For the relaunch of my personal website, I used the awesome Hugo static website generator, and for a shorter leadtime, extended it with two custom Hugo Shortcodes I use frequently. Automatic Gallery The template I am temporarily using for the launch phase already contains basic gallery support with the primary aim of styling based on Fancybox, but it lacked automatic serving of a directory as a gallery. What I knew was that I wanted to drop my galleries under /static/galleries/{name}, as I heavily prefer the convention-over-configuration maxime.

Having used legacy PHP-based CMS solutions such as Wordpress or Typo3 for a long time, I finally switched back to a static website generator, for various reasons. In this article, I want to outline a setup which makes it possible to treat distributed website development as clean as any other software, including versioning and continous deployment. Why Hugo? I retired Wordpress in favor of Hugo for several reasons: Wordpress has a very old codebase with mixed quality and reliability A lot of work was required to make it secure.

Given an overall systems architecture or infrastructure which gets the “IoT” box ticket, the will probably be a place where data transfer and size will come into account, for instance if constrained devices are using a potentially unreliable or expensive connection, such as a cellular data connection. For instance, an enbedded monitoring device which serves the purpose of delivering real-time telemetry to the core system of a car manufacturer will quickly come to a point where JSON-Encoding might exceed the computing power required for the actual job.

Thank you very much for attending my first conference talk on JCON which was, besides many talks at smaller user groups, actually my first big conference talk. The slides Data Serialization Frameworks for Java and the IoT from Manfred Dreese Companion Article Data Serialization Frameworks in Java

This is a companion article for my first talk at the Go User Group “Gophers” Aachen about Protocol Buffers and coupling Go services with Java. In a distributed system it is required to go beyond communication by shared memory, and even cross technology borders. This is nothing uncommon, it is more or less standard for a contemporary system to be designed as a distributed, interlinked collection of software modules which are not necessarily implemented in the same technology or even computer architecture.

In various test cases, primarily those covering components that interact with the filesystem and use filesystem entitites for a convention-based operation, it perfectly makes sense to provide a filesystem resource in an expected state to assess the component-under-test’s behavior. To provide a resource in an expected state, the classic approaches are: Have a handcrafted directory with testdata on the developer machine Couple the testdata with the source in the repository Both methods are quite poor, as the first will definitively yield into trouble when the application gets built on a CI or any other machine, or when the fact that the local filesystem is anything but immutable shows it evil face.

Performance Testing with Apache jMeter Designing and implementing distributed systems, both customer-faced or just datacrunching farms, one is soon required to determine performance impacts and possible bottlenecks. In this specific case, I wanted to gain information regarding the limits and scalability aspects of a customer-facing web application which also manages a high number of connected devices. Why I chose Apache jMeter The performance testing case I was working on made me opt for jMeter in the end, for the following reasons: