Publication | Closed Access
µqSim: Enabling Accurate and Scalable Simulation for Interactive Microservices
11
Citations
26
References
2019
Year
Unknown Venue
Interactive MicroservicesNetwork FlowsEngineeringMicroservices DesignCloud ComputingCurrent Cloud ServicesComputer EngineeringSystems EngineeringSimulationSimulation InfrastructureDistributed SystemsModeling And SimulationNetwork SimulatorNetwork SimulationParallel ComputingDistributed SimulationQueueing SystemsTail Latency
Current cloud services are moving away from monolithic designs and towards graphs of many loosely-coupled, single-concerned microservices. Microservices have several advantages, including speeding up development and deployment, allowing specialization of the software infrastructure, and helping with debugging and error isolation. At the same time they introduce several hardware and software challenges. Given that most of the performance and efficiency implications of microservices happen at scales larger than what is available outside production deployments, studying such effects requires designing the right simulation infrastructures. We present j);qSim, a scalable and validated queueing network simulator designed specifically for interactive microser-vices. μqSim provides detailed intra- and inter-microservice models that allow it to faithfully reproduce the behavior of complex, many-tier applications. μqSim is also modular, allowing reuse of individual models across microservices and end-to-end applications. We have validated μqSim both against simple and more complex microservices graphs, and have shown that it accurately captures performance in terms of throughput and tail latency. Finally, we use μqSim to model the tail at scale effects of request fanout, and the performance impact of power management in latency -sensitive microservices.
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