Towards Serverless Optimization with In-place Scaling

Abstract

Serverless computing has gained popularity due to its cost efficiency, ease of deployment, and enhanced scalability. However, in serverless environments, servers are initiated only after receiving a request, leading to increased response times. This delay is commonly known as the cold start problem. In this study, we explore the in-place scaling feature released in Kubernetes v1.27 and examine its impact on serverless computing. Our experimental results reveal improvements in request latency, with reductions ranging from 1.16 to 18.15 times across various workloads when compared to traditional cold policy.