datastrophic

Publicly exposed insecure service endpoints on Kubernetes produce a major risk of malicious workloads being deployed on your clusters. We’ve seen reports of the Kubernetes Dashboard, the Kubeflow Central Dashboard, and the Kubeflow Pipelines all were compromised when publicly exposed to the Internet. Combined with wide RBAC permissions, a publicly exposed software with workload scheduling capabilities opens your clusters for malicious deployments to anybody knowing the endpoint URL. This blog post focuses on building a secure ingress and authentication stack on Kubernetes with Istio targeting Kubeflow installations.

With Kubeflow gaining traction in the community and its early adoption in enterprises, security and observability concerns become more and more important. Many organizations that are running AI/ML workloads, operate with sensitive personal or financial data and have stricter requirements for data encryption, traceability, and access control. Quite often, we can see the use of the Istio service mesh for solving these problems and gaining other benefits of the rich functionality it provides.