AI blog posts

From packets to prompts: Inference adds a new layer to the stack

Inference is not training. It is not experimentation. It is not a data science exercise. Inference is production runtime behavior, and it behaves like an application tier.

Compression isn’t about speed anymore, it’s about the cost of thinking

In the AI era, compression reduces the cost of thinking—not just bandwidth. Learn how prompt, output, and model compression control expenses in AI inference.

Architecting for AI: Secure, scalable, multicloud

Operationalize AI-era multicloud with F5 and Equinix. Explore scalable solutions for secure data flows, uniform policies, and governance across dynamic cloud environments.

The efficiency trap: tokens, TOON, and the real availability question

Token efficiency in AI is trending, but at what cost? Explore the balance of performance, reliability, and correctness in formats like TOON and natural-language templates.

Multicloud data replication takes a village

Secure and scale multicloud data replication for AI. Learn how F5 and Equinix enable policy-driven connectivity, governance, and seamless network control.

Programmability is the only way control survives at AI scale

Learn why data and control plane programmability are crucial for scaling and securing AI-driven systems, ensuring real-time control in a fast-changing environment.

How AI inference changes application delivery

Learn how AI inference reshapes application delivery by redefining performance, availability, and reliability, and why traditional approaches no longer suffice.

The influence of inference: APIs, DPUs, and context chaos

AI, inference, and tokens, oh my!

AI applications run on inference servers, driven by tokens—not traffic. Discover why understanding tokens and JSON data is critical to designing smarter infrastructure.

Controlling generative AI applications through context

Controlling generative AI apps means leveraging application, environmental, and business context. Learn why complete context ensures trust and adoption.

Managing context windows in AI isn’t magic. It’s architecture.

Discover why AI app builders must manage context, memory, and infrastructure while evolving delivery and security to prevent drift, latency, and prompt attacks.

Protect AI innovation on AWS with API security

Learn the five key elements of a comprehensive approach to API security that addresses discovery, authentication, and the elevated risk of AI-specific threats.

Build fast, secure data pipelines for AI training on AWS

Achieve your AI training goals more effectively by complementing your AWS infrastructure with F5 traffic management and secure multicloud networking.