FaaSLoad
Repository on GitLabFaaSLoad is a tool to gather fine-grained data about performance and resource usage of the programs that run on Function-as-a-Service cloud platforms. It considers individual instances of functions to collect hardware and operating-system performance information, by monitoring them while injecting a workload.
FaaSLoad helps building a dataset of function executions to train machine learning models, studying at fine grain the behavior of function runtimes, and replaying real workload traces for in situ observations.
Cite as (get BibTeX record on dblp):
Mathieu Bacou. FaaSLoad: Fine-Grained Performance and Resource Measurement for Function-As-a-Service. In 28th International Conference on Principles of Distributed Systems (OPODIS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 324, pp. 22:1-22:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.OPODIS.2024.22
OFC's FaaSCache
FaaSCache (part of the Opportunistic FaaS Cache, a.k.a. OFC) is a transparent, vertically and horizontally elastic in-memory caching system for Function-as-a-Service platforms. The cache is distributed over worker nodes to mitigate the overheads of frequent interactions with an external data store, as required by the stateless FaaS paradigm.
FaaSCache is based on enhancements to the Apache OpenWhisk Function-as-a-Service platform, the OpenStack Swift persistent object storage service, and the RAMCloud in-memory store.
Cite as (get BibTeX record on dblp):
Djob Mvondo, Mathieu Bacou, Kevin Nguetchouang, Lucien Ngale, Stéphane Pouget, Josiane Kouam, Renaud Lachaize, Jinho Hwang, Tim Wood, Daniel Hagimont, Noël De Palma, Bernabé Batchakui, and Alain Tchana. 2021. OFC: an opportunistic caching system for FaaS platforms. In Proceedings of the Sixteenth European Conference on Computer Systems (EuroSys '21). Association for Computing Machinery, New York, NY, USA, 228–244. https://doi.org/10.1145/3447786.3456239
Last modify 2025-01-16