F5 announced early access of F5 AI Gateway to streamline interactions between applications, APIs, and large language models (LLMs) driving enterprise AI adoption.
This containerized solution optimizes performance, observability, and protection capabilities—all leading to reduced costs. Integrated with F5’s portfolio, AI Gateway gives security and operations teams a seamless path to adopting AI services through significantly improved data output quality and a superior user experience.
“LLMs are unlocking new levels of productivity and enhanced user experiences for customers, but they also require oversight, deep inspection at inference-time, and defense against new types of threats,” said Kunal Anand, Chief Innovation Officer at F5. “By addressing these new requirements and integrating with F5’s trusted solutions for API traffic management, we’re enabling customers to confidently and efficiently deploy AI-powered applications in a massively larger threat landscape.”
F5 AI Gateway observes, optimizes, and secures a vast number of user and automated variables to offer cost reductions, mitigate malicious threats, and ensure regulatory compliance.
F5 AI Gateway is designed to meet customers—and their apps—at the ideal place in their AI journey. It can be deployed in any cloud or data center and will natively integrate with F5’s NGINX and BIG-IP platforms to take advantage of F5’s leading app security and delivery services in traditional, multicloud, or edge deployments. In addition, the solution’s open extensibility enables organizations to develop and customize programmable security and controls enforced by F5 AI Gateway. These processes can be easily updated and applied dynamically to drive instant adherence to security policies and compliance mandates.
F5 AI Gateway:
- Delivers security and compliance policy enforcement with automated detection and remediation against the risks identified in the OWASP Top Ten for LLM Applications.
- Offloads duplicate tasks from LLMs with semantic caching, enhancing the user experience and reducing operations costs.
- Streamlines integration processes, allowing developers to focus on building out AI-powered applications rather than managing complex infrastructures.
- Optimizes load balancing, traffic routing, and rate limiting for local and third-party LLMs to maintain service availability and enhance performance.
- Provides a single API interface that developers can use to access their AI model of choice.
The Latest
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...
Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...
Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...