Category: Private AI
Guides, labs, and troubleshooting for building private, self-hosted AI on a private cloud platform.
-
Monitoring GPU Resources in a Private AI Platform: Metrics, Dashboards, and Tools
Which metrics tell you the truth about GPU health, and which tools to use to see them, with real dashboard patterns, alert thresholds, and practical habits for a private AI estate.
-
Data Sources in Private AI: Connectors and Supported File Formats
The four data source connectors in Private AI (Google Drive, Confluence, Amazon S3, SharePoint) and the file formats the platform can index for retrieval.
-
What Is in the Private AI Catalog: A Guide to the Blueprints
A plain-language field guide to every blueprint in the Private AI catalog, grouped by job: compute, model serving, RAG retrieval, OCR and speech, and the access layer.
Architect’s Toolkit
PJ’s Tools
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
You May Have Missed
DrJha