Related papers: A Comprehensive Survey on Root Cause Analysis in (…
The dramatic development of cloud and edge computing allows for better Quality of Service (QoS) in many scenarios by deploying services on cloud and edge servers. Microservice technology is also adopted in these scenarios to decompose…
Resource management for cloud-native microservices has attracted a lot of recent attention. Previous work has shown that machine learning (ML)-driven approaches outperform traditional techniques, such as autoscaling, in terms of both SLA…
As multi-agent AI systems are increasingly deployed in real-world settings - from automated customer support to DevOps remediation - failures become harder to diagnose due to cascading effects, hidden dependencies, and long execution…
To ensure the reliability of cloud systems, their performance is monitored using KPIs (key performance indicators). When issues arise, root cause localization identifies KPIs responsible for service degradation, aiding in quick diagnosis…
Microservice architectures provide an intuitive promise of high maintainability and evolvability due to loose coupling. However, these quality attributes are notably vulnerable to technical debt (TD). Few studies address TD in microservice…
The increasing complexity and usage of cloud systems have made it challenging for service providers to ensure reliability. This paper highlights two main challenges, namely internal and external factors, that affect the reliability of cloud…
Microservices fuel cloud-native systems with small service sets developed and deployed independently. The independent nature of this modular architecture also leads to challenges and gaps. The intended system design might deviate far from…
Microservices are a popular architectural style adopted by the industry when it comes to deploying software that requires scalability, maintainability, and agile development. There is an increasing demand for improving the sustainability of…
Building sound and precise static call graphs for real-world JavaScript applications poses an enormous challenge, due to many hard-to-analyze language features. Further, the relative importance of these features may vary depending on the…
The study assesses the impact of cloud-based microservices architectures on application performance. Several aspects of performance evaluation are discussed, including response time, throughput, scalability, and reliability. This article…
Capturing the workload of a database and replaying this workload for a new version of the database can be an effective approach for regression testing. However, false positive errors caused by many factors such as data privacy limitations,…
Large-scale monitoring, anomaly detection, and root cause analysis of metrics are essential requirements of the internet-services industry. To address the need to continuously monitor millions of metrics, many anomaly detection approaches…
With the evolution of microservice applications, the underlying architectures have become increasingly complex compared to their monolith counterparts. This mainly brings in the challenge of observability. By providing a deeper…
Unresolved production cloud incidents cost an average of over $2M per hour. This paper introduces PRAXIS, an orchestrator that manages and deploys an agentic workflow for diagnosing code- and configuration-caused cloud incidents. PRAXIS…
Implementing large language models (LLMs)-driven root cause analysis (RCA) in cloud-native systems has become a key topic of modern software operations and maintenance. However, existing LLM-based approaches face three key challenges:…
Software errors and incidents are inevitable in web based applications. Scalability challenges, increasing demand, and ongoing code changes can contribute to such failures. As software architectures evolve rapidly, understanding how and why…
[Context] Coupling is a widely discussed metric by software engineers while developing complex software systems, often referred to as a crucial factor and symptom of a poor or good design. Nevertheless, measuring the logical coupling among…
This study addresses the problem of anomaly detection and root cause tracing in microservice architectures and proposes a unified framework that combines graph neural networks with temporal modeling. The microservice call chain is…
Autoscaling functions provide the foundation for achieving elasticity in the modern cloud computing paradigm. It enables dynamic provisioning or de-provisioning resources for cloud software services and applications without human…
While Microservices promise several beneficial characteristics for sustainable long-term software evolution, little empirical research covers what concrete activities industry applies for the evolvability assurance of Microservices and how…