Scalable and Decoupled Logging for State Machine Replication
Luiz Gustavo C. Xavier, Fernando Luís Dotti, Cristina Meinhardt, Odorico Machado Mendizabal · 2020
State Machine Replication (SMR) is a widely used approach for fault tolerance of important services. Support for SMR implementations on shared infrastructures has emerged, allowing wider adoption. However, there are still non-trivial aspects that developers have to handle to build and deploy their dependable services. In this paper, we tackle the need for recovery to keep fault-tolerance levels, and propose an approach to: (i) simplify the development of logging; (ii) improve resource sharing in shared infrastructures; (iii) alleviate costs with replication in pay-per-use infrastructures. The central idea is to decouple service execution from logging and offer logging functionality as a service attachable to SMR deployments. Beyond the added simplicity to deploy an SMR, we show that this approach does not penalize performance of replicated services, and that a logging service can scale to look to several applications.