Joint$\lambda$: Orchestrating Serverless Workflows on Jointcloud FaaS Systems

TL;DR

Jointλ is a distributed system that orchestrates cross-cloud serverless workflows without centralized control, reducing overhead, costs, and improving fault tolerance on multi-FaaS platforms.

Contribution

It introduces a novel distributed runtime with function-side orchestration and failover mechanisms for efficient, reliable cross-cloud serverless workflow management.

Findings

Reduces workflow makespan by up to 3.3× compared to commercial services.

Saves up to 65% in execution costs.

Achieves up to 4.0× faster performance than state-of-the-art orchestrators.

Abstract

Existing serverless workflow orchestration systems are predominantly designed for a single-cloud FaaS system, leading to vendor lock-in. This restricts performance optimization, cost reduction, and availability of applications. However, orchestrating serverless workflows on Jointcloud FaaS systems faces two main challenges: (1) additional overhead caused by centralized cross-cloud orchestration; and (2) a lack of reliable failover and fault-tolerant mechanisms for cross-cloud serverless workflows. To address these challenges, we propose Joint$\lambda$, a distributed runtime system designed to orchestrate serverless workflows on multiple FaaS systems without relying on a centralized orchestrator. Joint$\lambda$ introduces a compatibility layer, Backend-Shim, leveraging inter-cloud heterogeneity to optimize makespan and reduce costs with on-demand billing. By using function-side orchestration instead of centralized nodes, it enables independent function invocations and data transfers, reducing cross-cloud communication overhead. For high availability, it ensures exactly-once execution via datastores and failover mechanisms for serverless workflows on Jointcloud FaaS systems. We validate Joint$\lambda$ on two heterogeneous FaaS systems, AWS and Aliyun, with four workflows. Compared to the most advanced commercial orchestration services for single-cloud serverless workflows, Joint$\lambda$ reduces makespan by up to 3.3$\times$ while saving up to 65% in cost. Joint$\lambda$ is also up to 4.0$\times$ faster than state-of-the-art orchestrators for cross-cloud serverless workflows, while achieving competitive cost in representative scenarios and providing strong execution guarantees.