Explore the AI reference architecture
Simplify and scale AI deployments with best practices, security insights, and tools for hybrid multicloud innovation.
Understanding scalable AI deployments
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.
AI architecture components
OWASP LLM Top 10
The most critical security risks in deploying and managing large language models and generative AI applications.
App Delivery Top 10
Key challenges in hybrid multicloud environments, offering solutions to reduce app delivery complexity.
Design Requirements
Essential capabilities, technologies, and principles needed to overcome technical challenges for effective AI solutions.
AI reference architecture
The following architecture is designed to help you understand and plan around the risks and considerations for deploying AI applications at scale.
Resources
Featured
The future is powered by connected and distributed AI models.
Scale your AI: Optimize training data throughput
Manage your AI: Simplify inference data management
Secure your AI: Protect AI models and data
Speak to an AI expert
Speak to an AI expert
If you have questions regarding AI application deployments, F5 can help. Fill out this form and an F5 business development representative will be in contact to schedule time with your F5 technical account team and an AI global solution architect.