Author: Dr. Pranay Jha
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Harbor for Beginners, Part 1: Getting Started
A friendly first tour of the Harbor registry for people from a VMware background. What Harbor is, how to read the Projects page, and what each screen does, with nothing changed and nothing to break.
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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.
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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.
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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.
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VCF 9.x Pre-Installation Checklist: What to Verify Before You Start the VCF Installer
A pre-check list for a fresh VMware Cloud Foundation 9.x management domain deployment (9.0 and 9.1), with the command to run for each item plus MTU-per-traffic and password requirement tables.
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Running NVIDIA AI On-Prem and on VCF: Cost, Trade-offs and the Verdict (NVIDIA AI Series, Part 30)
The finale: running the NVIDIA AI stack on bare metal, on VMware Cloud Foundation, or in the cloud; the real total cost of an AI factory; and the verdict on when to build versus rent.
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GPU Observability and Multi-Tenancy: DCGM, Honest Utilization, and Sharing (NVIDIA AI Series, Part 29)
Why GPU utilization lies, the DCGM profiling fields that tell the truth (SM and Tensor activity), dcgm-exporter into Prometheus, and choosing MIG vs time-slicing for multi-tenancy.
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NVIDIA Blueprints and Agentic AI: AI-Q and the NeMo Agent Toolkit (NVIDIA AI Series, Part 28)
NVIDIA Blueprints, the AI-Q enterprise research agent, and the framework-agnostic NeMo Agent Toolkit: how to build agents you can profile, afford, and trust in production.
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NVIDIA NeMo Framework: Training and Fine-Tuning at Scale (NVIDIA AI Series, Part 22)
What the NVIDIA NeMo framework is: Megatron-Core parallelism, NeMo 2.0 Python recipes and NeMo-Run, Megatron Bridge for Hugging Face interop, and when to fine-tune instead of pretrain.
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NVIDIA NeMo Retriever: RAG with Embeddings, Reranking and Guardrails (NVIDIA AI Series, Part 27)
How NVIDIA’s NeMo Retriever builds enterprise RAG: extraction, embedding and reranking NIMs, the open Nemotron Retriever models, and NeMo Guardrails, plus the retrieval failures they quietly fix.
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NVIDIA Nemotron Foundation Models: Open Weights from Nano to Ultra (NVIDIA AI Series, Part 26)
NVIDIA’s Nemotron family explained: genuinely open weights, data and recipes; the hybrid Mamba-Transformer MoE architecture; Nano, Super and Ultra; and when to self-host open models instead of calling a proprietary API.
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.
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