Assessing Database Contribution via Distributed Tracing for Microservice Systems

Abstract

Microservice architecture is the latest trend in software systems development and transformation. In microservice systems, databases are deployed in corresponding services. To better optimize runtime deployment and improve system stability, system administrators need to know the contributions of databases in the system. For the high dynamism and complexity of microservice systems, distributed tracing can be introduced to observe the behavior of business scenarios on databases. However, it is challenging to evaluate the database contribution by combining the importance weight of business scenarios with their behaviors on databases. To solve this problem, we propose a business-scenario-oriented database contribution assessment approach (DBCAMS) via distributed tracing, which consists of three steps: (1) determining the importance weight of business scenarios in microservice system by analytic hierarchy process (AHP); (2) reproducing business scenarios and aggregating the same operations on the same database via distributed tracing; (3) calculating database contribution by formalizing the task as a nonlinear programming problem based on the defined operators and solving it. To the best of our knowledge, our work is the first research to study this issue. The results of a series of experiments on two open-source benchmark microservice systems show the effectiveness and rationality of our proposed method.