Today, we are delighted to announce the successful defense of the outstanding master’s thesis titled “Architectural Anti-Pattern Identification and Mitigation in Microservice Applications Based on Telemetry” by our master student, Amund Lunke Rohne from the University of Amsterdam. This master’s project was a collaborative effort involving TNO-ESI and Thales.
The thesis addresses the problem that microservices offer benefits like scalability and separation of concerns, but also introduce many complex service dependencies. The decomposition of microservice applications can impact system performance and maintainability and can lead to architectural anti-patterns over time. While simple anti-patterns can be detected using analysis of service dependencies, there is a lack of formal mathematical definitions which prevents more complex anti-patterns from being automatically detected by tools. The thesis introduces a novel model called Granular Hardware Utilization-Based Service Dependency Graph (GHUBS), a fine-grained model that captures the interactions dependencies between services at the level of individual requests. The GHUBS model can be manually specified in early design phases to validate a microservice decomposition, or automatically created using telemetry data from a running application. Mathematical formalizations are introduced for four common architectural anti-patterns and methods for automatically detecting them using the GHUBS model is presented. A method for recommending how to mitigate the identified anti-patterns based on the service dependencies in the GHUBS model, as well as resource utilization metrics for the services, is also presented. The approach is implemented in a tool called Televisor and validated through case studies on open-source microservice benchmarking applications, revealing instances of these anti-patterns.
We thank Amund for his work and a fruitful collaboration, and wish him the best of luck in his future career.