Serverless is an attractive computing model that offers seamless scalability and elasticity; it takes the infrastructure management burden away from users and enables a pay-as-you-use billing model. As a result, serverless is becoming increasingly popular for highly elastic and bursty workloads. However, existing platforms are supported by bloated virtualization stacks, which, combined with bursty and irregular invocations, lead to high memory and latency overheads.

Function-as-a-Service has emerged as a trending paradigm that provides attractive solutions to execute fine-grained and short-lived workloads referred to as functions. Functions are typically developed in a managed language such as Java and execute atop a language runtime. However, traditional language runtimes such as the HotSpot JVM are designed for peak performance as considerable time is spent profiling and Just-in-Time compiling code. As a consequence, warmup time and memory footprint are impacted. We observe that FaaS workloads, which are short-lived, do not fit this profile.

Function-as-a-Service provides attractive solutions to execute fine-grained and short-lived functions. Functions are typically developed in a managed language and execute atop a language runtime. However, traditional runtimes are designed for peak performance as considerable time is spent profiling and Just-in-Time compiling code. We observe that short-lived FaaS workloads do not fit this profile.