Completion Time Prediction of Open Source FaaS Functions

Function as a Service (FaaS) is the latest stage of application virtualization in the cloud. It enables to deploy small code pieces – functions – in the cloud. FaaS focuses on event-driven functions in response to triggers from different sources. The functions run in ephemeral virtual environments. This means that the user is charged on the basis of the time the function is busy serving the invocation requests. With the advent of Industry 4.0 the need has arisen to run applications on Edge Computing nodes. FaaS is a promising solution for serving industrial applications that require predictable latency while meeting the demands of edge computing, which operates on a limited resource base. Therefore, knowing the completion time of the invocation requests is of key importance. In this paper, we introduce a function runtime design for opensource FaaS implementations that achieves a lower deviation in request completion times compared to default runtimes by regulating the function’s access to host CPU cores. We present the implementation details of our proposed function runtime design for Python, Go and Node.js. We also introduce a simulation framework that is able to estimate the completion time distribution of the incoming invocation requests. We validate the results of our simulation framework using real measurement data.