Abstrakt
Cloud platforms allow applications to meet fluctuating levels of demand through automatic horizontal scaling. These deployment models are characterized by short-lived applications running in resource-constrained environments.
This amplifies the overhead of dynamic languages with just-in-Time (JIT) compilation. Dynamic-language runtimes suffer from a warmup phase and resource-usage peaks caused by JIT compilation.
Offloading compilation jobs to a dedicated server is a possible mitigation for these problems. We propose leveraging remote JIT compilation as a means to enable coordination between the independent instances.
By sharing compilation results, aggregating profiles, and adapting the compiler and compilation policy, we strive to improve the peak performance and further reduce the warmup time of these applications. Additionally, an implementation on top of the Truffle framework enables us to bring these benefits to many popular languages.