Multi-DCs Operation with a LLM(3)

This diagram presents the 3 Core Expansion Strategies for Event Message-based LLM Data Center Operations System.

System Architecture Overview

Basic Structure:

• Collects event messages from various event protocols (Log, Syslog, Trap, etc.)
• 3-stage processing pipeline: Collector → Integrator → Analyst
• Final stage performs intelligent analysis using LLM and AI

3 Core Expansion Strategies

1️⃣ Data Expansion (Data Add On)

Integration of additional data sources beyond Event Messages:

• Metrics: Performance indicators and metric data
• Manuals: Operational manuals and documentation
• Configures: System settings and configuration information
• Maintenance: Maintenance history and procedural data

2️⃣ System Extension

Infrastructure scalability and flexibility enhancement:

• Scale Up/Out: Vertical/horizontal scaling for increased processing capacity
• To Cloud: Cloud environment expansion and hybrid operations

3️⃣ LLM Model Enhancement (More Better Model)

Evolution toward DC Operations Specialized LLM:

• Prompt Up: Data center operations-specialized prompt engineering
• Nice & Self LLM Model: In-house development of DC operations specialized LLM model construction and tuning

Strategic Significance

These 3 expansion strategies present a roadmap for evolving from a simple event log analysis system to an Intelligent Autonomous Operations Data Center. Particularly, through the development of in-house DC operations specialized LLM, the goal is to build an AI system that achieves domain expert-level capabilities specifically tailored for data center operations, rather than relying on generic AI tools.

With Claude