Use cases
Use cases overview
From securing applications and APIs to optimizing performance, scaling infrastructure, and enabling AI initiatives, F5 use cases demonstrate real-world approaches to solving today's most critical technology challenges. Filter by solution area to discover the use cases most relevant to your business goals.
All use cases
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Networking for Kubernetes
Standardize Kubernetes networking, support AI inference workloads, and scale securely without operational overhead.Get more sellable tokens from every GPU
AI-native inference companies earn on tokens per GPU hour, and request routing decides how many tokens each GPU producesRun your AI factory on infrastructure you control
Enterprises running AI on their own GPUs need data delivery, inference routing, separation between teams, and runtime security on one platform.Virtual patching is your first line of defense
Frontier AI can turn vulnerabilities into working exploits before they can be disclosed. With F5, enterprises leverage virtual patching to block exploits at runtime, buying time to build, test, and deploy patches.Bot management
Protect your apps and APIs from bots and malicious automation while maintaining engagement that drives your business.Full lifecycle API security
Leave no API Behind: ensure continuous protection for the fabric underlying your digital business.Hybrid multicloud application delivery
F5 enables you to secure, deliver, and optimize applications across hybrid and multicloud environments.Multicloud networking solutions and services
Securely connect distributed networks and apps across public clouds, on-premises data centers, and remote sites.AI data delivery for S3-compatible storage solutions
F5 accelerates secure AI data pipelines, ensuring storage, networking, and data delivery keep AI clusters fully utilized across hybrid and multicloud deployments.AI runtime security solutions
Secure AI applications, models, agents, and connected data with runtime protections and continuous testing. Detect, prevent, and outpace evolving risks across the AI attack surface.
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