Applying Continuous Delivery means to automate the delivery pipeline and to release frequently. However, databases are a big challenge, because with every deployment we may need to update and migrate our database before we can deploy our application. This post points out solutions for dealing with databases in a Continuous Delivery scenario.
Introducing Continuous Delivery means to automate the delivery process and to release our application frequently. This way, we improve the reliability of the release process, reduce the risk and get feedback faster. However, setting up a Continuous Delivery pipeline can be difficult in the beginning. In this step by step tutorial I will show you how to configure a simple Continuous Delivery pipeline using Git, Docker, Maven and Jenkins.
Docker allows us to easily create reproducible environments for our application. We automate the setup of the environment and eliminate manual error-prone tasks. This way we reduce the risks and the reliability of the deployment process. But there are also challenges and domains, where the usage of Docker can be difficult. This post discusses several advantages of Docker and points out some drawbacks.
Dropwizard produces a fat jar containing every dependency your microservice needs to run. This includes a web server. This way, no web server needs to be installed and configured on the target machine. However, there is some infrastructure left (like the JRE) which still has to be installed before the deployment. That’s where Docker enters the stage. With Docker we can produce an artifact containing really everything we need to run our microservice. In this post, we take a look at how we can integrate Docker into our Maven build, run our tests against the container and push the image to a repository.
Consuming RESTful services can be a laborious task, because there is much low-level-work to do. Jealously we looked at the WS*/SOAP guys: They can easily generate a nice client API based on the formal interface specification WSDL. This significantly simplifies the service consumption. For a long time the REST world lacks a widespread formal specification and generation tools. But Swagger sets out to change this.
Relational Databases seem to be the universal hammer in the toolbox of every developer. There is the notion that you can solve every problem with it – you just have to smash hard enough. However, if you use relational databases out of habit, you can easily run into troubles when it comes to schema evolution, scalability, performance or certain domains. This post discusses the strength and weaknesses of relational databases and points out alternatives.
Microservices are an interesting approach for achieving modularization of an application. An application is built as a set of services. These services can be independently developed, tested, built, deployed and scaled. However, microservices are not suitable for every use case. This post discusses the benefits and drawbacks of microservices.
Java has checked exceptions and is out on a limb. Is there a reason, why other languages like C++, Objective-C, C#, Kotlin, Scala don’t support this concept? What is the problem about checked exceptions and what can we do instead? And most important: What do water wings and checked exceptions have in common? This article gives the answer to all of these questions and shows why unchecked exceptions are the better choice.
Designing HTTP and RESTful APIs can be tricky as there is no official and enforced standard. Basically, there are many ways of implementing an API but some of them have proven in practice and are widley adopted. This post covers best practices for building HTTP and RESTful APIs. We’ll talk about URL structure, HTTP methods, creating and updating resources, designing relationships, payload formats, pagination, versioning and many more.
Vaadin is a mature web framework for developing rich internet applications. Building web-based GUIs with Vaadin feels like developing a desktop application, which is great, comfortable and fast. However, there are situations where Vaadin is not suitable. In this article, we take a look at the architecture of Vaadin and point out its strengths and weaknesses. Let’s start.