Modern microservice systems have gained widespread adoption due to their high
scalability, flexibility, and extensibility. However, the characteristics of independent …

Microservices architecture improves software scalability, resilience, and agility but also
poses significant challenges to system reliability due to their complexity and dynamic nature …

Automated incident management is critical for large-scale microservice systems, including
tasks such as anomaly detection (AD), failure triage (FT), and root cause localization (RCL) …

Many failure root cause analysis (RCA) algorithms for microservices have been proposed
with the widespread adoption of microservices systems. Existing algorithms generally focus …

This study demonstrates the salient facts and challenges of host failure operations in
hyperscale data centers. A host incident can involve hundreds of distinct host-level metrics …

With the development of cloud-native technologies, microservice-based software systems
face challenges in accurately localizing root causes when failures occur. Additionally, the …

Microservice-based systems often suffer from reliability issues due to their intricate
interactions and expanding scale. With the rapid growth of observability techniques, various …

Root cause localization in microservice systems refers to finding the root cause that causes
system anomalies using system information. Many methods construct a graph structure and …

Microservice systems are inherently complex and prone to failures, which can significantly
impact user experience. Existing diagnostic approaches based on single-modal data such …

AIOps algorithms play a crucial role in the maintenance of microservice systems. Many
previous benchmarks' performance leaderboard provides valuable guidance for selecting …