How can I test my LLM cloud agents?
AIOPSLAB: A HOLISTIC FRAMEWORK TO EVALUATE AI AGENTS FOR ENABLING AUTONOMOUS CLOUDS
January 14, 2025
https://arxiv.org/pdf/2501.06706This paper introduces AIOPSLAB, a framework for evaluating AI agents designed to automate cloud operations (AgentOps). AIOPSLAB sets up realistic microservice environments, injects faults, generates workloads, and collects telemetry data, allowing developers to assess how well their AI agents can detect, diagnose, and fix problems. It provides a standardized Agent-Cloud Interface (ACI) for agent interaction and includes a library of diverse fault scenarios.
Key points for LLM-based multi-agent systems:
- Standardized evaluation: AIOPSLAB enables consistent testing and comparison of different LLM-based agents for cloud operations.
- Realistic scenarios: The framework uses realistic microservice applications and injects complex faults, going beyond simple crashes, to thoroughly challenge LLM agents.
- Interactive environment: AIOPSLAB facilitates dynamic interaction between LLM agents and the cloud environment, enabling evaluation in dynamic, evolving scenarios.
- Observability: The framework collects comprehensive telemetry data (logs, metrics, traces), valuable for analysis and debugging of LLM agent behavior.
- Task-oriented fault library: AIOPSLAB includes a library of faults designed to test LLM agents across different operational tasks, such as detection, localization, root cause analysis, and mitigation.
- ACI: The Agent-Cloud Interface simplifies interaction by offering a concise set of APIs, streamlining LLM agent development and focusing evaluation on decision-making.
- Extensibility: AIOPSLAB can be extended with new cloud services, fault types, and evaluation metrics, supporting ongoing research and development.