Estimating the capacities of function-as-a-service functions

Anshul Jindal, Mohak Chadha, Shajulin Benedict, Michael Gerndt

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

Serverless computing is a cloud computing paradigm that allows developers to focus exclusively on business logic as cloud service providers manage resource management tasks. Serverless applications follow this model, where the application is decomposed into a set of fine-grained Function-as-a-Service (FaaS) functions. However, the obscurities of the underlying system infrastructure and dependencies between FaaS functions within the application pose a challenge for estimating the performance of FaaS functions. To characterize the performance of a FaaS function that is relevant for the user, we define Function Capacity (FC) as the maximal number of concurrent invocations the function can serve in a time without violating the Service-Level Objective (SLO). The paper addresses the challenge of quantifying the FC individually for each FaaS function within a serverless application. This challenge is addressed by sandboxing a FaaS function and building its performance model. To this end, we develop FnCapacitor - an end-to-end automated Function Capacity estimation tool. We demonstrate the functioning of our tool on Google Cloud Functions (GCF) and AWS Lambda. FnCapacitor estimates the FCs on different deployment configurations (allocated memory & maximum function instances) by conducting time-framed load tests and building various models using statistical: linear, ridge, and polynomial regression, and Deep Neural Network (DNN) methods on the acquired performance data. Our evaluation of different FaaS functions shows relatively accurate predictions with an accuracy greater than 75% using DNN for both cloud providers.

Original languageEnglish
Title of host publicationCompanion Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2021
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450391634
DOIs
StatePublished - 6 Dec 2021
Event14th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2021 - Leicester, United Kingdom
Duration: 6 Dec 20219 Dec 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference14th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2021
Country/TerritoryUnited Kingdom
CityLeicester
Period6/12/219/12/21

Keywords

  • function capacity
  • function-as-a-service
  • serverless computing

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