ppbench - A Visualizing Network Benchmark for Microservices
ppbench - A Visualizing Network Benchmark for Microservices
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ppbench - 微服务可视化网络基准
DOI：
10.5220/0005732202230231
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Peter
中科院分区：
文献类型：
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作者：
Nane Kratzke;Peter
：像Net Webix、Google、Amazon、Twitter这样的公司成功地为非常大的系统提供了艾德弹性和可扩展的微服务架构。微服务架构通常以将服务部署为容器集群上的容器的方式实现。容器化微服务通常使用轻量级和基于REST的机制。然而，这种轻量级通信通常由容器集群通过重量级软件定义网络（SDN）进行路由。服务通常是用不同的编程语言实现的，这给系统增加了额外的复杂性，最终可能会降低性能。令人惊讶的是，由于缺少专门的基准，在微服务设计过程的前期计算出这些影响是相当复杂的。这篇文章提出了一个专为这种微服务设置而设计的基准。我们提倡在微服务架构开发的前期而不是后期考虑基本设计决策及其性能影响更有用。我们提出了一些关于TIOBE TOP 50编程语言（Go，Java，Ruby，Dart），容器（Docker作为类型代表）和SDN解决方案（Weave作为类型代表）的性能影响的发现。
: 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 architecture 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).