AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
MLSys ’25 | May 2025
Systems Innovation
Algorithmic and hardware innovation for efficient, reliable, and sustainable cloud services and infrastructure at scale
出版物
年別出版物
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ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
The Eighth Annual Conference on Machine Learning and Systems (MLSys) | May 2025
Towards Cloud Efficiency with Large-scale Workload Characterization
A. Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri, Chetan Bansal
ICPE | May 2025
Time Warp: The Gap Between Developers’ Ideal vs Actual Workweeks in an AI-Driven Era
Sukrit Kumar, Drishti Goel, Tom Zimmermann, Brian Houck, B. Ashok, Chetan Bansal
ICSE SEIP ’25 | April 2025
Distinguished Paper Award
Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale
Kunal Jain, A. Parayil, Ankur Mallick, Rujia Wang, Renee St. Amant, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Shashwat Jaiswal, Yogesh Simmhan, Anoop Kulkarni, Steve Kofsky
ArXiv | February 2025
Towards Efficient Large Multimodal Model Serving
Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
February 2025
Triangle: Empowering Incident Triage with Multi-LLM-Agents
Zhaoyang Yu, Minghua Ma, Xiaoyong Feng, Ruomeng Ding, Chaoyun Zhang, Ze Li, Murali Chintalapati, Xuchao Zhang, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维
February 2025
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Ensuring Fair LLM Serving Amid Diverse Applications
Kunal Jain, Ankur Mallick, A. Parayil, Renee St. Amant, Rujia Wang, Victor Ruehle, Chetan Bansal, Saravan Rajmohan, Redwan Ibne Seraj Khan, Haiying Shen, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Yue Cheng
ArXiv | November 2024
Building AI Agents for Autonomous Clouds: Challenges and Design Principles
Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
2024 Symposium on Cloud Computing | November 2024
Can We Trust Auto-Mitigation? Improving Cloud Failure Prediction with Uncertain Positive Learning
Haozhe Li, Minghua Ma, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | October 2024
COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
33rd ACM International Conference on Information and Knowledge Management (CIKM) | October 2024
Early Bird: Ensuring Reliability of Cloud Systems Through Early Failure Prediction
Yudong Liu, Minghua Ma, Pu Zhao, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | October 2024
FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents
Xuchao Zhang, Tanish Mittal, Chetan Bansal, Rujia Wang, Minghua Ma, Zhixin Ren, Hao Huang, Saravan Rajmohan
October 2024
Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling
A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Kunal Jain, Anoop Kulkarni, Steve Kofsky
ArXiv | August 2024, 巻abs/2408.13510
Large Language Models Can Provide Accurate and Interpretable Incident Triage
Zexin Wang, Minghua Ma, Ze Li, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | August 2024
Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
Xuchao Zhang, Supriyo GHOSH, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan
Foundations of Software Engineering (FSE) | July 2024
X-lifecycle Learning for Cloud Incident Management using LLMs
Drishti Goel, Fiza Husain, Aditya Singh, Supriyo GHOSH, A. Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan
Foundations of Software Engineering (FSE) | July 2024
MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
Foundations of Software Engineering (FSE) | July 2024
Exploring LLM-based Agents for Root Cause Analysis
Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
FSE ’24: 32nd ACM International Conference on the Foundations of Software Engineering | July 2024
Designing Cloud Servers for Lower Carbon
Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
ISCA | June 2024
SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
ISCA | June 2024
LeanAttention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Ruehle, Saravan Rajmohan
May 2024
Dependency Aware Incident Linking in Large Cloud Systems
Supriyo GHOSH, Karish Grover, Jimmy Wong, Chetan Bansal, Rakesh Namineni, Mohit Verma, Saravan Rajmohan
The Web Conference (WWW) | May 2024
Intelligent Overclocking for Improved Cloud Efficiency
Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
AIOps ’24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
EuroSys’24 | April 2024
Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
NSDI 2024 | April 2024
Workload Intelligence: Punching Holes Through the Cloud Abstraction
Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
ArXiv | April 2024, 巻abs/2404.19143
Workload Intelligence: Punching Holes Through the Cloud Abstraction
Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
April 2024
Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective
Zexin Wang, Changhua Pei, Minghua Ma, Xin Wang, Zhihan Li, Dan Pei, Saravan Rajmohan, Dongmei Zhang, Qingwei Lin 林庆维, Haiming Zhang, Jianhui Li, Gaogang Xie
TheWebConf’24 | February 2024
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NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
IEEE Big Data 2023 | December 2023
Special session on Machine Learning on Big Data (MLBD)
Detection Is Better Than Cure: A Cloud Incidents Perspective
A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei Zhang, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
ArXiv | November 2023, 巻abs/2311.04254
PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
September 2023
How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads
Xiaoting Qin, Minghua Ma, Yueng Zhao, Jue Zhang, Chao Du, Yudong Liu, A. Parayil, Chetan Bansal, Saravan Rajmohan, Íñigo Goiri, Eli Cortez, Si Qin, Qingwei Lin 林庆维, Dongmei Zhang
DSN | June 2023
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
ICSE 2023 | May 2023
Snape: Reliable and Low-Cost Computing with Mixture of Spot and On-Demand VMs
Fangkai Yang, Lu Wang, Zhenyu Xu, Jue Zhang, Liqun Li, Bo Qiao, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Terry Yang, Victor Ruehle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
Proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) | March 2023
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AutoTSG: Learning and Synthesis for Incident Troubleshooting
Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
ESEC/FSE 2022 | November 2022
How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath
SoCC 2022 | November 2022
Best Paper Award
AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
ICPR | August 2022
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
SIGKDD 2022 | August 2022
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
SIGKDD’22 | August 2022
DeepAnalyze: Learning to Localize Crashes at Scale
Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
ICSE 2022 | May 2022
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
Yudong Liu, …, Qingwei Lin 林庆维, …
SIGKDD 2022 | May 2022
SoftNER: Mining knowledge graphs from Cloud Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
Empirical Software Engineering | April 2022, 巻27(4)
Spot Virtual Machine Eviction Prediction in Microsoft Cloud
Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
TheWebConf 2022 | April 2022
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HALO: Hierarchy-aware Fault Localization for Cloud Systems
Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
SigKDD 2021 | October 2021
How Long Will it Take to Mitigate this Incident for Online Service Systems?
Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
ISSRE’21 | September 2021
Best Research Paper
Intelligent container reallocation at Microsoft 365
Bo Qiao, Fangkai Yang, Chuan Luo, Yanan Wang, Johnny Li, Qingwei Lin 林庆维, Hongyu Zhang, Mohit Datta, Andrew Zhou, Thomas Moscibroda, Saravanakumar Rajmohan, Dongmei Zhang
2021 Foundations of Software Engineering | August 2021
Fighting the Fog of War: Automated Incident Detection for Cloud Systems
Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
Neural Knowledge Extraction From Cloud Service Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Tom Zimmermann
43rd International Conference on Software Engineering (ICSE ’21) – SEIP Track | May 2021
Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
AAAI’21 | March 2021
PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
Chuan Luo, …, Qingwei Lin 林庆维
AAAI’21 | March 2021
NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
WWW (TheWebConf) 2021 | February 2021
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DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services
Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman
ICSE 2020 | May 2020
Rex: Preventing Bugs and Misconfiguration in Large Services using Correlated Change Analysis
Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, B. Ashok, Chetan Bansal, Chandra Maddila, Christian Bird, Sumit Asthana, Aditya Kumar
Networked System Design and Implementation (NSDI) | February 2020
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WhoDo: Automating Reviewer Suggestions at Scale
Sumit Asthana, Rahul Kumar, Ranjita Bhagwan, Chetan Bansal, Christian Bird, Chandra Maddila, Sonu Mehta, B. Ashok
ESEC/FSE 2019 | August 2019
Predicting Pull Request Completion Time: A Case Study on Large Scale Cloud Services
Chandra Maddila, Chetan Bansal, Nachi Nagappan
ESEC/FSE 2019 | August 2019
Building sankie: an AI platform for DevOps
Rahul Kumar, Chetan Bansal, Chandra Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava
1st International Workshop on Bots in Software Engineering (BotSE ’19) | May 2019
FastLane: Test Minimization for Rapidly Deployed Large-scale Online Services
Ranjita Bhagwan, Adithya Philip, Rahul Kumar, Chandra Maddila, Nachi Nagappan
International Conference on Software Engineering | May 2019
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Orca: Differential Bug Localization in Large-Scale Services
Ranjita Bhagwan, Rahul Kumar, Chandra Maddila, Adithya Abraham Philip
13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
Won the Jay Lepreau Best Paper Award
研究分野別論文
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ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
The Eighth Annual Conference on Machine Learning and Systems (MLSys) | May 2025
AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
MLSys ’25 | May 2025
Towards Cloud Efficiency with Large-scale Workload Characterization
A. Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri, Chetan Bansal
ICPE | May 2025
Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale
Kunal Jain, A. Parayil, Ankur Mallick, Rujia Wang, Renee St. Amant, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Shashwat Jaiswal, Yogesh Simmhan, Anoop Kulkarni, Steve Kofsky
ArXiv | February 2025
Towards Efficient Large Multimodal Model Serving
Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
February 2025
Ensuring Fair LLM Serving Amid Diverse Applications
Kunal Jain, Ankur Mallick, A. Parayil, Renee St. Amant, Rujia Wang, Victor Ruehle, Chetan Bansal, Saravan Rajmohan, Redwan Ibne Seraj Khan, Haiying Shen, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Yue Cheng
ArXiv | November 2024
Building AI Agents for Autonomous Clouds: Challenges and Design Principles
Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
2024 Symposium on Cloud Computing | November 2024
FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents
Xuchao Zhang, Tanish Mittal, Chetan Bansal, Rujia Wang, Minghua Ma, Zhixin Ren, Hao Huang, Saravan Rajmohan
October 2024
COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
33rd ACM International Conference on Information and Knowledge Management (CIKM) | October 2024
Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling
A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Kunal Jain, Anoop Kulkarni, Steve Kofsky
ArXiv | August 2024, 巻abs/2408.13510
Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
Xuchao Zhang, Supriyo GHOSH, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan
Foundations of Software Engineering (FSE) | July 2024
X-lifecycle Learning for Cloud Incident Management using LLMs
Drishti Goel, Fiza Husain, Aditya Singh, Supriyo GHOSH, A. Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan
Foundations of Software Engineering (FSE) | July 2024
MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
Foundations of Software Engineering (FSE) | July 2024
Exploring LLM-based Agents for Root Cause Analysis
Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
FSE ’24: 32nd ACM International Conference on the Foundations of Software Engineering | July 2024
LeanAttention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Ruehle, Saravan Rajmohan
May 2024
Dependency Aware Incident Linking in Large Cloud Systems
Supriyo GHOSH, Karish Grover, Jimmy Wong, Chetan Bansal, Rakesh Namineni, Mohit Verma, Saravan Rajmohan
The Web Conference (WWW) | May 2024
Intelligent Overclocking for Improved Cloud Efficiency
Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
AIOps ’24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
EuroSys’24 | April 2024
Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
Workload Intelligence: Punching Holes Through the Cloud Abstraction
Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
April 2024
NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
IEEE Big Data 2023 | December 2023
Special session on Machine Learning on Big Data (MLBD)
Detection Is Better Than Cure: A Cloud Incidents Perspective
A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei Zhang, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
ArXiv | November 2023, 巻abs/2311.04254
PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
September 2023
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
ICSE 2023 | May 2023
AutoTSG: Learning and Synthesis for Incident Troubleshooting
Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
ESEC/FSE 2022 | November 2022
AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
ICPR | August 2022
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
SIGKDD 2022 | August 2022
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
Yudong Liu, …, Qingwei Lin 林庆维, …
SIGKDD 2022 | May 2022
DeepAnalyze: Learning to Localize Crashes at Scale
Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
ICSE 2022 | May 2022
Spot Virtual Machine Eviction Prediction in Microsoft Cloud
Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
TheWebConf 2022 | April 2022
SoftNER: Mining knowledge graphs from Cloud Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
Empirical Software Engineering | April 2022, 巻27(4)
HALO: Hierarchy-aware Fault Localization for Cloud Systems
Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
SigKDD 2021 | October 2021
How Long Will it Take to Mitigate this Incident for Online Service Systems?
Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
ISSRE’21 | September 2021
Best Research Paper
Intelligent container reallocation at Microsoft 365
Bo Qiao, Fangkai Yang, Chuan Luo, Yanan Wang, Johnny Li, Qingwei Lin 林庆维, Hongyu Zhang, Mohit Datta, Andrew Zhou, Thomas Moscibroda, Saravanakumar Rajmohan, Dongmei Zhang
2021 Foundations of Software Engineering | August 2021
Fighting the Fog of War: Automated Incident Detection for Cloud Systems
Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
Neural Knowledge Extraction From Cloud Service Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Tom Zimmermann
43rd International Conference on Software Engineering (ICSE ’21) – SEIP Track | May 2021
Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
AAAI’21 | March 2021
PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
Chuan Luo, …, Qingwei Lin 林庆维
AAAI’21 | March 2021
NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
WWW (TheWebConf) 2021 | February 2021
Predicting Pull Request Completion Time: A Case Study on Large Scale Cloud Services
Chandra Maddila, Chetan Bansal, Nachi Nagappan
ESEC/FSE 2019 | August 2019
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ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
The Eighth Annual Conference on Machine Learning and Systems (MLSys) | May 2025
AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
MLSys ’25 | May 2025
Towards Cloud Efficiency with Large-scale Workload Characterization
A. Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri, Chetan Bansal
ICPE | May 2025
Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale
Kunal Jain, A. Parayil, Ankur Mallick, Rujia Wang, Renee St. Amant, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Shashwat Jaiswal, Yogesh Simmhan, Anoop Kulkarni, Steve Kofsky
ArXiv | February 2025
Triangle: Empowering Incident Triage with Multi-LLM-Agents
Zhaoyang Yu, Minghua Ma, Xiaoyong Feng, Ruomeng Ding, Chaoyun Zhang, Ze Li, Murali Chintalapati, Xuchao Zhang, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维
February 2025
Towards Efficient Large Multimodal Model Serving
Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
February 2025
Ensuring Fair LLM Serving Amid Diverse Applications
Kunal Jain, Ankur Mallick, A. Parayil, Renee St. Amant, Rujia Wang, Victor Ruehle, Chetan Bansal, Saravan Rajmohan, Redwan Ibne Seraj Khan, Haiying Shen, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Yue Cheng
ArXiv | November 2024
Building AI Agents for Autonomous Clouds: Challenges and Design Principles
Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
2024 Symposium on Cloud Computing | November 2024
COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
33rd ACM International Conference on Information and Knowledge Management (CIKM) | October 2024
Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling
A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Kunal Jain, Anoop Kulkarni, Steve Kofsky
ArXiv | August 2024, 巻abs/2408.13510
Large Language Models Can Provide Accurate and Interpretable Incident Triage
Zexin Wang, Minghua Ma, Ze Li, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | August 2024
Designing Cloud Servers for Lower Carbon
Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
ISCA | June 2024
SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
ISCA | June 2024
LeanAttention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers
Rya Sanovar, Srikant Bharadwaj, Renee St. Amant, Victor Ruehle, Saravan Rajmohan
May 2024
Intelligent Overclocking for Improved Cloud Efficiency
Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
AIOps ’24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
EuroSys’24 | April 2024
Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
Workload Intelligence: Punching Holes Through the Cloud Abstraction
Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
ArXiv | April 2024, 巻abs/2404.19143
OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
NSDI 2024 | April 2024
NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
IEEE Big Data 2023 | December 2023
Special session on Machine Learning on Big Data (MLBD)
Detection Is Better Than Cure: A Cloud Incidents Perspective
A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
September 2023
How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads
Xiaoting Qin, Minghua Ma, Yueng Zhao, Jue Zhang, Chao Du, Yudong Liu, A. Parayil, Chetan Bansal, Saravan Rajmohan, Íñigo Goiri, Eli Cortez, Si Qin, Qingwei Lin 林庆维, Dongmei Zhang
DSN | June 2023
Snape: Reliable and Low-Cost Computing with Mixture of Spot and On-Demand VMs
Fangkai Yang, Lu Wang, Zhenyu Xu, Jue Zhang, Liqun Li, Bo Qiao, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Terry Yang, Victor Ruehle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
Proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) | March 2023
AutoTSG: Learning and Synthesis for Incident Troubleshooting
Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
ESEC/FSE 2022 | November 2022
How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath
SoCC 2022 | November 2022
Best Paper Award
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
SIGKDD’22 | August 2022
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
SIGKDD 2022 | August 2022
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
Yudong Liu, …, Qingwei Lin 林庆维, …
SIGKDD 2022 | May 2022
DeepAnalyze: Learning to Localize Crashes at Scale
Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
ICSE 2022 | May 2022
Spot Virtual Machine Eviction Prediction in Microsoft Cloud
Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
TheWebConf 2022 | April 2022
HALO: Hierarchy-aware Fault Localization for Cloud Systems
Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
SigKDD 2021 | October 2021
How Long Will it Take to Mitigate this Incident for Online Service Systems?
Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
ISSRE’21 | September 2021
Best Research Paper
Intelligent container reallocation at Microsoft 365
Bo Qiao, Fangkai Yang, Chuan Luo, Yanan Wang, Johnny Li, Qingwei Lin 林庆维, Hongyu Zhang, Mohit Datta, Andrew Zhou, Thomas Moscibroda, Saravanakumar Rajmohan, Dongmei Zhang
2021 Foundations of Software Engineering | August 2021
Fighting the Fog of War: Automated Incident Detection for Cloud Systems
Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services
Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman
ICSE 2020 | May 2020
Rex: Preventing Bugs and Misconfiguration in Large Services using Correlated Change Analysis
Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, B. Ashok, Chetan Bansal, Chandra Maddila, Christian Bird, Sumit Asthana, Aditya Kumar
Networked System Design and Implementation (NSDI) | February 2020
Building sankie: an AI platform for DevOps
Rahul Kumar, Chetan Bansal, Chandra Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava
1st International Workshop on Bots in Software Engineering (BotSE ’19) | May 2019
FastLane: Test Minimization for Rapidly Deployed Large-scale Online Services
Ranjita Bhagwan, Adithya Philip, Rahul Kumar, Chandra Maddila, Nachi Nagappan
International Conference on Software Engineering | May 2019
Orca: Differential Bug Localization in Large-Scale Services
Ranjita Bhagwan, Rahul Kumar, Chandra Maddila, Adithya Abraham Philip
13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
Won the Jay Lepreau Best Paper Award
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AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
MLSys ’25 | May 2025
Triangle: Empowering Incident Triage with Multi-LLM-Agents
Zhaoyang Yu, Minghua Ma, Xiaoyong Feng, Ruomeng Ding, Chaoyun Zhang, Ze Li, Murali Chintalapati, Xuchao Zhang, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维
February 2025
Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
EuroSys’24 | April 2024
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
SIGKDD’22 | August 2022
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
SIGKDD 2022 | August 2022
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
Yudong Liu, …, Qingwei Lin 林庆维, …
SIGKDD 2022 | May 2022
Spot Virtual Machine Eviction Prediction in Microsoft Cloud
Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
TheWebConf 2022 | April 2022
HALO: Hierarchy-aware Fault Localization for Cloud Systems
Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
SigKDD 2021 | October 2021
How Long Will it Take to Mitigate this Incident for Online Service Systems?
Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
ISSRE’21 | September 2021
Best Research Paper
Fighting the Fog of War: Automated Incident Detection for Cloud Systems
Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
AAAI’21 | March 2021
PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
Chuan Luo, …, Qingwei Lin 林庆维
AAAI’21 | March 2021
NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
WWW (TheWebConf) 2021 | February 2021
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Can We Trust Auto-Mitigation? Improving Cloud Failure Prediction with Uncertain Positive Learning
Haozhe Li, Minghua Ma, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | October 2024
Early Bird: Ensuring Reliability of Cloud Systems Through Early Failure Prediction
Yudong Liu, Minghua Ma, Pu Zhao, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | October 2024
Exploring LLM-based Agents for Root Cause Analysis
Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
FSE ’24: 32nd ACM International Conference on the Foundations of Software Engineering | July 2024
Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
EuroSys’24 | April 2024
OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
NSDI 2024 | April 2024
Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective
Zexin Wang, Changhua Pei, Minghua Ma, Xin Wang, Zhihan Li, Dan Pei, Saravan Rajmohan, Dongmei Zhang, Qingwei Lin 林庆维, Haiming Zhang, Jianhui Li, Gaogang Xie
TheWebConf’24 | February 2024
NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
IEEE Big Data 2023 | December 2023
Special session on Machine Learning on Big Data (MLBD)
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
SIGKDD’22 | August 2022
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
SIGKDD 2022 | August 2022
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
Yudong Liu, …, Qingwei Lin 林庆维, …
SIGKDD 2022 | May 2022
Spot Virtual Machine Eviction Prediction in Microsoft Cloud
Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
TheWebConf 2022 | April 2022
HALO: Hierarchy-aware Fault Localization for Cloud Systems
Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
SigKDD 2021 | October 2021
How Long Will it Take to Mitigate this Incident for Online Service Systems?
Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
ISSRE’21 | September 2021
Best Research Paper
Fighting the Fog of War: Automated Incident Detection for Cloud Systems
Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
AAAI’21 | March 2021
PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
Chuan Luo, …, Qingwei Lin 林庆维
AAAI’21 | March 2021
NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
WWW (TheWebConf) 2021 | February 2021
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Time Warp: The Gap Between Developers’ Ideal vs Actual Workweeks in an AI-Driven Era
Sukrit Kumar, Drishti Goel, Tom Zimmermann, Brian Houck, B. Ashok, Chetan Bansal
ICSE SEIP ’25 | April 2025
Distinguished Paper Award
Building AI Agents for Autonomous Clouds: Challenges and Design Principles
Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
2024 Symposium on Cloud Computing | November 2024
FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents
Xuchao Zhang, Tanish Mittal, Chetan Bansal, Rujia Wang, Minghua Ma, Zhixin Ren, Hao Huang, Saravan Rajmohan
October 2024
Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
EuroSys’24 | April 2024
Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
Detection Is Better Than Cure: A Cloud Incidents Perspective
A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
ICSE 2023 | May 2023
AutoTSG: Learning and Synthesis for Incident Troubleshooting
Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
ESEC/FSE 2022 | November 2022
How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath
SoCC 2022 | November 2022
Best Paper Award
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
SIGKDD 2022 | August 2022
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
Yudong Liu, …, Qingwei Lin 林庆维, …
SIGKDD 2022 | May 2022
DeepAnalyze: Learning to Localize Crashes at Scale
Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
ICSE 2022 | May 2022
Spot Virtual Machine Eviction Prediction in Microsoft Cloud
Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
TheWebConf 2022 | April 2022
SoftNER: Mining knowledge graphs from Cloud Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
Empirical Software Engineering | April 2022, 巻27(4)
How Long Will it Take to Mitigate this Incident for Online Service Systems?
Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
ISSRE’21 | September 2021
Best Research Paper
Fighting the Fog of War: Automated Incident Detection for Cloud Systems
Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
Neural Knowledge Extraction From Cloud Service Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Tom Zimmermann
43rd International Conference on Software Engineering (ICSE ’21) – SEIP Track | May 2021
DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services
Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman
ICSE 2020 | May 2020
Rex: Preventing Bugs and Misconfiguration in Large Services using Correlated Change Analysis
Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, B. Ashok, Chetan Bansal, Chandra Maddila, Christian Bird, Sumit Asthana, Aditya Kumar
Networked System Design and Implementation (NSDI) | February 2020
WhoDo: Automating Reviewer Suggestions at Scale
Sumit Asthana, Rahul Kumar, Ranjita Bhagwan, Chetan Bansal, Christian Bird, Chandra Maddila, Sonu Mehta, B. Ashok
ESEC/FSE 2019 | August 2019
Predicting Pull Request Completion Time: A Case Study on Large Scale Cloud Services
Chandra Maddila, Chetan Bansal, Nachi Nagappan
ESEC/FSE 2019 | August 2019
Building sankie: an AI platform for DevOps
Rahul Kumar, Chetan Bansal, Chandra Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava
1st International Workshop on Bots in Software Engineering (BotSE ’19) | May 2019
FastLane: Test Minimization for Rapidly Deployed Large-scale Online Services
Ranjita Bhagwan, Adithya Philip, Rahul Kumar, Chandra Maddila, Nachi Nagappan
International Conference on Software Engineering | May 2019
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Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
ICSE 2023 | May 2023
種類別出版物
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Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale
Kunal Jain, A. Parayil, Ankur Mallick, Rujia Wang, Renee St. Amant, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Shashwat Jaiswal, Yogesh Simmhan, Anoop Kulkarni, Steve Kofsky
ArXiv | February 2025
Ensuring Fair LLM Serving Amid Diverse Applications
Kunal Jain, Ankur Mallick, A. Parayil, Renee St. Amant, Rujia Wang, Victor Ruehle, Chetan Bansal, Saravan Rajmohan, Redwan Ibne Seraj Khan, Haiying Shen, Anoop Kulkarni, Steve Kofsky, Pankhuri Choudhary, Yue Cheng
ArXiv | November 2024
Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Scheduling
A. Parayil, Ankur Mallick, Esha Choukse, Xiaoting Qin, Jue Zhang, Íñigo Goiri, Rujia Wang, Chetan Bansal, Victor Ruehle, Saravan Rajmohan, Kunal Jain, Anoop Kulkarni, Steve Kofsky
ArXiv | August 2024, 巻abs/2408.13510
Workload Intelligence: Punching Holes Through the Cloud Abstraction
Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
ArXiv | April 2024, 巻abs/2404.19143
Workload Intelligence: Punching Holes Through the Cloud Abstraction
Lexiang Huang, A. Parayil, Jue Zhang, Xiaoting Qin, Chetan Bansal, Jovan Stojkovic, Pantea Zardoshti, Pulkit Misra, Eli Cortez, Raphael Ghelman, Íñigo Goiri, Saravan Rajmohan, Jim Kleewein, Rodrigo Fonseca, Timothy Zhu, Ricardo Bianchini
April 2024
Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei Zhang, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
ArXiv | November 2023, 巻abs/2311.04254
SoftNER: Mining knowledge graphs from Cloud Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
Empirical Software Engineering | April 2022, 巻27(4)
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ProtoRAIL: A Risk-cognizant Imitation Agent for Adaptive vCPU Oversubscription In The Cloud
Lu Wang, Mayukh Das, Fangkai Yang, Bo Qiao, Hang Dong, Si Qin, Victor Ruehle, Chetan Bansal, Eli Cortez, Íñigo Goiri, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
The Eighth Annual Conference on Machine Learning and Systems (MLSys) | May 2025
AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud
Yinfang Chen, Manish Shetty, Gagan Somashekar, Minghua Ma, Yogesh Simmhan, Jonathan Mace, Chetan Bansal, Rujia Wang, Saravan Rajmohan
MLSys ’25 | May 2025
Towards Cloud Efficiency with Large-scale Workload Characterization
A. Parayil, Jue Zhang, Xiaoting Qin, Íñigo Goiri, Chetan Bansal
ICPE | May 2025
Time Warp: The Gap Between Developers’ Ideal vs Actual Workweeks in an AI-Driven Era
Sukrit Kumar, Drishti Goel, Tom Zimmermann, Brian Houck, B. Ashok, Chetan Bansal
ICSE SEIP ’25 | April 2025
Distinguished Paper Award
Building AI Agents for Autonomous Clouds: Challenges and Design Principles
Manisha M Shetty, Yinfang Chen, Gagan Somashekar, Minghua Ma, Yogesh L. Simmhan, Xuchao Zhang, Jonathan Mace, Pedro Las-Casas, Shachee Mishra Gupta, Suman Nath, Chetan Bansal, Saravan Rajmohan
2024 Symposium on Cloud Computing | November 2024
Can We Trust Auto-Mitigation? Improving Cloud Failure Prediction with Uncertain Positive Learning
Haozhe Li, Minghua Ma, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | October 2024
Early Bird: Ensuring Reliability of Cloud Systems Through Early Failure Prediction
Yudong Liu, Minghua Ma, Pu Zhao, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | October 2024
COIN: Chance-Constrained Imitation Learning for Safe and Adaptive Resource Oversubscription under Uncertainty
Lu Wang, Mayukh Das, Fangkai Yang, Chao Du, Bo Qiao, Hang Dong, Chetan Bansal, Si Qin, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang, Qi Zhang
33rd ACM International Conference on Information and Knowledge Management (CIKM) | October 2024
Large Language Models Can Provide Accurate and Interpretable Incident Triage
Zexin Wang, Minghua Ma, Ze Li, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
2024 International Symposium on Software Reliability Engineering | August 2024
Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
Xuchao Zhang, Supriyo GHOSH, Chetan Bansal, Rujia Wang, Minghua Ma, Yu Kang, Saravan Rajmohan
Foundations of Software Engineering (FSE) | July 2024
X-lifecycle Learning for Cloud Incident Management using LLMs
Drishti Goel, Fiza Husain, Aditya Singh, Supriyo GHOSH, A. Parayil, Chetan Bansal, Xuchao Zhang, Saravan Rajmohan
Foundations of Software Engineering (FSE) | July 2024
MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
Zhaoyang Yu, Minghua Ma, Chaoyun Zhang, Si Qin, Yu Kang, Chetan Bansal, Saravan Rajmohan, Yingnong Dang, Changhua Pei, Dan Pei, Qingwei Lin 林庆维, Dongmei Zhang
Foundations of Software Engineering (FSE) | July 2024
Exploring LLM-based Agents for Root Cause Analysis
Devjeet Roy, Xuchao Zhang, Rashi Bhave, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
FSE ’24: 32nd ACM International Conference on the Foundations of Software Engineering | July 2024
Designing Cloud Servers for Lower Carbon
Jaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene, Chaojie Zhang, Esha Choukse, Kali Frost, Rodrigo Fonseca, Brijesh Warrier, Chetan Bansal, Jonathan Stern, Ricardo Bianchini, Akshitha Sriraman
ISCA | June 2024
SmartOClock: Workload- and Risk-Aware Overclocking in the Cloud
Jovan Stojkovic, Pulkit Misra, Íñigo Goiri, Sam Whitlock, Esha Choukse, Mayukh Das, Chetan Bansal, Jason Lee, Zoey Sun, Haoran Qiu, Reed Zimmermann, Savyasachi Samal, Brijesh Warrier, Ashish Raniwala, Ricardo Bianchini
ISCA | June 2024
Dependency Aware Incident Linking in Large Cloud Systems
Supriyo GHOSH, Karish Grover, Jimmy Wong, Chetan Bansal, Rakesh Namineni, Mohit Verma, Saravan Rajmohan
The Web Conference (WWW) | May 2024
Intelligent Overclocking for Improved Cloud Efficiency
Aditya Soni, Mayukh Das, Pulkit Misra, Chetan Bansal
AIOps ’24 workshop @ ASPLOS [5th International Workshop on Cloud Intelligence / AIOps] | April 2024
Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xue‐Chao Gao, Hao Fan, Ming Wen, Jun Zeng, Supriyo GHOSH, Xuchao Zhang, Qingwei Lin 林庆维, Saravan Rajmohan, Dongmei Zhang
EuroSys’24 | April 2024
Intelligent Monitoring Framework for Cloud Services: A Data-Driven Approach
Pooja Srinivas, Fiza Husain, A. Parayil, Ayush Choure, Chetan Bansal, Saravan Rajmohan
46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’24) | April 2024
OPPerTune: Post-Deployment Configuration Tuning of Services Made Easy
Gagan Somashekar, Karan Tandon, Anush Kini, Chieh-Chun Chang, Petr Husak, Ranjita Bhagwan, Mayukh Das, Anshul Gandhi, Nagarajan Natarajan
NSDI 2024 | April 2024
Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective
Zexin Wang, Changhua Pei, Minghua Ma, Xin Wang, Zhihan Li, Dan Pei, Saravan Rajmohan, Dongmei Zhang, Qingwei Lin 林庆维, Haiming Zhang, Jianhui Li, Gaogang Xie
TheWebConf’24 | February 2024
NASerEx: Optimizing Early Exits via AutoML for Scalable Efficient Inference in Big Image Streams
Aakash Kapoor, Rajath Elias Soans, Soham Dixit, Pradeep NS, Brijraj Singh, Mayukh Das
IEEE Big Data 2023 | December 2023
Special session on Machine Learning on Big Data (MLBD)
Detection Is Better Than Cure: A Cloud Incidents Perspective
A. Parayil, Supriyo GHOSH, Yu Kang, Minghua Ma, Chetan Bansal, Suman Nath, Jonathan Mace, Vaibhav Ganatra
ESEC/FSE 2023: Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering | November 2023
How Different are the Cloud Workloads? Characterizing Large-Scale Private and Public Cloud Workloads
Xiaoting Qin, Minghua Ma, Yueng Zhao, Jue Zhang, Chao Du, Yudong Liu, A. Parayil, Chetan Bansal, Saravan Rajmohan, Íñigo Goiri, Eli Cortez, Si Qin, Qingwei Lin 林庆维, Dongmei Zhang
DSN | June 2023
Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models
Toufique Ahmed, Supriyo GHOSH, Chetan Bansal, Tom Zimmermann, Xuchao Zhang, Saravan Rajmohan
ICSE 2023 | May 2023
Snape: Reliable and Low-Cost Computing with Mixture of Spot and On-Demand VMs
Fangkai Yang, Lu Wang, Zhenyu Xu, Jue Zhang, Liqun Li, Bo Qiao, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Terry Yang, Victor Ruehle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
Proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) | March 2023
AutoTSG: Learning and Synthesis for Incident Troubleshooting
Manish Shetty, Chetan Bansal, Sai Pramod Upadhyayula, Arjun Radhakrishna, Anurag Gupta
ESEC/FSE 2022 | November 2022
How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
Supriyo GHOSH, Manish Shetty, Chetan Bansal, Suman Nath
SoCC 2022 | November 2022
Best Paper Award
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
Jie Yan, Yunlei Lu, Liting Chen, Si Qin, Yixin Fang, Qingwei Lin 林庆维, Thomas Moscibroda, Saravan Rajmohan, Dongmei Zhang
SIGKDD’22 | August 2022
AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
Mayukh Das, Brijraj Singh, Harsh Kanti Chheda, Pawan Sharma, Pradeep NS
ICPR | August 2022
NENYA: Cascade Reinforcement Learning for Cost-Aware Failure Mitigation at Microsoft 365
Lu Wang, Pu Zhao, Chao Du, Chuan Luo, Mengna Su, Fangkai Yang, Yudong Liu, Qingwei Lin 林庆维, Min Wang, Yingnong Dang, Hongyu Zhang, Saravan Rajmohan, Dongmei Zhang
SIGKDD 2022 | August 2022
Multi-task Hierarchical Classification for Disk Failure Prediction in Online Service Systems
Yudong Liu, …, Qingwei Lin 林庆维, …
SIGKDD 2022 | May 2022
DeepAnalyze: Learning to Localize Crashes at Scale
Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
ICSE 2022 | May 2022
Spot Virtual Machine Eviction Prediction in Microsoft Cloud
Fangkai Yang, Bowen Pang, Jue Zhang, Bo Qiao, Lu Wang, Camille Couturier, Chetan Bansal, Soumya Ram, Si Qin, Zhen Ma, Íñigo Goiri, Eli Cortez, Senthil Baladhandayutham, Victor Rühle, Saravan Rajmohan, Qingwei Lin 林庆维, Dongmei Zhang
TheWebConf 2022 | April 2022
HALO: Hierarchy-aware Fault Localization for Cloud Systems
Xu Zhang, Chao Du, Yifan Li, Yong Xu, Hongyu Zhang, Si Qin, Ze Li, Qingwei Lin 林庆维, Yingnong Dang, Andrew Zhou, Saravanakumar Rajmohan, Dongmei Zhang
SigKDD 2021 | October 2021
How Long Will it Take to Mitigate this Incident for Online Service Systems?
Weijing Wang, Junjie Chen, Lin Yang, Hongyu Zhang, Pu Zhao, Bo Qiao, Yu Kang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Feng Gao, Zhangwei Xu, Yingnong Dang, Dongmei Zhang
ISSRE’21 | September 2021
Best Research Paper
Intelligent container reallocation at Microsoft 365
Bo Qiao, Fangkai Yang, Chuan Luo, Yanan Wang, Johnny Li, Qingwei Lin 林庆维, Hongyu Zhang, Mohit Datta, Andrew Zhou, Thomas Moscibroda, Saravanakumar Rajmohan, Dongmei Zhang
2021 Foundations of Software Engineering | August 2021
Fighting the Fog of War: Automated Incident Detection for Cloud Systems
Liqun Li, Xu Zhang, Xin Zhao, Hongyu Zhang, Yu Kang, Pu Zhao, Bo Qiao, Shilin He, Pochian Lee, Jeffrey Sun, Feng Gao, Li Yang, Qingwei Lin 林庆维, Saravanakumar Rajmohan, Zhangwei Xu, Dongmei Zhang
2021 USENIX Annual Technical Conference (USENIX ATC’21) | August 2021
Neural Knowledge Extraction From Cloud Service Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Tom Zimmermann
43rd International Conference on Software Engineering (ICSE ’21) – SEIP Track | May 2021
Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
Chuan Luo, Bo Qiao, Wenqian Xing, Xin Chen, Pu Zhao, Chao Du, Randolph Yao, Hongyu Zhang, Wei Wu, Shaowei Cai, Saravanakumar Rajmohan, Qingwei Lin 林庆维
AAAI’21 | March 2021
PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector
Chuan Luo, …, Qingwei Lin 林庆维
AAAI’21 | March 2021
NTAM: Neighborhood-Temporal Attention Model for Disk Failure Prediction in Cloud Platforms
Chuan Luo, Pu Zhao, …, Qingwei Lin 林庆维, …
WWW (TheWebConf) 2021 | February 2021
DeCaf: Diagnosing and Triaging Performance Issues in Large-Scale Cloud Services
Chetan Bansal, Sundararajan Renganathan, Ashima Asudani, Olivier Midy, Mathru Janakiraman
ICSE 2020 | May 2020
Rex: Preventing Bugs and Misconfiguration in Large Services using Correlated Change Analysis
Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, B. Ashok, Chetan Bansal, Chandra Maddila, Christian Bird, Sumit Asthana, Aditya Kumar
Networked System Design and Implementation (NSDI) | February 2020
WhoDo: Automating Reviewer Suggestions at Scale
Sumit Asthana, Rahul Kumar, Ranjita Bhagwan, Chetan Bansal, Christian Bird, Chandra Maddila, Sonu Mehta, B. Ashok
ESEC/FSE 2019 | August 2019
Predicting Pull Request Completion Time: A Case Study on Large Scale Cloud Services
Chandra Maddila, Chetan Bansal, Nachi Nagappan
ESEC/FSE 2019 | August 2019
Building sankie: an AI platform for DevOps
Rahul Kumar, Chetan Bansal, Chandra Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava
1st International Workshop on Bots in Software Engineering (BotSE ’19) | May 2019
FastLane: Test Minimization for Rapidly Deployed Large-scale Online Services
Ranjita Bhagwan, Adithya Philip, Rahul Kumar, Chandra Maddila, Nachi Nagappan
International Conference on Software Engineering | May 2019
Orca: Differential Bug Localization in Large-Scale Services
Ranjita Bhagwan, Rahul Kumar, Chandra Maddila, Adithya Abraham Philip
13th USENIX Symposium on Operating Systems Design and Implementation | October 2018
Won the Jay Lepreau Best Paper Award
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Triangle: Empowering Incident Triage with Multi-LLM-Agents
Zhaoyang Yu, Minghua Ma, Xiaoyong Feng, Ruomeng Ding, Chaoyun Zhang, Ze Li, Murali Chintalapati, Xuchao Zhang, Rujia Wang, Chetan Bansal, Saravan Rajmohan, Qingwei Lin 林庆维
February 2025
Towards Efficient Large Multimodal Model Serving
Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca
February 2025
FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents
Xuchao Zhang, Tanish Mittal, Chetan Bansal, Rujia Wang, Minghua Ma, Zhixin Ren, Hao Huang, Saravan Rajmohan
October 2024
PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, Saravan Rajmohan
September 2023
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