A FaaS Instance Management Algorithm for Minimizing Cost subject to Response Time

Abstract: With the development of cloud computing technologies, the concept of Function as a Service (FaaS) has become increasingly popular over the years. Developers can choose to create applications in the form of functions, and delegate the deployment and management of the infrastructure to the FaaS provider. Before a function can be executed at the infrastructure of the FaaS service provider, an environment to execute a function needs to be initiated; this environment initialization is known as cold start. Loading and maintaining a function is costly for FaaS providers, especially the cold start process which costs more system resources like Central Processing Unit (CPU) and memory than keeping functions alive. Therefore it is essential to prevent a cold start whenever possible because this would lead to an increase in both the response time and the cost. An instance management policy need to be implemented to reduce the probability of cold starts while minimizing costs. This project’s objective is to develop an instance management algorithm to minimize total costs while meeting response time requirements. By investigating three widely used instance management algorithms we found that none of them utilize the dependency existing between functions. We believe these dependencies can be useful to reduce response time and cold start probability by predicting next invocations. By leveraging this observation, we proposed a novel Dependency Based Algorithm (DBA). By using extensive simulations we showed that proposed algorithm can solve the problem and provide low response time with low costs compare to baselines.