Virtual CMTS (vCMTS) revolutionizes bandwidth management by virtualizing DOCSIS processing on x86 servers, paving the way for DOCSIS 4.0. Intel's Xeon 6 processors enhance encryption efficiency, while Red Hat's OpenShift Cloud Platform unifies workload management. This lab explores a deployment of vCMTS on OpenShift, showcasing performance insights via Grafana.

AI has taken center stage in the automation landscape, transforming how we develop and manage infrastructure. In this hands-on lab, you'll explore how to harness the innovative capabilities of Red Hat Ansible Lightspeed with IBM watsonx Code Assistant—a powerful generative AI service designed to accelerate your Ansible content creation and maintenance. Guided step-by-step, you'll set up and utilize this service within your local development environment using Visual Studio Code, empowering you to automate faster and smarter.

Red Hat OpenShift AI, formerly known as Red Hat OpenShift Data Science, is a platform designed to streamline the process of building and deploying machine learning (ML) models. It caters to both data scientists and developers by providing a collaborative environment for the entire lifecycle of AI/ML projects, from experimentation to production. In this lab, you will explore the features of OpenShift AI by building and deploying a fraud detection model. This environment is built ontop of Dell R660's and Intel Xeon's 5th generation processors.

This lab focuses on implementing live person tracking using Intel's OpenVINO™, a toolkit for high-performance deep learning inference. The objective is to read frames from a video sequence, detect people within the frames, assign unique identifiers to each person, and track them as they move across frames. The tracking algorithm utilized here is Deep SORT (Simple Online and Realtime Tracking), an extension of SORT that incorporates appearance information along with motion for improved tracking accuracy.

In this hands-on lab, learners will explore how to build and configure a data-driven automation workflow using Ansible Automation Platform and NetBox. The lab guides users through practical exercises that demonstrate how real-time source of truth changes can trigger automated configuration. Participants will configure NetBox event rules and webhooks to emit actionable events, set up Event-Driven Ansible event streams to receive and process those events, and create rulebook activations that respond intelligently. By the end of the lab, learners will have a working solution that tightly integrates their source of truth with automation workflows—enabling scalable, responsive infrastructure management.

Learn to automate Pure FlashArray on Purity using Ansible. This lab provides an overview of Ansible and dives into how it works together to simplify automation for Pure Storage solutions.

This lab will provide access to an Openshift cluster running the F5 AI Gateway solution. We will walk through how the F5 AI Gateway routes requests to different models by either allowing them to pass through or, more importantly, securing them via prompt injection checking. We have also added a couple of other tests that will allow for language detection of that input that the F5 AI Gateway can also detect.

This lab will provide access to an Openshift cluster running the F5 AI Gateway solution. We will walk through how the F5 AI Gateway routes requests to different models by either allowing them to pass through or, more importantly, securing them via prompt injection checking. We have also added a couple of other tests that will allow for language detection of that input that the F5 AI Gateway can also detect.

If you are familiar with Ansible and want to learn how to use Ansible with the Pure Storage FlashArray, continue on with this lab that demonstrates how to simplify automation of a Pure Storage FlashArray. *** If you are a Storage admin, new to automation, and want to learn how to automate your Pure Storage environment using Ansible, check out this lab instead that teaches the basics of Ansible from a storage admin point of view.- "Ansible Automation Workshop - Pure Ansible Lab" (https://www.wwt.com/lab/ansible-automation-workshop-pure-ansible-lab)

NVIDIA Blueprints: PDF Ingestion, also known as NVIDIA-Ingest, or NV-Ingest, this blueprint is a scalable, performance-oriented document content and metadata extraction microservice. Including support for parsing PDFs, Word and PowerPoint documents, it uses specialized NVIDIA NIM microservices to find, contextualize, and extract text, tables, charts and images for use in downstream generative applications.