The online website Skill Circuits is a tool developed by teachers at the Delft University of Technology. Skill Circuits is an online learning tool that presents students with a node-link (i.e. a tree) structure where each node represents a skill, containing tasks that aim to teach the skill. The website aims to benefit teachers, by letting them think how all the 'skills' in their course relate and whether or not they have sufficient material to teach these skills. At the same time, the website aims to benefit students by giving them a learning path to follow, where each step is a small task, and each skill is visually connected to previous skills, showing how the learning material is connected.
This thesis aimed to help new teachers understand the concept of these node-link structures --- called skill circuits --- and also expand the website with features to help them evaluate their skill circuits, both before and during the course.
A documentation help page was developed, which explained the concept and intended usage of the website and was accompanied by a proof-of-concept skill circuit explaining the same topics. Tools to help evaluate a skill circuit were also developed, which included tools that could be used before the course was held, and tools that used analytics generated by students. One noteworthy tool took inspiration from the Constructive Alignment principle, where a teacher can label parts of their skill circuit with learning objectives to see if there is alignment with their course material.
All of these features were evaluated with a small focus group consisting of teachers, which showed enthusiasm toward the proposed features.

It has become a common practice for software developers to analyse monitoring data as a means to understand issues, trends and performance of large-scale software systems. The combination of this practice with the software development workflow can however be cumbersome at times. One recent effort into evaluating the effects of integrating monitoring directly into the software development workflow has been done at the large-scale payment company Adyen in cooperation with the TU Delft. This project is a new attempt at making a flexible, open-source and useful monitoring tool based on the results of that research effort. This report will detail how the system is designed, implemented and the development methodology that was used for its creation. After researching popular monitoring stacks and solutions, an architecture for the Hyperion pipeline was designed that would maximize compatibility with logging setups. The monitoring data is first retrieved from a log source like Logstash or Elasticsearch. It is preprocessed by a pipeline consisting of configurable and flexible plugins. A large range of plugins is supported: functionalities include debugging, transformation, load balancing, and adding new data from third-party systems. There is also extensive support for third-party developers to create their own pipeline plugin to manipulate data in any way required, which allows Hyperion to account for unconventional logging setups. The pipeline typically ends at some type of aggregator, which exposes an interface for developer tools to retrieve metrics. These metrics can be queried with the Hyperion IDE plugin, which visualizes them in the development environment itself. To verify that the designed Hyperion pipeline adheres to the requirements defined in the research report, validation tests have been performed on every module of the system. All code is extensively tested with unit, integration, and container-based system tests. An evaluation of the performance of the pipeline additionally verified the scalability of the system even when provided with a large number of incoming logs. Finally, in order to ensure easy extension and adoption of the Hyperion pipeline a large amount of documentation was written, that explains the architecture of the project and how a third-party developer can adjust and extend it.