Controlling Garbage Collection and Request Admission to Improve Performance of FaaS Applications

Abstract

Runtime environments like Java's JRE, .NET's CLR, and Ruby's MRI, are popular choices for cloud-based applications and particularly in the Function as a Service (FaaS) serverless computing context. A critical component of runtime environments of these languages is the garbage collector (GC). The GC frees developers from manual memory management, which could potentially ease development and avoid bugs. The benefits of using the GC come with a negative impact on performance; that impact happens because either the GC needs to pause the runtime execution or competes with the running program for computational resources. In this work, we evaluated the usage of a technique - Garbage Collector Control Interceptor (GCI) - that eliminates the negative impact of GC on performance by controlling GC executions and transparently shedding requests while the collections are happening. We executed experiments simulating AWS Lambda's behavior and found that GCI is a viable solution. It benefited the user by improving the response time up to 10.86% at 99.9th percentile and reducing cost by 7.22%, but it also helped the platform provider by improving resource utilization by 14.52%.