Cost-Effective, Workload-Adaptive Migration of Big Data Applications to the Cloud

被引:0
|
作者
Giannakouris, Victor [1 ]
Fernandez, Alejandro [1 ]
Simitsis, Alkis [1 ]
Babu, Shivnath [1 ]
机构
[1] Unravel Data Syst, Bengaluru, Karnataka, India
关键词
Cloud migration; Big data stack; Application performance management;
D O I
10.1145/3299869.3320240
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
More than 10,000 enterprises worldwide use the big data stack composed of multiple distributed systems. At Unravel, we build the next-generation APM platform for the big data stack, and we have worked with a representative sample of these enterprises that covers most industry verticals. This sample covers the spectrum of choices for deploying the big data stack across on-premises datacenters, private and public cloud deployments, and hybrid combinations of these. In this paper, we present a solution for assisting enterprises planning the migration of their big data stacks from on-premises deployments to the cloud. Our solution is goal driven and adapts to various migration scenarios. We present the system architecture we built and several cloud mapping options. We also describe a demonstration script that involves practical, real-world use-cases of the path to cloud adoption.
引用
收藏
页码:1909 / 1912
页数:4
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