Zenix: Efficient Execution of Bulky Serverless Applications
Zhiyuan Guo, Zachary Blanco, Junda Chen, Jinmou Li, Zerui Wei, Bili, Dong, Ishaan Pota, Mohammad Shahrad, Harry Xu, Yiying Zhang

TL;DR
Zenix introduces a resource-centric serverless model that significantly reduces resource usage and enhances performance for bulky applications compared to traditional function-centric approaches.
Contribution
The paper proposes a novel resource-centric serverless computing model and implements Zenix, demonstrating substantial resource savings and performance improvements for large applications.
Findings
Zenix reduces resource consumption by up to 90%.
Zenix improves application performance by up to 64%.
The resource-centric model outperforms traditional function-centric systems.
Abstract
Serverless computing, commonly offered as Function-as-a-Service, was initially designed for small, lean applications. However, there has been an increasing desire to run larger, more complex applications (what we call bulky applications) in a serverless manner. Existing strategies for enabling such applications are to either increase function sizes or to rewrite applications as DAGs of functions. These approaches cause significant resource wastage, manual efforts, and/or performance overhead. We argue that the root cause of these issues is today's function-centric serverless model, where a function is the resource allocation and scaling unit. We propose a new, resource-centric serverless-computing model for executing bulky applications in a resource- and performance-efficient way, and we build the Zenix serverless platform following this model. Our results show that Zenix reduces…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCloud Computing and Resource Management · IoT and Edge/Fog Computing · Caching and Content Delivery
