This repository is a curated collection of academic research and industrial materials focused on the application of Large Language Models (LLMs) within Artificial Intelligence for IT Operations (AIOps).
The list covers several primary domains including:
- Incident management, such as root cause analysis, reporting, mitigation, and postmortem analysis.
- Log analysis tasks like parsing, anomaly detection, and logging statement generation.
- Infrastructure management involving benchmarks, vision, infrastructure-as-code, and training platforms.
The list covers several primary domains including:
- Incident management, such as root cause analysis, reporting, mitigation, and postmortem analysis.
- Log analysis tasks like parsing, anomaly detection, and logging statement generation.
- Infrastructure management involving benchmarks, vision, infrastructure-as-code, and training platforms.
Google explores the transition from traditional deterministic automation to agentic AI within Site Reliability Engineering. As system complexity grows due to microservices, cloud scale, and increased code generation, Google is implementing SRE AI across the entire software development lifecycle to enhance reliability. The approach includes using agents for automated runbook improvement, advanced anomaly detection, incident management orchestration, and autonomous investigation utilizing observability data.
- Moving from deterministic automation to agentic AI models
- Integration of AI in reliability design and documentation
- Using anomaly detection rather than static thresholds for alerting
- Orchestrating incident response via communication monitoring and automated summaries
- Leveraging historical data through AI Insights for risk management
- Adhering to principles of transparency, security, and agent identity
- Moving from deterministic automation to agentic AI models
- Integration of AI in reliability design and documentation
- Using anomaly detection rather than static thresholds for alerting
- Orchestrating incident response via communication monitoring and automated summaries
- Leveraging historical data through AI Insights for risk management
- Adhering to principles of transparency, security, and agent identity
This article examines the development of Microsoft’s Azure SRE Agent, designed to mitigate operational toil in mission-critical environments. By utilizing an "agentic workflow" of specialized AI agents, Microsoft has integrated automation across the entire software development lifecycle. This human-AI partnership has autonomously resolved over 35,000 incidents and saved more than 50,000 developer hours, accelerating root cause analysis and mitigation while maintaining rigorous governance and human oversight.
A study by ClickHouse found that large language models (LLMs) aren't currently capable of replacing Site Reliability Engineers (SREs) for incident root cause analysis, despite advancements in AI. LLMs can be helpful tools, but require human oversight.
This article explains what BigPanda is, its use cases, features, architecture, installation, and provides basic tutorials. BigPanda is an AI-powered platform for incident management and automation within AIOps, helping businesses streamline incident detection, resolution, and prevention.
