FaaSKeeper: Learning from Building Serverless Services with ZooKeeper as an Example

TL;DR

FaaSKeeper introduces a serverless version of ZooKeeper, enabling scalable, cost-effective coordination services in cloud environments while maintaining strong consistency guarantees.

Contribution

It presents the first serverless implementation of ZooKeeper, demonstrating how to adapt coordination services to serverless architectures with significant cost reductions.

Findings

Maintains ZooKeeper's consistency guarantees

Reduces costs by up to 719x on infrequent workloads

Explores limitations and improvements for serverless coordination services

Abstract

FaaS (Function-as-a-Service) revolutionized cloud computing by replacing persistent virtual machines with dynamically allocated resources. This shift trades locality and statefulness for a pay-as-you-go model more suited to variable and infrequent workloads. However, the main challenge is to adapt services to the serverless paradigm while meeting functional, performance, and consistency requirements. In this work, we push the boundaries of FaaS computing by designing a serverless variant of ZooKeeper, a centralized coordination service with a safe and wait-free consensus mechanism. We define synchronization primitives to extend the capabilities of scalable cloud storage and outline a set of requirements for efficient computing with serverless. In FaaSKeeper, the first coordination service built on serverless functions and cloud-native services, we explore the limitations of serverless offerings and propose improvements essential for complex and latency-sensitive applications. We share serverless design lessons based on our experiences of implementing a ZooKeeper model deployable to clouds today. FaaSKeeper maintains the same consistency guarantees and interface as ZooKeeper, with a serverless price model that lowers costs up to 110-719x on infrequent workloads.