Fault Tolerance of Stateful Microservices for Industrial Edge Scenarios

Yuke Jia, Tiejun Wang, Tianbo Qiu, Xiaohan Zhang, Rui Wang, Tianyu Wo
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Abstract

Due to the ubiquitous increase of Industrial Internet of Things(IIoT) devices, there is a tendency to move some of the microservices-based applications from Cloud to Edge. However, edge devices are prone to node failures because of weak reliability, resulting in the loss of stateful microservices computing state, which may involve fault tolerance of stateful microservices. Moreover, the method of traditional mechanisms for microservices fault tolerance could not meet the real-time requirement. Within this context, based on stateful microservices characteristics, we propose a novel fault tolerant mechanism for IIoT Edge, which mainly consists of causal logging and distributed checkpoint algorithm. This fault recovery mechanism utilizes causal logging to record the nondeterministic events of microservices, and completes the state recovery of microservices by loading checkpoint and replaying log records, which achieves exactly-once guarantees for distributed microservices. In addition, a set of experiments was performed to evaluate the proposed mechanism by integration with Kubernetes. The results show that the proposed mechanism has less impact on service performance compared with other methods.
工业边缘场景下有状态微服务的容错
由于工业物联网(IIoT)设备的普遍增加,有一种趋势是将一些基于微服务的应用程序从云转移到边缘。但是,边缘设备由于可靠性较弱,容易出现节点故障,导致有状态微服务计算状态丢失,这可能涉及到有状态微服务的容错。传统的微服务容错机制无法满足实时性要求。在此背景下,基于有状态微服务的特点,提出了一种新的IIoT Edge容错机制,主要包括因果日志和分布式检查点算法。该故障恢复机制利用因果日志记录微服务的不确定性事件,并通过加载检查点和重放日志记录完成微服务的状态恢复,实现了分布式微服务的“一次精确”保证。此外,通过与Kubernetes集成,进行了一组实验来评估所提出的机制。结果表明,与其他方法相比,该机制对服务性能的影响较小。
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