Cloud technologies have become more important than ever with the rising need for scalable
and distributed software systems. A pattern that is used in many such systems is a
microservice-based architecture (MSA). MSAs have become a blueprint for many large
companies and big software systems. In many scientific fields like energy and environmental
informatics, efficient and scalable software systems with a primary focus on measurement
data are a core requirement. Nowadays, there are many ways to solve research questions
using data-driven approaches. Most of them have a need for large amounts of measurement
data and according metadata. However, many measurement systems still follow deprecated
guidelines such as monolithic architectures, classic relational database principles and are
missing semantic awareness and interpretation of data. These problems and the resulting
requirements are tackled by the introduction of a reference architecture with a focus on
measurement systems that utilizes the principles of microservices.
The thesis first presents the systematic design of the reference architecture by using the
principles of Domain-driven Design (DDD). This process ensures that the reference architecture
is defined in a modular and sustainable way in contrast to complex monolithic
software systems. An extensive scientific analysis leads to the core parts of the concept
consisting of the data management and semantics for measurement systems. Different data
services define a concept for managing measurement data, according meta data and master
data describing the business objects of the application implemented by using the reference
architecture. Further concepts allow the reference architecture to define a way for the system
to understand and interpret the data using semantic information. Lastly, the introduction of
a frontend framework for dashboard applications represents an example for visualizing the
data managed by the microservices
