28d • General discussion
Part 2 - A real World use of Local AI
In Part 2 of his series, I demonstrates the practical power of a local LLM-driven "AI DBA Analyst" that processed a massive 67,000-character SQL Server health report in just 12 seconds to identify three critical, interconnected performance issues. By utilizing a three-layer architecture collection, storage, and a Python-based intelligence pipeline the system successfully correlated memory pressure with log file growth and job slowdowns, providing immediate, actionable T-SQL fixes. Beyond simple analysis, I Try to highlight the AI's ability to modernize legacy database code by auditing and fixing 34 stored procedures, ultimately arguing that while AI lacks business context, it serves as an invaluable, tireless partner that allows DBAs to bypass manual data parsing and move straight to strategic resolution.
❤️🔥This is a real world solution for a real world problem solved by AI integration with legacy tools.🔥
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Part 2 - A real World use of Local AI
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