is code that will create new code. It does this by manipulating the Abstract Syntax Tree (AST) before the code is compiled. So when we use a macro, the macro will change the AST and those changes will be compiled. The three built-in macros SV, SVI and SVD can create a GString instance with the names and values of the variables that are passed as argument. This can be very useful to create some meaningful debugging statements. Normally we would have to type in the variable name ourselves followed by the value. Now with these macros we don’t have to type the variable as the macro will add that to the AST for us.

DataWeave has a nice language feature called literal types. Literal types are types with a single predefined values and can be defined using a String, Number or Boolean value. So the value of a literal type is a fixed value. We can combine multiple literal types into a new type using a union type to define an enumaration in DataWeave. The enumaration can only be one of the literal types used to define it.
Together with overloaded functions literal types are very useful. We can define a function where one of the input arguments is a literal type to define specific behaviour based on the literal type. Then we can overload the function for other literal types with different behaviour. DataWeave will make sure the correct function is called based on the value of the input argument and how it matches to the literal type value.