CrossFit: Fine-grained Benchmarking of Serverless Application Performance across Cloud Providers
Paper in proceeding, 2022

Serverless computing emerged as a promising cloud computing paradigm for deploying cloud-native applications but raises new performance challenges. Existing performance evaluation studies focus on micro-benchmarking to measure an individual aspect of serverless functions, such as CPU speed, but lack an in-depth analysis of differences in application performance across cloud providers. This paper presents CrossFit, an approach for detailed and fair cross-provider performance benchmarking of serverless applications based on a providerindependent tracing model. Our case study demonstrates how detailed distributed tracing enables drill-down analysis to explain performance differences between two leading cloud providers, AWS and Azure. The results for an asynchronous application show that trigger time contributes most delay to the end-to-end latency and explains the main performance difference between cloud providers. Our results further reveal how increasing and bursty workloads affect performance stability, median latency, and tail latency.

observability

benchmarking

distributed tracing

performance

FaaS

serverless

Author

Joel Scheuner

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

Rui Deng

Student at Chalmers

Jan-Philipp Steghöfer

University of Gothenburg

Philipp Leitner

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

Proceedings - 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing, UCC 2022

51-60
9781665460873 (ISBN)

15th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2022
Vancouver, USA,

Subject Categories

Computer Engineering

Communication Systems

Computer Systems

DOI

10.1109/UCC56403.2022.00016

More information

Latest update

10/25/2023