The Ifs and Buts of Less is More: A Serverless Computing Reality Check

Serverless computing defines a pay-as-you-go cloud execution model, where the unit of computation is a function that a cloud provider executes and auto-scales on behalf of a cloud consumer. Serverless suggests not (or less) caring about servers but focusing (more) on business logic expressed in functions. Server'less' may be `more' when getting developer expectations and platform propositions right and when engineering solutions that take specific behavior and constraints of (current) Function-as-a-Service platforms into account. To this end, in this invited paper, we present a summary of findings and lessons learned from a series of research experiments conducted over the past two years. We argue that careful attention must be placed on the promises associated with the serverless model, provide a reality-check for five common assumptions, and suggest ways to mitigate unwanted effects. Our findings focus on application workload distribution and computational processing complexity, the specific auto-scaling mechanisms in place, the behavior and strategies implemented with operational tasks, the constraints and limitations existing when composing functions, and the costs of executing functions.