Enhancing microservices architectures using data-driven service discovery and QoS guarantees

Microservices promise the benefits of services with an efficient granularity using dynamically allocated resources. In the current evolving architectures, data producers and consumers are created as decoupled components that support different data objects and quality of service. Actual implementations of service meshes lack support for data-driven paradigms, and focus on goal-based approaches designed to fulfill the general system goal. This diversity of available components demands the integration of users requirements and data products into the discovery mechanism. This paper proposes a data-driven service discovery framework based on profile matching using data-centric service descriptions. We have designed and evaluated a microservices architecture for providing service meshes with a standalone set of components that manages data profiles and resources allocations over multiple geographical zones. Moreover, we demonstrated an adaptation scheme to provide quality of service guarantees. Evaluation of the implementation on a real life testbed shows effectiveness of this approach with stable and fluctuating request incoming rates.