An Open-Source Benchmark Suite for Microservices and Their Hardware-Software Implications for Cloud & Edge Systems

被引：378

作者：

Gan, Yu ^{[1
]}

Zhang, Yanqi ^{[1
]}

Cheng, Dailun ^{[1
]}

Shetty, Ankitha ^{[1
]}

Rathi, Priyal ^{[1
]}

Katarki, Nayan ^{[1
]}

Bruno, Ariana ^{[1
]}

Hu, Justin ^{[1
]}

Ritchken, Brian ^{[1
]}

Jackson, Brendon ^{[1
]}

Hu, Kelvin ^{[1
]}

Pancholi, Meghna ^{[1
]}

He, Yuan ^{[1
]}

Clancy, Brett ^{[1
]}

Colen, Chris ^{[1
]}

Wen, Fukang ^{[1
]}

Leung, Catherine ^{[1
]}

Wang, Siyuan ^{[1
]}

Zaruvinsky, Leon ^{[1
]}

Espinosa, Mateo ^{[1
]}

Lin, Rick ^{[1
]}

Liu, Zhongling ^{[1
]}

Padilla, Jake ^{[1
]}

Delimitrou, Christina ^{[1
]}

机构：

[1] Cornell Univ, Ithaca, NY 14853 USA

来源：

TWENTY-FOURTH INTERNATIONAL CONFERENCE ON ARCHITECTURAL SUPPORT FOR PROGRAMMING LANGUAGES AND OPERATING SYSTEMS (ASPLOS XXIV) | 2019年

关键词：

cloud computing; datacenters; microservices; cluster management; serverless; acceleration; fpga; QoS; SCALE;

D O I：

10.1145/3297858.3304013

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Cloud services have recently started undergoing a major shift from monolithic applications, to graphs of hundreds of loosely-coupled microservices. Microservices fundamentally change a lot of assumptions current cloud systems are designed with, and present both opportunities and challenges when optimizing for quality of service (QoS) and utilization. In this paper we explore the implications microservices have across the cloud system stack. We first present DeathStarBench, a novel, open-source benchmark suite built with microservices that is representative of large end-to-end services, modular and extensible. DeathStarBench includes a social network, a media service, an e-commerce site, a banking system, and IoT applications for coordination control of UAV swarms. We then use DeathStarBench to study the architectural characteristics of microservices, their implications in networking and operating systems, their challenges with respect to cluster management, and their trade-offs in terms of application design and programming frameworks. Finally, we explore the tail at scale effects of microservices in real deployments with hundreds of users, and highlight the increased pressure they put on performance predictability.

引用

页码：3 / 18

页数：16

共 67 条

[1]

[Anonymous], 2007, TECHNICAL REPORT

[2]

[Anonymous], 2014, P 41 INT S COMP ARCH

[3]

[Anonymous], 2011, S NETW SYST DES IMPL

[4]

[Anonymous], 2005, DATA MINING PRACTICA

[5]

[Anonymous], 2014, P 41 ANN INT S COMP

[6]

[Anonymous], 2010, Technical report

[7]

[Anonymous], 2004, Linux J.

[8]

Barroso Luiz, 2009, The Datacenter as a Computer: An Introduction to the Design of WarehouseScale Machines

[9] Large-Scale Machine Learning with Stochastic Gradient Descent [J].

Bottou, Leon .

COMPSTAT'2010: 19TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STATISTICS, 2010, :177-186

[10]

Caulfield AM, 2016, INT SYMP MICROARCH

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