In this lab we will explore F5 AI Guardrails which is a runtime security platform for generative AI and agentic AI systems, focused on securing the AI inference layer—the point where models receive prompts and generate outputs.

In this lab you will explore an NVIDIA Data Flywheel running on Cisco Secure AI Factory hardware with NVIDIA in WWT's AI Proving Ground. Built on the NVIDIA NeMo microservices platform, the flywheel automatically turns production traffic into evaluation and fine-tuning datasets, LoRA fine-tunes candidate models with NeMo Customizer, scores them against the incumbent with NeMo Evaluator, and deploys the winner as an NVIDIA NIM. Using a clinical coding application as the example workload, you will watch a 1-billion-parameter model close the accuracy gap on a 70-billion-parameter model at a fraction of the inference cost.

This lab will guide and educate you on what the F5 BIG-IP Next Cloud-Native Network Functions are, how they are deployed with NVIDIA DOCA, and how they will ultimately help show the gains in offloading traffic to DPUs instead of tying up resources for your applications on the CPU of the physical K8 host.