Incremental causal graph learning for online root cause analysis
The task of root cause analysis (RCA) is to identify the root causes of system faults/failures
by analyzing system monitoring data. Efficient RCA can greatly accelerate system failure …
by analyzing system monitoring data. Efficient RCA can greatly accelerate system failure …
Root cause analysis for microservice systems via hierarchical reinforcement learning from human feedback
In microservice systems, the identification of root causes of anomalies is imperative for
service reliability and business impact. This process is typically divided into two phases:(i) …
service reliability and business impact. This process is typically divided into two phases:(i) …
Multi-task federated learning-based system anomaly detection and multi-classification for microservices architecture
J Hao, P Chen, J Chen, X Li - Future Generation Computer Systems, 2024 - Elsevier
The microservices architecture is extensively utilized in cloud-based application
development, characterized by the construction of applications through a series of …
development, characterized by the construction of applications through a series of …
Learning DAGs from data with few root causes
P Misiakos, C Wendler… - Advances in Neural …, 2024 - proceedings.neurips.cc
We present a novel perspective and algorithm for learning directed acyclic graphs (DAGs)
from data generated by a linear structural equation model (SEM). First, we show that a linear …
from data generated by a linear structural equation model (SEM). First, we show that a linear …
Active causal structure learning with advice
D Choo, T Gouleakis… - … Conference on Machine …, 2023 - proceedings.mlr.press
We introduce the problem of active causal structure learning with advice. In the typical well-
studied setting, the learning algorithm is given the essential graph for the observational …
studied setting, the learning algorithm is given the essential graph for the observational …
[HTML][HTML] A fine-grained robust performance diagnosis framework for run-time cloud applications
To maintain the required service quality of time-critical cloud applications, operators must
continuously monitor their runtime status, detect potential performance anomalies, and …
continuously monitor their runtime status, detect potential performance anomalies, and …
Root Cause Analysis in Microservice Using Neural Granger Causal Discovery
In recent years, microservices have gained widespread adoption in IT operations due to
their scalability, maintenance, and flexibility. However, it becomes challenging for site …
their scalability, maintenance, and flexibility. However, it becomes challenging for site …
MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems
Effective root cause analysis (RCA) is vital for swiftly restoring services, minimizing losses,
and ensuring the smooth operation and management of complex systems. Previous data …
and ensuring the smooth operation and management of complex systems. Previous data …
Multi-modal Causal Structure Learning and Root Cause Analysis
Effective root cause analysis (RCA) is vital for swiftly restoring services, minimizing losses,
and ensuring the smooth operation and management of complex systems. Previous data …
and ensuring the smooth operation and management of complex systems. Previous data …
iSCAN: identifying causal mechanism shifts among nonlinear additive noise models
Structural causal models (SCMs) are widely used in various disciplines to represent causal
relationships among variables in complex systems. Unfortunately, the underlying causal …
relationships among variables in complex systems. Unfortunately, the underlying causal …