Automated functional and robustness testing of microservice architectures

Microservice Architectures (MSA) are nowadays largely adopted by companies in several domains to provide on-demand services. The reliability of microservices is fundamental to avoid failures compromising the business functionalities. MSA automated testing is possible thanks to well-defined service interfaces specified in open formats like OpenAPI/Swagger.To support automated MSA functional and non-functional testing, we define a framework that: (i) generates test cases with valid and invalid inputs, and executes and monitors tests; (ii) provides coverage and failure information not only on edge, but also on internal microservices; (iii) has the novel feature of identifying causal relations in observed chains of microservices failures.We abstract the testing process of MSA, present the MACROHIVE framework and its causal inference engine, compare it experimentally to state-of-the-art tools, and discuss its benefits in the MSA testing process.MACROHIVE exhibits performance comparable to advanced existing tools in terms of edge-level coverage. However, MACROHIVE has a better failure rate and provides the unique advantages of giving insights about internal coverage and failures, and of inferring causality in failure chains, evidencing microservices to be improved to increase the whole MSA reliability.