17 citations · 39 across the 17 of their papers we have counts for
17 papers
From General Agents to RCA Experts: A Self-Evolving Harness for Root Cause Analysis
Haiyu Huang, Jiewei Lyu, Zhihan Jiang +5
Automated root cause analysis (RCA) with large language models (LLMs) has drawn growing attention. Today, SREs typically automate RCA with LLMs in one of two ways: directly using a…
Help Without Being Asked: A Deployed Proactive Agent System for On-Call Support with Continuous Self-Improvement
Fengrui Liu, Xiao He, Tieying Zhang
In large-scale cloud service platforms, thousands of customer tickets are generated daily and are typically handled through on-call dialogues. This high volume of on-call interacti…
KairosVL: Orchestrating Time Series and Semantics for Unified Reasoning
Haotian Si, Changhua Pei, Xiao He +9
Driven by the increasingly complex and decision-oriented demands of time series analysis, we introduce the Semantic-Conditional Time Series Reasoning task, which extends convention…
ZeroCard: Cardinality Estimation with Zero Dependence on Target Databases -- No Data, No Query, No Retraining
Xianghong Xu, Rong Kang, Xiao He +3
Cardinality estimation is a fundamental task in database systems and plays a critical role in query optimization. Despite significant advances in learning-based cardinality estimat…
ErrorPrism: Reconstructing Error Propagation Paths in Cloud Service Systems
Junsong Pu, Yichen Li, Zhuangbin Chen +6
Reliability management in cloud service systems is challenging due to the cascading effect of failures. Error wrapping, a practice prevalent in modern microservice development, enr…
LogPilot: Intent-aware and Scalable Alert Diagnosis for Large-scale Online Service Systems
Zhihan Jiang, Jinyang Liu, Yichen Li +7
Effective alert diagnosis is essential for ensuring the reliability of large-scale online service systems. However, on-call engineers are often burdened with manually inspecting ma…
Data-Agnostic Cardinality Learning from Imperfect Workloads
Peizhi Wu, Rong Kang, Tieying Zhang +3
Cardinality estimation (CardEst) is a critical aspect of query optimization. Traditionally, it leverages statistics built directly over the data. However, organizational policies (…
Towards VM Rescheduling Optimization Through Deep Reinforcement Learning
Xianzhong Ding, Yunkai Zhang, Binbin Chen +6
Modern industry-scale data centers need to manage a large number of virtual machines (VMs). Due to the continual creation and release of VMs, many small resource fragments are scat…
ABase: the Multi-Tenant NoSQL Serverless Database for Diverse and Dynamic Workloads in Large-scale Cloud Environments
Rong Kang, Yanbin Chen, Ye Liu +8
Multi-tenant architectures enhance the elasticity and resource utilization of NoSQL databases by allowing multiple tenants to co-locate and share resources. However, in large-scale…
Adaptive and Efficient Log Parsing as a Cloud Service
Zeyan Li, Jie Song, Tieying Zhang +6
Logs are a critical data source for cloud systems, enabling advanced features like monitoring, alerting, and root cause analysis. However, the massive scale and diverse formats of…
TickIt: Leveraging Large Language Models for Automated Ticket Escalation
Fengrui Liu, Xiao He, Tieying Zhang +6
In large-scale cloud service systems, support tickets serve as a critical mechanism for resolving customer issues and maintaining service quality. However, traditional manual ticke…
PLM4NDV: Minimizing Data Access for Number of Distinct Values Estimation with Pre-trained Language Models
Xianghong Xu, Xiao He, Tieying Zhang +3
Number of Distinct Values (NDV) estimation of a multiset/column is a basis for many data management tasks, especially within databases. Despite decades of research, most existing m…
AdaNDV: Adaptive Number of Distinct Value Estimation via Learning to Select and Fuse Estimators
Xianghong Xu, Tieying Zhang, Xiao He +8
Estimating the Number of Distinct Values (NDV) is fundamental for numerous data management tasks, especially within database applications. However, most existing works primarily fo…
VIDEX: A Disaggregated and Extensible Virtual Index for the Cloud and AI Era
Rong Kang, Shuai Wang, Tieying Zhang +6
Virtual index, also known as hypothetical indexes, play a crucial role in database query optimization. However, with the rapid advancement of cloud computing and AI-driven models f…
Flow-of-Action: SOP Enhanced LLM-Based Multi-Agent System for Root Cause Analysis
Changhua Pei, Zexin Wang, Fengrui Liu +9
In the realm of microservices architecture, the occurrence of frequent incidents necessitates the employment of Root Cause Analysis (RCA) for swift issue resolution. It is common t…
Query Performance Explanation through Large Language Model for HTAP Systems
Haibo Xiu, Li Zhang, Tieying Zhang +2
In hybrid transactional and analytical processing (HTAP) systems, users often struggle to understand why query plans from one engine (OLAP or OLTP) perform significantly slower tha…
ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning
Zhe Xie, Zeyan Li, Xiao He +6
Understanding time series is crucial for its application in real-world scenarios. Recently, large language models (LLMs) have been increasingly applied to time series tasks, levera…