Ilya Krutov

Explore strategic advantages of securing AI/ML applications at the Ingress Controller layer in a Kubernetes environment.

Learn how to simplify and streamline model serving, experimentation, monitoring, and security for AI/ML workloads using Ingress controllers and F5 NGINX Connectivity Stack for Kubernetes.

Discover how to efficiently scale AI/ML models on Kubernetes and achieve high-performance adaptability across hybrid, multi-cloud environments.

Learn about the first major release of NGINX Gateway Fabric, our Kubernetes Gateway API implementation built on the NGINX data plane, and how it enables extensibility, reduces complexity, and more.

When new CVEs are reported, it’s easy to become confused by their applicability to a particular NGINX Ingress controller tool because there are multiple projects out there. This blog discusses the CVEs and how to distinguish between different Ingress controller projects to clear the confusion.

We discuss how NGINX’s unified approach to application connectivity in Kubernetes and customer-centric solutions can help simplify your cloud environments, now and into the future.

Protect your users, distributed applications, microservices, and APIs at scale and end-to-end across any environment – on-premises, hybrid, and multi-cloud.

NGINX Kubernetes Gateway, our implementation of the Kubernetes Gateway API, enables multiple teams to manage Kubernetes infrastructure in modern app environments. It delivers many capabilities natively that with an Ingress controller require CRDs.