HawkEDA: a tool for quantifying data integrity violations in event-driven microservices

Abstract

A microservice architecture advocates for subdividing an application into small and independent components, each communicating via well-defined APIs or asynchronous events, to allow for higher scalability, availability, and fault isolation. However, the implementation of substantial amount of data management logic at the application-tier and the existence of functional dependencies cutting across microservices create a great barrier for developers to reason about application safety and performance trade-offs. To fill this gap, this work presents HawkEDA, the first data management tool that allows practitioners to experiment their microservice applications with different real-world workloads to quantify the amount of data integrity anomalies. In our demonstration, we present a case study of a popular open-source event-driven microservice to showcase the interface through which developers specify application semantics and the flexibility of HawkEDA.