CloudIntelligence 2021
Sat 29 May 2021
co-located with ICSE 2021
Sat 29 May 2021 16:42 - 16:55 at CloudIntelligence Room - Project Showcase Session Chair(s): Yingnong Dang

In cloud computing, provisioning virtual machines (VMs) fast and reliably is a fundamental yet challenging problem, particularly in cloud environments of changing workloads and shifting demand patterns. A trivial solution of instantiating a VM from scratch per customer request may not satisfy business SLA’s and would degrade customer experience. Hence, provisioning VMs in advance motivated with machine learning (ML) infused into the cloud computing system to predict upcoming VM request demands is an advisable solution. In this paper, we first describe a number of system integration challenges including 1) how to achieve low latency provisioning to quickly adjust to customer demand pattern shifts, 2) how to efficiently scale to serve a large number of VM configurations supported in the cloud environment, and 3) how to reliably consume recommended prediction results for VM provision despite of anticipated operation failures and timeout. We then present the high level solution design with discussions of our developed system to address the aforementioned challenges. Our system has been deployed successfully in Microsoft Azure exhibiting significant improvements for VM provisioning experience with regards to latency and reliability requirements.

Sat 29 May
Times are displayed in time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

16:30 - 17:20
Project Showcase SessionCloudIntelligence 2021 at CloudIntelligence Room
Chair(s): Yingnong DangMicrosoft, USA
16:30
12m
Demonstration
Building a Secured Data Intelligence Platform
CloudIntelligence 2021
Conan  YangSalesforce
16:42
12m
Demonstration
Infusing ML into VM Provisioning in Cloud
CloudIntelligence 2021
Chuan LuoMicrosoft Research, China, Randolph YaoMicrosoft, USA, Bo QiaoMicrosoft Research, Beijing, China, Qingwei LinMicrosoft Research, Beijing, China, Tri M. TranMicrosoft Azure, Gil  Shafriri Microsoft Azure, Yingnong DangMicrosoft, USA, Raphael  Ghelman Microsoft Azure, Pulak  Goyal Microsoft Azure, Eli CortezMicrosoft Azure, Daud  Howlader Microsoft Azure, Sushant  Rewaskar Microsoft Azure, Murali ChintalapatiMicrosoft Azure, Dongmei ZhangMicrosoft Research
16:55
12m
Demonstration
F3: Fault Forecasting Framework for Cloud Systems
CloudIntelligence 2021
Chuan LuoMicrosoft Research, China, Pu ZhaoMicrosoft Research, Beijing, China, Bo QiaoMicrosoft Research, Beijing, China, Youjiang WuMicrosoft, USA, Yingnong DangMicrosoft, USA, Murali ChintalapatiMicrosoft Azure, Susy  YiMicrosoft 365, Paul WangMicrosoft 365, Andrew  ZhouMicrosoft 365, Saravanakumar RajmohanMicrosoft Office, United States, Qingwei LinMicrosoft Research, Beijing, China, Dongmei ZhangMicrosoft Research
17:07
12m
Demonstration
SEAT: statistically sound infra-side deployment and integration testing
CloudIntelligence 2021
Nutcha  TemiyasathitFacebook, Tao YangFacebook, Karan LuthraFacebook, Nick RuffFacebook, Petar ZuljevicFacebook, Ethan BenowitzFacebook, Boris BaracaldoFacebook, Oytun EskiyenenturkFacebook, Xin FuFacebook

Information for Participants
Info for CloudIntelligence Room: