Tigera: Calico Demo: Securing AI Workloads on Kubernetes with Calico

AI workloads, from model training to real-time inference, introduce new security challenges that traditional Kubernetes controls can’t handle. Multi-cluster pipelines, high-volume east-west traffic, and complex egress patterns make it difficult to protect sensitive model data and prevent exfiltration.

In this demo, you’ll discover how Calico delivers the visibility and control required to secure AI workloads across Kubernetes environments:

• Implement zero-trust microsegmentation to isolate training, inference, and data pipelines
• Use DNS-aware egress controls to prevent data exfiltration and protect AI model IP
• Enforce consistent multi-cluster network policies
• Gain AI-specific observability to detect abnormal traffic and potential breaches using Calico Service Graph

Join us to see how Calico simplifies AI workload security, helping platform teams protect data, models, and APIs while enabling innovation at scale.