Connecting and securing workloads from anywhere made easy with AI/ML
summary
Demo builds a simple microservice app with GitHub Actions publishing containers to Azure Container Registry and deploying to a Virtual Kubernetes cluster spanning three edges, then advertises it via Anycast with an XC-issued TLS certificate. The platform performs automatic API discovery and generates an OpenAPI spec, surfaces a missing “colors” endpoint and blocked shadow endpoint traffic using the API Protection rules engine. A default WAAP policy and behavioral analysis flag and mitigate multiple malicious users in real time.
AI-written summary · about
chapters (14)
- 0:00F5 Distributed Cloud intro
- 0:50Cloud app delivery challenges
- 1:55F5 Distributed Cloud solutions
- 2:39F5 Distributed Cloud infra
- 3:22Demo: Build app
- 5:10Demo: Deploy app
- 6:58Demo: Make app public
- 7:18Demo: Observe traffic
- 8:32Demo: Discover API specs
- 9:21Demo: Secure app with API protection
- 10:40Demo: Configure WAAP policies
- 11:31Demo: Analyze security insights
- 13:12Demo summary
- 13:55Resources & closing
related talks
51mUsing AI to Deploy Java apps to Kubernetes
49mProtecting API workloads OWASP Top 10
36mEnabling DevSecOps best practices with GitHub Actions
47mZero Trust DevOps with Azure & Github Actions
30mMinimum Viable Security for Cloud Native Stacks
31munlighted, but what about Security and Multi tenancy?
18mDeploying Secure Angular Apps that Scale
25mSecuring AI Pipelines: Real-World Attacks on Kubernetes-Based AI Infrastructure