This paper presents the first comprehensive review of techniques that pertain to Fault Injection Testing (FIT) of Microservice systems. FIT is a popular resilience engineering technique for examining the correctness and robustness of fault-tolerance mechanisms in software systems. Despite its wide adoption in building Microservice systems of high reliability, the techniques and tools that underpin effective fault injection have not yet been systematically reviewed. To this end, a general FIT framework that consists of five key components is first summarized, with each component indicating a key design decision that should be carefully determined. Then, a systematic literature review (SLR) is performed to investigate the current practices that address the challenges associated with each of these components. Finally, the potential limitations and future research directions of FIT for Microservice systems are discussed.

Modern large-scale service systems are usually deployed with redundant components to ensure high dependability in distributed and volatile environments. Fault Injection Testing (FIT) is a popular technique for testing such systems, while the application of FIT to validating the correctness of redundant components remains a challenging task, especially when the system's structural information is unavailable when testing starts. In this study, we refer to a minimum set of faults that, when injected, will cut off all execution paths in a service system as afault-tolerance bottleneck, and we propose a novel Fault-tolerance Bottleneck driven Fault Injection (FBFI) approach to the exploration and validation of redundant components without prior knowledge of the system's business structure. The core idea of FBFI is to iteratively infer and inject bottlenecks of the business structure constructed so far. In this way, FBFI is able to discover and test redundant components by repeatedly triggering new system behaviors. The effectiveness and efficiency of FBFI is evaluated using two microservice benchmark systems with different deployment scales. The results reveal that FBFI is more practical and cost-effective than random and lineage-driven FIT approaches in testing service systems of high redundancy levels.