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Function as a Service (FaaS) has been gaining popularity as a way to deploycomputations to serverless backends in the cloud. This paradigm shifts thecomplexity of allocating and provisioning resources to the cloud provider,which has to provide the illusion of always-available resources (i.e., fastfunction invocations without cold starts) at the lowest possible resource cost.Doing so requires the provider to deeply understand the characteristics of theFaaS workload. Unfortunately, there has been little to no public information onthese characteristics. Thus, in this paper, we first characterize the entireproduction FaaS workload of Azure Functions. We show for example that mostfunctions are invoked very infrequently, but there is an 8-order-of-magnituderange of invocation frequencies. Using observations from our characterization,we then propose a practical resource management policy that significantlyreduces the number of function coldstarts,while spending fewerresources thanstate-of-the-practice policies.

Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider