Lab

Securing AI/ML Workloads with Isovalent Enterprise

Learn how to secure AI/ML workloads using Isovalent Enterprise with Tetragon runtime security capabilities.

Learn how to deploy and manage AI/ML workloads on Kubernetes using Cilium for advanced networking, load balancing, security, and observability. This comprehensive hands-on lab covers ML model training, inference deployment, security monitoring with Tetragon, and API security with network policies.

  • 🚀 Setting up the Environment

    Set up a Kubernetes cluster with Cilium networking for AI/ML workloads

  • 🧠 Training the Neural Network

    Deploy and run neural network training on Kubernetes with Cilium networking

  • 🔮 Deploying ML Inference API

    Deploy ML inference API with L2 LoadBalancer, interactive UI, and Layer 7 observability

  • 🚨 Data Poisoning Detection with Tetragon

    Use Cilium Tetragon to detect and investigate ML data poisoning attacks

  • 🛡️ Secure ML Data with WireGuard Encryption

    Enable WireGuard encryption to protect ML data in transit after detecting poisoning

  • 🛡️ Final Exam: Prevent AI YAML Injection with Tetragon

    Secure AI applications against YAML deserialization attacks using eBPF-based runtime protection