Quick and easy: A multi-node Kubernetes cluster on CentOS 7 + QEMU/KVM (libvirt)

Kubernetes is a popular container orchestration platform. As a developer understanding the environment in which your application is going to run is important since this can help you use available services of the platform and fix issues.

There are several options to run Kubernetes locally to get some experience with Kubernetes as developer. For example Minikube, MicroK8s and MiniShift. These options however are not representative for a real environment. They for example usually do not have master and slave nodes. Running locally requires quite different configuration compared to running multiple nodes in VMs. Think for example about how to deal with storage and a container registry which you want to share over the different nodes. Installing a full blown environment requires a lot of work and resources. Using a cloud service usually is not free and you usually have less to no control over the environment Kubernetes is running in.

In this blog I'll describe a 'middle way'. Get an easy to manage small multi node Kubernetes environment running in different VMs. You can use this environment for example to learn what the challenges of clusters are and how to deal with them efficiently.

It uses the work done here with some minor additions to get a dashboard ready.

Spring: Blocking vs non-blocking: R2DBC vs JDBC and WebFlux vs Web MVC

Spring Framework version 5, released in Sept 2017, introduced Spring WebFlux. A fully reactive stack. In Dec 2019 Spring Data R2DBC, a reactive relational database driver was released. In this blog post I'll show that at high concurrency, WebFlux and R2DBC perform better. They have better response times and higher throughput. As additional benefits, they use less memory and CPU per request processed and when leaving out JPA in case of R2DBC, your fat JAR becomes a lot smaller. At high concurrency using WebFlux and R2DBC is a good idea!