~/talk

Forget Kubectl and Talk to Your Clusters: Using LLMs to Simplify Kubernetes Cluster...

name:Qian Ding
links:none on file
slides:none on file

A prototype converts natural-language intents into deterministic API calls by fine-tuning local LLMs on 40,000 example pairs to extract entities and map to actions (initial models include internal GB/D variants), replaces basic "kubectl get" workflows, and adds a SQL cache layer that turns watched Kubernetes resources into queryable tables plus a federation layer across clusters. Results: high NER and intent accuracy but persistent hallucination and long-context limits (≈4,000-token requests); deployed as read‑only with human verification.

AI-written summary · about

  1. 0:00LLMs for Kubernetes
  2. 2:50Motivations for LLM approach
  3. 6:23Goals and requirements
  4. 10:39First API experiment
  5. 16:15User constraints challenges
  6. 20:49LLM YAML testing
  7. 23:57SQL and caching solution
  8. 26:06Achievements and limitations
  9. 29:00Lessons learned and future
  10. 31:29Q&A
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