Java Optional and Kotlin Nullable

We are using Kotlin and Spring Boot in one of our projects. This includes Spring Boot Jpa Repositories. We are using a CrudRepository that provides basic functionalities like save(), delete(), findById() etc. This library is written in Java, hence method signatures look like this:

Optional<T> findById(ID var1);

Using this API out of the box would force us to deal with cumbersome Java Optionals. Since we are implementing in Kotlin we would like to use Kotlin Nullables instead and as it turned out we can achieve this very easily.

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Logging with Azure Application Insights – Part 1: Spring-Boot

When developing and running apps inside Microsoft Azure you have to deal with the topics like monitoring and logging. Azure provides a central solution for that question which is Application Insights. AppInsights (for short) is the central hub to get metrics and log data from our applications and let you access these data within the azure portal in an easy and convenient way. While the metric aspect is well documented, how to connect your favorite application logger to AppInsights it is not.

In this blog post we will show you how to enhance your typical Spring-Boot application to have all the logging data send to Azure AppInsights automatically. In a followup post we will show the same for a typical nodejs based application.

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Multi-target compilation with Kotlin

Kotlin allows to compile application code for different platforms, namely into JVM (byte code), JavaScript and native binaries. In one of our projects we were facing the challenge to use the same source code as well in a Java client as in a web application written in TypeScript/Angular. The main reason not to just copy the code and convert it manually to TypeScript is maintenance, i.e. the code is expected to evolve over time.

Thus we came up with the solution to convert the original Java code to Kotlin and compile it for both platforms.

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Different JSON views from a single source

Getting data in JSON format via REST services from the backend server is common practice. In the simplest case a JSON provider like Jackson translates your Java objects into a JSON string and back into Java objects automatically.

However, this does not cover cases where the data model (e.g., implemented as JPA entities) is different from the view model. For example, if you have BLOBs in your model it does not make much sense to transfer them as BASE64 encoded strings. Mostly, because BLOBs tend to be large and may not be needed at once.

In this article we will show how to provide different JSON “views” or dialects of the data using the same REST service.

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Jacoco and Sonar with Kotlin

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.

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