AI and machine learning (AI/ML) workloads are revolutionizing how businesses operate and innovate. Kubernetes, the de facto standard for container orchestration and management, is the platform of choice for powering scalable AI/ML workloads and inference models. F5 NGINX delivers better uptime, protection, and visibility at scale for AI/ML workloads across hybrid, multi-cloud Kubernetes environments, while reducing complexity and operational cost.
Operationalize AI/ML workloads easily and reliably with adaptive load balancing, non-disruptive reconfiguration, A/B testing, and canary deployments. Reduce complexity through consistency across environments.
Improve model serving efficiency, uptime, and SLAs by resolving app connectivity issues quickly with extensive, granular metrics and dashboards using real-time and historical data.
Protect AI/ML workloads with strong security controls across distributed environments that don’t add extra complexity, overhead, or slow down release velocity or performance.
NGINX facilitates the experimentation of new models and deployment without disruption. It allows you to collect, monitor, and analyze health and performance metrics for the model, improving its efficacy and accuracy while ensuring holistic protection through strong and consistent security controls.
NGINX advanced load balancing and health monitoring features reduce downtime, ensuring your AI services are always available when needed and directly supporting stringent SLAs and uptime guarantees.

Explore how Ingress controllers and F5 NGINX Connectivity Stack for Kubernetes can help simplify and streamline model serving, experimentation, monitoring, and security for AI/ML workloads.
Read the blogA Quick Guide to Scaling AI/ML Workloads on Kubernetes ›
The Ingress Controller: Touchstone for Securing AI/ML Apps in Kubernetes ›
Compare NGINX One to NGINX Open Source ›
Securing NVIDIA NIM Inference with NGINX Ingress Controller ›
Scalable AI Deployment: Harnessing OpenVINO and NGINX Plus for Efficient Inference ›
IDC Spotlight: Enhancing AI Workload Performance with Advanced Networking Solutions ›