Architectural Practices for Improving Fault Tolerance in a Service-Driven Environment

Abstract

Enterprises that implement Service-driven applications face challenges relating to unprecedented scale, high availability, and fault-tolerance. There is exponential growth with respect to request volume in Service-driven systems, requiring the ability to provide multipoint access to shared services and data while preserving a single system image. Maintaining fault-tolerance in business services is a significant challenge due to their compositional nature, which instills dependencies among the services in the composition. This causes the dependability of the business services to be based on the reliability of the individual services in the composition. This chapter explores the architectural approaches such as service redundancy and design diversity, scaling, clustering, distributed data caching, in-memory data grid, and asynchronous messaging, for improving the dependability of services. It also explores the data scaling bottleneck in data centralization paradigms and illustrates how that presents significant scalability and fault-tolerance challenges in service-driven environments. Prevalent strategies to handle failure recovery such as backward and forward recovery mechanisms as well as the built-in mechanisms in WS-BPEL for exception handling and transactional compensation are discussed.