As I'm writing this, I have been working hard for the Platformatic v1.0.0 launch on Tuesday, the 26th of September (tomorrow as you are reading this). Register to be part of the excitement!
After almost 10 years of defending my Ph.D., I would have never imagined that. I got back to writing a research paper as part of my startup. As part of our business research in Platformatic, Luca Maraschi and I identified a critical problem every adopter of a microservice system had: catch a breaking change in one microservice before it could cause downtime in others. We knew we had to build something new, and we identified an algorithm and an architecture to map the complete network of microservices in a system and calculate a percentage of risk.
In a microservices-based system, reliability and availability are key components to guarantee the best-in-class experience for the consumers. One of the key advantages of microservices architecture is the ability to independently deploy services, providing maximum change flexibility. However, this introduces an extra complexity in managing the risk associated with every change: any mutation of a service might cause the whole system to fail. In this research, we would propose an algorithm to enable development teams to determine the risk associated with each change to any of the microservices in the system.
Download the full paper on Arxiv.