Summary of The Vision Of Autonomic Computing: Can Llms Make It a Reality?, by Zhiyang Zhang et al.
The Vision of Autonomic Computing: Can LLMs Make It a Reality?
by Zhiyang Zhang, Fangkai Yang, Xiaoting Qin, Jue Zhang, Qingwei Lin, Gong Cheng, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
First submitted to arxiv on: 19 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Distributed, Parallel, and Cluster Computing (cs.DC); Multiagent Systems (cs.MA); Software Engineering (cs.SE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed Vision of Autonomic Computing (ACV) aims to create computing systems that self-manage, adapting to changing environments like biological organisms. Despite decades of research, achieving ACV remains challenging due to the dynamic and complex nature of modern computing systems. Recent advancements in Large Language Models (LLMs) offer promising solutions by leveraging their knowledge, language understanding, and task automation capabilities. This paper explores realizing ACV through an LLM-based multi-agent framework for microservice management. A five-level taxonomy is introduced for autonomous service maintenance, and an online evaluation benchmark based on the Sock Shop microservice demo project assesses the framework’s performance. The findings demonstrate significant progress towards achieving Level 3 autonomy, highlighting the effectiveness of LLMs in detecting and resolving issues within microservice architectures. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper explores how Large Language Models (LLMs) can help make computers more self-managing, like living things. Computers are getting more complex and need to be able to adapt to changing conditions. The authors tested an idea for making this happen using LLMs and found it works well for managing small parts of a computer system. |
Keywords
» Artificial intelligence » Language understanding
