ELMo-Tune-V2 introduces a novel LLM-assisted auto-tuning framework that optimizes LSM-based key-value stores without requiring expert knowledge.

• Automates the entire tuning cycle from workload analysis to configuration optimization
• Leverages large language models to interpret performance metrics and recommend configurations
• Achieves performance improvements while reducing manual tuning effort
• Adapts dynamically to changing workload patterns

This research represents a significant advancement for engineering teams by eliminating the need for specialized knowledge in storage system optimization, potentially reducing operating costs and improving application performance across diverse workloads.

ELMo-Tune-V2: LLM-Assisted Full-Cycle Auto-Tuning to Optimize LSM-Based Key-Value Stores