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Meeting ID: 646 6810 2295

Passcode: 760417

A gather.town/AIOPS2021 session will be open for networking purposes. Please use it to interact as much as possible and take out the most of the virtual experience.

It is our greatest pleasure to welcome Prof. David Lo, as one of the keynote speakers of our workshop. Professor David Lo is an ACM Distinguished Member, Professor of Computer Science, and Director of the Information Systems and Technology cluster at Singapore Management University. His research interest is in the intersection of software engineering, cybersecurity, and AI, encompassing socio-technical aspects and analysis of different kinds of software artefacts, with the goal of improving software quality and security and developer productivity. He has won more than 15 international research and service awards including 6 ACM SIGSOFT Distinguished Paper awards and the 2021 IEEE TCSE Distinguished Service Award. He has served in more than 30 organizing committees and hundreds of program committees, including serving as general or program co-chairs of ASE 2020, SANER 2019, ICSME 2018, ICPC 2017, and ASE 2016. He is also serving on many journal editorial boards including IEEE Transactions on Software Engineering and IEEE Transactions on Reliability. More information about him and his group are available at https://soarsmu.github.io/.

He is going to give a talk with the title: Learning from History: How Can Past Failures Power Automation?

Failures are prevalent and affect many systems ranging from mobile apps to cloud services. Needless to say, these failures need to be resolved (or mitigated) to improve (or restore) software quality. To deal with failures, processes and systems have been set up to record failures as an issue (or incident) reports. These reports are then assigned to engineers who manage the reports with the eventual goal of resolving the corresponding failures. Much data about failures have been collected in repositories such as issue tracking systems (ITS) or incident management systems (IMS). Can this trove of data about past failures be used to help engineers in their jobs? This talk will provide an overview and reflection of the large body of work that builds automated tools that leverage the power of AI, trained on rich data in repositories recording past failures, for various tasks in the failure resolution process. Some open challenges will also be presented, with the goal of encouraging more research in this exciting area in the intersection of Software Engineering, Service-Oriented Computing, and AI. We are very excited and looking forward to this great talk!

It is our greatest pleasure to welcome Dr. Qingwei Lin, as one of the keynote speakers of our workshop. Qingwei Lin is a Sr. Principal Research Manager in the DKI (Data, Knowledge, Intelligence) area of Microsoft Research Asia. He is leading a team of researchers working on data-driven technologies for cloud intelligence, with innovations in machine learning and data mining algorithms. In the cloud intelligence area, Qingwei has multiple publications in the conferences of AAAI, IJCAI, SigKDD, WWW, ICSE, FSE, ASE, OSDI, NSDI, USENIX ATC, etc. The research technologies have been transferred into multiple Microsoft product divisions, such as Microsoft Azure, Office365, Windows, Bing, etc. Qingwei hosted Microsoft company-wide “Cloud Service Intelligence Summit” as the Chair for 4 consecutive years. He joined Microsoft Research in 2006. git ad A list of his recent publications can be found here.

He is going to give a talk with the title: Cloud Intelligence / AIOps - Infusing AI into Cloud Computing System
We are very excited and looking forward to this great talk!

The International Workshop on Artificial Intelligence for IT Operations should bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field. We want to strengthen the community and unite it towards the goal of joining the efforts for solving the main challenges the field is currently facing. A consensus and adoption of the principles of openness and reproducibility will boost the research in this emerging area significantly.

Following the great sucess of last year (AIOPS 2020, videos, proceedings), this workshop will be in conjunction with the 19th International Conference on Service-Oriented Computing (ICSOC) in Dubai, 22nd November 2021.

• Early anomaly, fault and failure (AFF) detection and analysis
• Self-healing, self-correction and auto-remediation
• Self-adaptive time-series based models for prognostics and forecasting
• AFF identification, localization, and isolation
• Root cause analysis
• Adaptive fault tolerance policies
• Forecasting of hardware and process quality
• Performance management
• Planning under uncertainty
• Predictive and prescriptive maintenance
• Maintenance scheduling and on-demand maintenance planning
• Alarm correlation
• Log analysis
• Fault tolerant system control
• Resiliency, reliability, and quality assurance
• Software dependability
• Autonomic process optimization
• Energy-efficient cloud operation
• Distributed resource management
• Autonomous service provisioning
• Visual analytics and interactive machine learning
• Active and life-long learning
• Design of experiment (DoE) and benchmarking
• Fault injection and chaos engineering
• Use-cases, testbeds, evaluation scenarios