TY - GEN

T1 - The Performance of Distributed Applications

T2 - 14th Annual ACM/SPEC International Conference on Performance Engineering, ICPE 2023

AU - Hasenoot, Jasper A.

AU - Rellermeyer, Jan S.

AU - Uta, Alexandru

N1 - Funding Information: The work in this article was in part supported by The Dutch National Science Foundation NWO Veni grant VI.202.195.

PY - 2023/4/15

Y1 - 2023/4/15

N2 - Widely used in datacenters and clouds, network traffic shaping is a performance influencing factor that is often overlooked when benchmarking or simply deploying distributed applications. While in theory traffic shaping should allow for a fairer sharing of network resources, in practice it also introduces new problems: performance (measurement) inconsistency and long tails. In this paper we investigate the effects of traffic shaping mechanisms on common distributed applications. We characterize the performance of a distributed key-value store, big data workloads, and high-performance computing under state-of-the-art benchmarks, while the underlying network's traffic is shaped using state-of-the-art mechanisms such as token-buckets or priority queues. Our results show that the impact of traffic shaping needs to be taken into account when benchmarking or deploying distributed applications. To help researchers, practitioners, and application developers we uncover several practical implications and make recommendations on how certain applications are to be deployed so that performance is least impacted by the shaping protocols.

AB - Widely used in datacenters and clouds, network traffic shaping is a performance influencing factor that is often overlooked when benchmarking or simply deploying distributed applications. While in theory traffic shaping should allow for a fairer sharing of network resources, in practice it also introduces new problems: performance (measurement) inconsistency and long tails. In this paper we investigate the effects of traffic shaping mechanisms on common distributed applications. We characterize the performance of a distributed key-value store, big data workloads, and high-performance computing under state-of-the-art benchmarks, while the underlying network's traffic is shaped using state-of-the-art mechanisms such as token-buckets or priority queues. Our results show that the impact of traffic shaping needs to be taken into account when benchmarking or deploying distributed applications. To help researchers, practitioners, and application developers we uncover several practical implications and make recommendations on how certain applications are to be deployed so that performance is least impacted by the shaping protocols.

KW - networked application performance

KW - traffic shaping

UR - http://www.scopus.com/inward/record.url?scp=85158152350&partnerID=8YFLogxK

U2 - 10.1145/3578244.3583733

DO - 10.1145/3578244.3583733

M3 - Conference contribution

AN - SCOPUS:85158152350

SP - 207

EP - 220

BT - ICPE 2023 - Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering

Y2 - 15 April 2023 through 19 April 2023

ER -