The MLSys'22 Workshop on Cloud Intelligence / AIOps

MLSys'22

 Workshop on Cloud Intelligence / AIOps

In conjunction with the 5th Conference on Machine Learning and Systems

September 1st, 2022 

Santa Clara Convention Center

Due to the surge in the Omicron Variant and based on feedback from the MLSys Program Committee, the MLSys Board and 2022 Chairs have collectively decided to postpone the conference to Aug. 29th through Sept.1st, 2022. As result, the Cloud Intelligence Workshop will be hosted on Sept.1st, 2022 at Santa Clara Convention Center.

Call for Papers

Important Dates

• Submissions due: April 18th, 2022

• Notification of acceptance: May 6th, 2022

• Camera-ready Deadline: July 6th, 2022

All deadlines are at 11:59pm Pacific Time.

Overview

Digital transformation is happening in all industries. However, the large-scale and high complexity of cloud services, the core of the transformation, bring great challenges to the industry. We envision that with the advance of Artificial intelligence (AI) and machine learning (ML) and other related technologies, the cloud industry will achieve significant progress in the following aspects while keeping a sustained and exponential growth:

• Highly resilient cloud service. Cloud services will have built-in capabilities of self-monitoring, self-diagnosis, and self-healing without compromising the service quality or the user experience.

• Intelligence at users’ fingertips. Users can easily use, maintain, and troubleshoot their workloads or get efficient support on top of the underlying cloud service offerings.

• Highly efficient and effective DevOps (developer & operators) powered by intelligent tools.

The industry is calling for AIOps solutions but is still at an early stage towards realizing this vision. We advocate the urgency of driving and accelerating AI/ML for efficient and manageable cloud services through collaborative efforts in multiple areas including but not limited to software engineering, systems, artificial intelligence, machine learning, and data analytics.

This workshop provides a forum for researchers and practitioners to present the state of research and practice in AI/ML for efficient and manageable cloud services, and network with colleagues.

Cloud Intelligence / AIOps: Infusing AI/ML into all aspects of the design, development, and operations of cloud service systems

Topics

The workshop targets creating an interdisciplinary forum for researchers and practitioners from the fields mentioned above. It encourages submissions on innovative technologies and applications that leverage AI/ML for efficient and manageable cloud services. Topics of interest include:

• New design, development, and operational pattern

• Service quality monitoring and anomaly detection

• Deployment and integration testing

• System configuration

• Service quality monitoring and anomaly detection

• Resource scheduling and optimization

• Capacity/workload management and prediction

• Hardware/software failure prediction

• Auto-diagnosis and problem localization

• Incident management

• Security & Privacy

Attendance Expectation

If a submission is accepted, at least one author of the paper is required to register for the workshop and present the paper.

Abstract and Papers Submission

The workshop invites submission of manuscripts with original research results that have not been previously published and that are not currently under review by another conference and journal. Submissions will be assessed based on their novelty, technical quality, potential impact, interest, clarity, relevance, and reproducibility. Submitted papers will be peer-reviewed and selected for oral presentation. Accepted papers will be listed on the workshop’s website.

Submissions must be in PDF format, no more than six pages long for technical papers and two pages for project showcases, including all content and references. Submissions must conform to the IEEE Conference Proceedings Formatting Guidelines.

The project showcase track focuses on innovative cloud intelligence projects. Submissions should contain a brief description of the project including its goal, problem statement, solution, and deployment status if applicable. A project URL is recommended.

Submission site:

https://cmt3.research.microsoft.com/CIWS2022/

Contact: 

cloudintelligenceworkshop@gmail.com 

Organizers

Steering Committee

Rama Akkiraju IBM

Ricardo Bianchini Microsoft Research Redmond

Mike Dahlin Google

Marcus Fontoura Microsoft Azure

Ahmed E. Hassan Queen’s University

Michael R. Lyu Chinese University of Hongkong

Erik Meijer Facebook

Tao Xie Peking University

Dongmei Zhang Microsoft Research Asia

Yuanyuan ZhouUniversity of California San Diego

Program Co-Chairs

Jian Zhang Microsoft Azure

Christina DelimitrouCornell University

Program Committee

Shuang Chen Huawei Cloud

Dan Crankshaw Microsoft Research Redmond

Yingnong Dang Microsoft Azure

Mingyu Gao Tsingha University

Ryan Huang Johns Hopkins University

Odej Kao Technische Universität Berlin

Neeraj Kulkarni Microsoft

Qingwei Lin Microsoft Research Asia

Shan Lu University of Chicago

Elena Novakovskaia Salesforce

Dan Pei Tsinghua University

Xin Peng Fudan University

Saravan Rajmohan Microsoft

Weiyi Shang Concordia University

Hanzhang Wang Ebay

Rich Wolski University of California Santa Barbara

Neeraja Yadwadkar Stanford University

Hongyu Zhang The University of Newcastle

Ming Zhao Arizona State University

Organizing Committee

Eli Cortez Microsoft Azure

Dan Crankshaw Microsoft Research Redmond

Yingnong Dang Microsoft Azure

Qingwei LinMicrosoft Research Asia

Publicity Chair

Igal FiglinMicrosoft Azure

Web Chair

Murali ChintalapatiMicrosoft Azure

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