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Wed 11 Nov 2020 01:09 - 01:10 at Virtual room 2 - Cloud / Services 1

Mono2Micro is an AI-based toolchain that provides recommendations for decomposing legacy web applications into microservice partitions. Mono2Micro consists of a set of tools that collect static and runtime information from a monolithic application and process the information using an AI-based technique to generate recommendations for partitioning the application classes. Each partition represents a candidate microservice or a grouping of classes with similar business functionalities. Mono2Micro takes a temporo-spatial clustering approach to compute meaningful and explainable partitions. It generates two types of partition recommendations. First, it computes business-logic-seams-based partitions that represent a desired encapsulation of business functionalities. However, such a recommendation may cut across data dependencies between classes, accommodating which could require significant application updates. To address this, Mono2Micro computes natural-seams-based partitions, which respect data dependencies. We describe the set of tools that comprise Mono2Micro and illustrate them using a well-known open-source JEE application.

Wed 11 Nov

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01:00 - 01:30
01:00
2m
Talk
Beware the Evolving ‘Intelligent’ Web Service! An Integration Architecture Tactic to Guard AI-First Components
Research Papers
Alex Cummaudo Deakin University, Australia, Scott Barnett Deakin University, Australia, Rajesh Vasa Deakin University, Australia, John Grundy Monash University, Australia, Mohamed Abdelrazek Deakin University, Australia
DOI
01:03
1m
Talk
Efficient Customer Incident Triage via Linking with System Incidents
Industry Papers
Jiazhen Gu Fudan University, China, Jiaqi Wen Peking University, China, Zijian Wang Fudan University, China, Pu Zhao Microsoft Research, China, Chuan Luo Microsoft Research, China, Yu Kang Microsoft Research, China, Yangfan Zhou Fudan University, China, Li Yang Microsoft Azure, USA, Jeffrey Sun Microsoft Azure, USA, Zhangwei Xu Microsoft, China, Bo Qiao Microsoft Research, China, Liqun Li Microsoft Research, China, Qingwei Lin Microsoft Research, China, Dongmei Zhang Microsoft Research, China
DOI
01:05
1m
Talk
How to Mitigate the Incident? An Effective Troubleshooting Guide Recommendation Technique for Online Service Systems
Industry Papers
Jiajun Jiang Tianjin University, China, Weihai Lu Peking University, China, Junjie Chen Tianjin University, China, Qingwei Lin Microsoft Research, China, Pu Zhao Microsoft Research, China, Yu Kang Microsoft Research, China, Hongyu Zhang University of Newcastle, Australia, Yingfei Xiong Peking University, Feng Gao Microsoft, China, Zhangwei Xu Microsoft, China, Yingnong Dang Microsoft, USA, Dongmei Zhang Microsoft Research, China
DOI
01:07
1m
Talk
Identifying Linked Incidents in Large-Scale Online Service Systems
Research Papers
Yujun Chen Microsoft Research, China, Xian Yang Hong Kong Baptist University, China, Hang Dong Microsoft Research, China, Xiaoting He Chinese Academy of Sciences, China, Hongyu Zhang University of Newcastle, Australia, Qingwei Lin Microsoft Research, China, Junjie Chen Tianjin University, China, Pu Zhao Microsoft Research, China, Yu Kang Microsoft Research, China, Feng Gao Microsoft, China, Zhangwei Xu Microsoft, China, Dongmei Zhang Microsoft Research, China
DOI
01:09
1m
Talk
Mono2Micro: An AI-Based Toolchain for Evolving Monolithic Enterprise Applications to a Microservice Architecture
Tool Demos
Anup K. Kalia IBM Research, USA, Jin Xiao IBM Research, USA, Chen Lin IBM Research, USA, Saurabh Sinha IBM Research, John Rofrano IBM Research, USA, Maja Vukovic IBM Research, USA, Debasish Banerjee IBM, n.n.
DOI
01:11
1m
Talk
Threshy: Supporting Safe Usage of Intelligent Web Services
Tool Demos
Alex Cummaudo Deakin University, Australia, Scott Barnett Deakin University, Australia, Rajesh Vasa Deakin University, Australia, John Grundy Monash University, Australia
DOI
01:13
1m
Talk
Towards Intelligent Incident Management: Why We Need It and How We Make It
Industry Papers
Zhuangbin Chen Chinese University of Hong Kong, China, Yu Kang Microsoft Research, China, Liqun Li Microsoft Research, China, Xu Zhang Microsoft Research, China, Hongyu Zhang University of Newcastle, Australia, Hui Xu Fudan University, China, Yangfan Zhou Fudan University, China, Li Yang Microsoft Azure, USA, Jeffrey Sun Microsoft Azure, USA, Zhangwei Xu Microsoft, China, Yingnong Dang Microsoft, USA, Feng Gao Microsoft, China, Pu Zhao Microsoft Research, China, Bo Qiao Microsoft Research, China, Qingwei Lin Microsoft Research, China, Dongmei Zhang Microsoft Research, China, Michael Lyu CUHK
DOI Media Attached File Attached
01:15
15m
Talk
Conversations on Cloud / Services 1
Paper Presentations
Alex Cummaudo Deakin University, Australia, Anup K. Kalia IBM Research, USA, Jiajun Jiang Tianjin University, China, Zhuangbin Chen Chinese University of Hong Kong, China, M: Satish Chandra Facebook, USA