jerome
b671546622
Created complete documentation structure with: • Root README.md with repository overview • Documentation directory structure (01-05 + templates) • Migrated content from public repository • New operational documentation • Comprehensive templates for business workflows Sections: 1. 01-business-strategy/ - Business vision, market analysis, financials 2. 02-technical-architecture/ - Infrastructure, AI agents, deployment 3. 03-operations/ - Client onboarding, support processes 4. 04-customer-portal/ - Placeholder for client-facing docs 5. 05-development/ - Placeholder for dev standards 6. templates/ - 5 reusable business templates This commit establishes the foundation for the repository reorganization. Content review will be conducted separately.
86 lines
2.7 KiB
Markdown
86 lines
2.7 KiB
Markdown
1|# 02 - TECHNICAL INFRASTRUCTURE — Overview
|
|
2|**Purpose:** Complete technical guide for Syslog infrastructure, GPU passthrough, and model deployment.
|
|
3|
|
|
4|## Infrastructure Components
|
|
5|
|
|
6|### **01 - Proxmox & VM Passthrough**
|
|
7|- GPU passthrough configuration (AMD/Intel)
|
|
8|- VM networking setup
|
|
9|- Resource allocation best practices
|
|
10|
|
|
11|### **02 - GPU Monitoring**
|
|
12|- Grafana dashboards for GPU telemetry
|
|
13|- ROCm monitoring setup
|
|
14|- Real-time performance tracking
|
|
15|
|
|
16|### **03 - AMD GPU Passthrough (Strix Halo)**
|
|
17|- Detailed AMD APU passthrough for host LLM access
|
|
18|- Vulkan driver configuration
|
|
19|- HIP SDK integration
|
|
20|
|
|
21|### **04 - Qwen3.5 Model Setup**
|
|
22|- Qwen3.5-MoE (Mixture of Experts) installation
|
|
23|- Vulkan backend optimization
|
|
24|- Production inference configuration
|
|
25|
|
|
26|### **05 - AWS Cloud Infrastructure**
|
|
27|- VPC and networking architecture
|
|
28|- EC2 instance configuration for AI workloads
|
|
29|- S3 data pipeline setup
|
|
30|- Cost optimization strategies
|
|
31|
|
|
32|## Deployment Standards
|
|
33|
|
|
34|- **GPU Access:** AMD Strix Halo for host inference, NVIDIA for training
|
|
35|- **Model Hosting:** Ollama local deployment @ 192.168.68.8:8080
|
|
36|- **Cloud:** AWS for scalable cloud workloads
|
|
37|- **Storage:** S3 for model weights and datasets
|
|
38|- **Monitoring:** Grafana + Prometheus for observability
|
|
39|
|
|
40|## Common Operations
|
|
41|
|
|
42|### Start Qwen3.5-MoE
|
|
43|```bash
|
|
44|ollama pull qwen3.5:250b-moe
|
|
45|ollama serve --model qwen3.5:250b-moe
|
|
46|```
|
|
47|
|
|
48|### Check GPU Status
|
|
49|```bash
|
|
50|# AMD
|
|
51|rocm-smi
|
|
52|watch -n 5 rocm-smi
|
|
53|
|
|
54|# NVIDIA
|
|
55|nvidia-smi
|
|
56|watch -n 5 nvidia-smi
|
|
57|```
|
|
58|
|
|
59|### Deploy New Agent
|
|
60|```bash
|
|
61|# Clone agent repository
|
|
62|git clone https://github.com/sysloggh/agent-template.git
|
|
63|cd agent-template
|
|
64|
|
|
65|# Configure environment
|
|
66|cp .env.example .env
|
|
67|# Edit .env with API keys and settings
|
|
68|
|
|
69|# Install dependencies
|
|
70|pip install -r requirements.txt
|
|
71|
|
|
72|# Deploy
|
|
73|source venv/bin/activate
|
|
74|python main.py
|
|
75|```
|
|
76|
|
|
77|## Related Documentation
|
|
78|
|
|
79|- [Business Strategy](../01\ -\ BUSINESS\ \&\ STRATEGY/00\ -\ Business Strategy Home.md)
|
|
80|- [AI Agents Framework](../03\ -\ AI\ AGENTS\ \&\ LEARNING/00\ -\ AI Agents Learning Home.md)
|
|
81|- [Operational Excellence](../05\ -\ OPERATIONAL\ EXCELLENCE/00\ -\ Operational Excellence Home.md)
|
|
82|
|
|
83|---
|
|
84|
|
|
85|*This section pairs implementation guides with their respective scripts for rapid deployment.*
|
|
86| |