Efficient Performance Guarantees for Function-as-a-Service with Cloud Allocators.

Conventional Function-as-a-Service (FaaS) systems provide limited support for the applications to configure FaaS deployments for performance needs, limiting the FaaS applicability and productivity. Recent work addresses these limitations by introducing a performance abstraction, which allows applications to specify their performance needs through predefined Software-level Agreements (SLAs). FaaS systems then use these SLAs to manage resources and scheduling, guaranteeing application performance. In this paper, we propose efficient methods for realizing a performance abstraction in FaaS systems. Our approach enables resource sharing across deployments and uses cloud resource allocation statistics to determine the optimal timing and quantity of resource provisioning. This allows us to meet SLAs cost-effectively while maintaining robustness across diverse applications and deployment environments. Our experiments demonstrate a 500x higher guarantee availability compared to current cloud standards, with 10x fewer resource costs. More extensive studies show that this efficiency is consistent across deployment scenarios, supporting up to 1,000 concurrent FaaS deployments with 99.95% availability and using less than 40% additional resources.