BeeHive: Sub-second Elasticity for Web Services with Semi-FaaS Execution

Zhao, Ziming; Wu, Mingyu; Tang, Jiawei; Zang, Binyu; Wang, Zhaoguo; Chen, Haibo

doi:10.1145/3575693.3575752

Cited by 4 publications

(1 citation statement)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yussupov et al 38 suggested serverless parachutes, of which the idea is to extract crucial components from annotated source code and prepare them as standby serverless functions for exceptional workloads. Zhao et al 39 introduced BeeHive, a semi‐FaaS execution model that relies on the runtime environment to extract code snippets from a Java application and offload them to the target FaaS platform. BeeHive intrinsically follows the development principles advocated later by Ghemawat 40…”

Section: Related Workmentioning

confidence: 99%

RADF: Architecture decomposition for function as a service

Zhu,

Tamburri,

Casale

2023

Softw Pract Exp

View full text Add to dashboard Cite

As the most successful realization of serverless, function as a service (FaaS) brings in a novel cloud computing paradigm that can save operating costs, reduce management effort, enable seamless scalability, and augment development productivity. Migration of an existing application to the serverless architecture is, however, an intricate task as a great number of decisions need to be made along the way. We propose in this paper RADF, a semi‐automatic approach that decomposes a monolith into serverless functions by analyzing the business logic inherent in the interface of the application. The proposed approach adopts a two‐stage refactoring strategy, where a coarse‐grained decomposition is performed at first, followed by a fine‐grained one. As such, the decomposition process is simplified into smaller steps and adaptable to generate a solution at either microservice or function level. We have implemented RADF in a holistic DevOps methodology and evaluated its capability for microservice identification and feasibility for code refactoring. In the evaluation experiments, RADF achieves lower coupling and relatively balanced cohesion, compared to previous decomposition approaches.

show abstract

Section: Related Workmentioning

confidence: 99%