Enabling Secure, High-performance Infrastructure for AI and LLM Environments

Artificial Intelligence has been part of the technology landscape for decades, but recent developments in GPU processing power have accelerated its evolution and adoption at an unprecedented rate. Generative AI (GenAI) and large language models (LLMs) are now at the forefront of this transformation, redefining how organizations operate, innovate, and serve their customers. These technologies are no longer experimental—they are being deployed in production environments to deliver real-time experiences, automate operations, and unlock new levels of efficiency.

Yet, as organizations embrace AI, they are also encountering new and complex challenges. The very capabilities that make AI powerful—its ability to learn, adapt, and generate—also make it vulnerable. The attack surface is expanding. Threats are becoming more sophisticated. Traditional cybersecurity tools are no longer sufficient. And the infrastructure required to support AI workloads is demanding, both in terms of performance and operational complexity.

A10 is not an AI company. We don’t build AI models or train neural networks. But we do understand what it takes to deliver secure, high-performance digital infrastructure. For more than 20 years, we have helped organizations around the world ensure the availability, security, and efficiency of their applications and networks. Today, we are applying that same expertise to help customers build AI-ready environments that are resilient, responsive, and secure.

As AI becomes more deeply embedded in enterprise and service provider operations, we believe customers will face three primary challenges:

1. Latency is a critical factor in AI and LLM inference environments. Users expect real-time responses from AI and LLM systems, whether they are interacting with a chatbot, querying a knowledge base, or receiving automated recommendations. Any delay in processing can degrade the user experience and diminish the value of the AI application. High-performance networking and low-latency data paths are essential to meet these expectations.
2. Security is a major concern. AI models are often trained on sensitive internal data, including proprietary business information, customer records, and intellectual property. This makes them attractive targets for cyber attackers. Moreover, the nature of AI introduces new types of threats—such as prompt injection, model poisoning, and adversarial manipulation—that traditional security tools are not equipped to detect or mitigate. As a result, organizations must adopt new approaches to safeguard their AI assets and prevent data leakage, model corruption, and regulatory violations.
3. Operational complexity is the third challenge. AI infrastructure is not simply an extension of traditional IT—it introduces new workloads, new performance requirements, and new architectural considerations. Many IT teams are still learning how to manage GPU-intensive applications, optimize data flows, and monitor AI-specific performance metrics. Without the right tools and insights, it can be difficult to ensure that AI deployments are scalable, reliable, and cost-effective.

As AI becomes more deeply embedded in enterprise and service provider operations, we believe customers will face three primary challenges:

• Delivering real-time experience with AI and LLM inference environments. A10 enables high performance for AI and LLM inference environments. We do this by offloading processor intensive tasks like TLS and SSL decryption, caching, optimizing traffic routing.
• Providing actionable insights and predicting issues before they happen. This enables customers to maximize network availability and performance.
• Preventing, detecting and mitigating threats to AI and LLM environments. We do this by enabling customers to test their AI inference model against known vulnerabilities and helping remove them using A10’s proprietary LLM safeguarding techniques. We detect AI-level threats like prompt injections and sensitive information disclosure by inspecting request and response traffic at the prompt level and enforcing security policies required for mitigating these threats at the edge.

A10 recently announced new capabilities designed to support AI-ready applications and infrastructure. These capabilities, currently in the alpha stage, are being demonstrated at Interop Tokyo 2025 and are being showcased as part of our ongoing collaboration with customers and partners.

The first of these capabilities is an AI firewall. This solution is designed to protect AI and LLM inference environments from a range of emerging threats. It runs on a GPU-enabled A10 appliance and provides comprehensive protection against prompt injection, data and model poisoning, and other AI-specific vulnerabilities. In addition, it includes a testing workflow for security operations center (SOC) red teams, allowing them to simulate attacks, identify weaknesses, and remediate issues using A10’s proprietary LLM safeguarding techniques. This proactive approach helps organizations ensure the integrity and reliability of their AI models before they are deployed in production. It can be deployed in any infrastructure as an incremental security capability.

The second capability is predictive performance insights, an early warning system for performance degradation and network capacity issues. Also running on a GPU-enabled A10 appliance, this solution leverages advanced analytics to detect performance degradation before it impacts users. It provides actionable insights that enable IT teams to proactively address bottlenecks, allocate resources more effectively, and maintain the high-speed environment that AI workloads require. Predictive performance insights are designed to work seamlessly with existing A10 products, including A10 Thunder ADC and A10 Thunder CGN, providing a unified platform for performance optimization and infrastructure resilience.

These capabilities are tailored to meet the unique demands of AI environments. They reflect our commitment to innovation and our deep understanding of the evolving technology landscape. As these capabilities mature, we will continue to engage with customers, gather feedback, and refine our approach to ensure that we are delivering meaningful value.

For customers who are interested in learning more about our AI firewall or predictive performance capabilities, we encourage them to engage directly with our product management and engineering teams. These conversations are critical to ensuring that our solutions align with real-world needs and use cases. We are also making external resources available on our website, including our point of view on AI, our infrastructure solution page, and our security solution page.

As these capabilities progress through development, we will provide updates on timelines, availability, and customer engagement opportunities.

AI is transforming the way organizations operate, but it also introduces new risks and complexities. We are focused on helping our customers navigate this transformation with confidence. By delivering secure, high-performance infrastructure solutions, we are enabling the next generation of AI applications to be faster, safer, and more effective.

We look forward to continuing this journey with our customers and partners, and to playing a vital role in shaping the future of AI infrastructure.

*** This is a Security Bloggers Network syndicated blog from A10 Networks Blog: Cyber Security authored by A10 Networks. Read the original post at: https://www.a10networks.com/blog/enabling-secure-high-performance-infrastructure-for-ai-and-llm-environments/