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Serverless computing increases developer productivity by removing operationalconcerns such as managing hardware or software runtimes. Developers, however,still need to partition their application into functions, which can beerror-prone and adds complexity: Using a small function size where only thesmallest logical unit of an application is inside a function maximizesflexibility and reusability. Yet, having small functions leads to invocationoverheads, additional cold starts, and may increase cost due to busy waiting.In this paper we present Fusionize, a framework that removes these concernsfrom developers by automatically fusing the application code into amulti-function orchestration with varying function size. Developers only needto write the application code following a lightweight programming model and donot need to worry how the application is turned into functions. Our frameworkautomatically fuses different parts of the application into functions andmanages their interactions. Leveraging monitoring data, the framework optimizesthe distribution of application parts to functions to optimize deployment goalssuch as end-to-end latency and cost. Using two example applications, we showthat Fusionize can automatically and iteratively improve the deploymentartifacts of the application.

Fusionize: Improving Serverless Application Performance through Feedback-Driven Function Fusion