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.

We propose CloudJIT, a self-optimizing FaaS platform that takes advantage of Ahead-of-Time compilation to achieve reduced startup latency and instantaneous peak performance with a smaller memory footprint. While AOT compilation is an expensive operation, the platform automatically detects which functions will benefit from it the most, performs all prerequisite preparation procedures, and compiles selected functions into native binaries. Our preliminary analysis, based on a public FaaS invocations trace, shows that optimizing a small fraction of all functions positively affects a vast majority of all cold starts.