Large language models for forecasting and anomaly detection: A systematic literature review
This systematic literature review comprehensively examines the application of Large
Language Models (LLMs) in forecasting and anomaly detection, highlighting the current …
Language Models (LLMs) in forecasting and anomaly detection, highlighting the current …
MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models
In large-scale cloud service systems, monitoring metric data and conducting anomaly
detection is an important way to maintain reliability and stability. However, great disparity …
detection is an important way to maintain reliability and stability. However, great disparity …
DABL: Detecting Semantic Anomalies in Business Processes Using Large Language Models
Detecting anomalies in business processes is crucial for ensuring operational success.
While many existing methods rely on statistical frequency to detect anomalies, it's important …
While many existing methods rely on statistical frequency to detect anomalies, it's important …
A Comprehensive Survey on Root Cause Analysis in (Micro) Services: Methodologies, Challenges, and Trends
T Wang, G Qi - arXiv preprint arXiv:2408.00803, 2024 - arxiv.org
The complex dependencies and propagative faults inherent in microservices, characterized
by a dense network of interconnected services, pose significant challenges in identifying the …
by a dense network of interconnected services, pose significant challenges in identifying the …
KubePlaybook: A Repository of Ansible Playbooks for Kubernetes Auto-Remediation with LLMs
In the evolving landscape of software development and system operations, the demand for
automating traditionally manual tasks has surged. Continuous operation and minimal …
automating traditionally manual tasks has surged. Continuous operation and minimal …
A Survey of AIOps for Failure Management in the Era of Large Language Models
As software systems grow increasingly intricate, Artificial Intelligence for IT Operations
(AIOps) methods have been widely used in software system failure management to ensure …
(AIOps) methods have been widely used in software system failure management to ensure …
[PDF][PDF] Don't Train, Just Prompt: Towards a Prompt Engineering Approach for a More Generative Container Orchestration Management.
N Kratzke, A Drews - CLOSER, 2024 - scitepress.org
Background: The intricate architecture of container orchestration systems like Kubernetes
relies on the critical role of declarative manifest files that serve as the blueprints for …
relies on the critical role of declarative manifest files that serve as the blueprints for …
Optimal automated generation of playbooks
Cyberattacks have become more complex and analysts need help managing all alerts
promptly. Many organizations implement Security, Orchestration, Automation, and Response …
promptly. Many organizations implement Security, Orchestration, Automation, and Response …
OpenLogParser: Unsupervised Parsing with Open-Source Large Language Models
Log parsing is a critical step that transforms unstructured log data into structured formats,
facilitating subsequent log-based analysis. Traditional syntax-based log parsers are efficient …
facilitating subsequent log-based analysis. Traditional syntax-based log parsers are efficient …
Leveraging Large Language Models for the Auto-remediation of Microservice Applications: An Experimental Study
Runtime auto-remediation is crucial for ensuring the reliability and efficiency of distributed
systems, especially within complex microservice-based applications. However, the …
systems, especially within complex microservice-based applications. However, the …