See why the public sector relies on F5 to secure its apps from increasingly sophisticated cyberattacks—while delivering the performance constituents demand.
Three AI deployment patterns are emerging, each with their own operational responsibilities and trade-offs. The choice of model and deployment pattern should be strategic while acknowledging the fast-evolving landscape of generative AI for enterprises.
The F5 Pride EIG builds community and advocates for the company’s LGBTQ+ employees, and seeks broader impact by extending allyship to employees’ family and friends.
AI applications are modern apps, but they do have differences. Learn the key things to know when it comes to AI-powered applications.
Don't let GPU resources sit idle, build out scalable and secure AI compute complexes with the right hardware that lets inferencing inference.
Explore how to transform an OpenAPI schema definition into a fully functioning NGINX configuration running as an API Gateway with Web Application Firewall security and a Developer Portal using a declarative API approach.
To support the full AI life cycle, organizations will require significant updates in their architecture—specifically changes in the network. Failure to do so may lead to the inability scale and unreliable operations.
NGINX One is the next phase of our journey and an effort to make all NGINX products easier to configure, secure, scale and manage.
Explore F5's 'State of AI Application Strategy', focusing on enterprise AI adoption, security concerns, technology stack, and model management practices.
AI inference services enable AI access for developers, and can be consumed in a variety of ways. Key patterns include SaaS, Cloud Managed, and Self-Managed, each with unique trade-offs in scalability, cost, and data control.