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Authors: Nane Kratzke and Peter-Christian Quint

Affiliation: Lübeck University of Applied Sciences, Germany

ISBN: 978-989-758-182-3

Keyword(s): Microservice, Container, Docker, Cluster, Network, Performance, Reference, Benchmark, REST, SDN.

Related Ontology Subjects/Areas/Topics: Cloud Applications Performance and Monitoring ; Cloud Computing ; Cloud Computing Enabling Technology ; Collaboration and e-Services ; Data Engineering ; Development Methods for Cloud Applications ; e-Business ; Enterprise Information Systems ; Mobile Software and Services ; Ontologies and the Semantic Web ; Performance Development and Management ; Platforms and Applications ; Services Science ; Software Agents and Internet Computing ; Software Engineering ; Software Engineering Methods and Techniques ; Telecommunications ; Web Services ; Wireless Information Networks and Systems

Abstract: Companies like Netflix, Google, Amazon, Twitter successfully exemplified elastic and scalable microservice architectures for very large systems. Microservice architectures are often realized in a way to deploy services as containers on container clusters. Containerized microservices often use lightweight and REST-based mechanisms. However, this lightweight communication is often routed by container clusters through heavyweight software defined networks (SDN). Services are often implemented in different programming languages adding additional complexity to a system, which might end in decreased performance. Astonishingly it is quite complex to figure out these impacts in the upfront of a microservice design process due to missing and specialized benchmarks. This contribution proposes a benchmark intentionally designed for this microservice setting. We advocate that it is more useful to reflect fundamental design decisions and their performance impacts in the upfront of a microservice a rchitecture development and not in the aftermath. We present some findings regarding performance impacts of some TIOBE TOP 50 programming languages (Go, Java, Ruby, Dart), containers (Docker as type representative) and SDN solutions (Weave as type representative). (More)

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Paper citation in several formats:
Kratzke, N. and Quint, P. (2016). ppbench - A Visualizing Network Benchmark for Microservices.In Proceedings of the 6th International Conference on Cloud Computing and Services Science - Volume 2: CLOSER, ISBN 978-989-758-182-3, pages 223-231. DOI: 10.5220/0005732202230231

@conference{closer16,
author={Nane Kratzke. and Peter{-}Christian Quint.},
title={ppbench - A Visualizing Network Benchmark for Microservices},
booktitle={Proceedings of the 6th International Conference on Cloud Computing and Services Science - Volume 2: CLOSER,},
year={2016},
pages={223-231},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005732202230231},
isbn={978-989-758-182-3},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Cloud Computing and Services Science - Volume 2: CLOSER,
TI - ppbench - A Visualizing Network Benchmark for Microservices
SN - 978-989-758-182-3
AU - Kratzke, N.
AU - Quint, P.
PY - 2016
SP - 223
EP - 231
DO - 10.5220/0005732202230231

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