Scaling AI requires a unified framework to navigate secure Next-Gen Application Delivery Controllers . For more than two decades, growing complexity has evolved the demands placed on ADCs. From hybrid and multicloud environments to AI-driven applications, a new approach is vital.
Below, you can use the F5 AI reference architecture to simplify planning for AI Web Apps, Microservices, and AI model foundry by breaking workflows into seven core blocks, providing guidance for security, traffic management, and platform optimization.
The most critical security risks in deploying and managing large language models and generative AI applications.
Key challenges in hybrid multicloud environments, offering solutions to reduce app delivery complexity.
Essential capabilities, technologies, and principles needed to overcome technical challenges for effective AI solutions.
The following architecture is designed to help you understand and plan around the risks and considerations for deploying AI applications at scale.
The future is powered by connected and distributed AI models.
Explore AI solutionsADC 3.0: Redefining the Application Delivery Controller for AI ›
Traffic Management for AI Data Ingest ›
Accelerating and Optimizing Networking for AI Factories ›
Secure Model Inference for Kubernetes ›
