Live presentation + demo:

GPU-ready in minutes: AI development on Azure with RLC Pro AI

April 16, 2026 | 2:00 PM ET | 60 minutes

Your local machine got you started with AI development. Now your models need more power than your laptop can deliver, and managed AI platforms feel like they're locking you in. This session shows how to move from local experimentation to Azure GPU instances.


We discuss RLC Pro AI on Azure NV-series (A10), NC-series (H100), and the newly GA RTX Pro 6000 instances, walking through real-world AI developer workflows: running Jupyter notebooks with GPU acceleration, fine-tuning a model and running it with Ollama to validate the results, and deploying a RAG-based Q&A service. CIQ and Microsoft engineers walk through the actual setup process, from Azure Marketplace deployment to running your first inference.


Whether you are an AI engineer who wants a familiar Linux environment in the cloud, an enterprise R&D team moving beyond your laptop, or a developer who finds managed AI platforms too restrictive, this session gives you a practical, tested path from local experimentation to production-ready cloud infrastructure.

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What you'll learn

  • A working deployment pattern for Azure GPU instances: A10, H100, and RTX Pro 6000
  • Confidence to move local AI projects to cloud infrastructure on your own terms
  • Understanding of which Azure GPU instance fits your workload
  • Hands-on reference for PyTorch, Hugging Face, and Ollama on Azure

Is this for you?

  • Engineering Leads and AI Platform Architects rAI/ML developers and engineers who have outgrown local development environments

  • Enterprise R&D teams needing scalable GPU compute for training and fine-tuning

  • Engineers and researchers who prefer open, Linux-native workflows over managed AI platforms

  • Teams evaluating cloud GPU options without vendor lock-in

 

Agenda preview

  • Why traditional Linux waits for patches, and how RLC-Hardened fights back
  • LKRG deep dive: runtime kernel protection that detects exploitation as it happens
  • The layered defense stack: how LKRG + hardened_malloc + hardened glibc make your foundation hostile to attackers
  • From 40+ hours to 30 minutes: automated STIG compliance in RLC-Hardened
  • Real ROI: how security-first architecture saves 1-3 FTEs annually
  • Live Q&A with our expert panel
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