Secure access service edge platforms are emerging as a potential answer to the growing mismatch between legacy security architectures and modern AI workloads. But closing that gap may require more than modern SASE can handle — instead calling for a true AI-native SASE platform. The SASE market is growing at a compound annual growth rate ...

The shift from conversational AI to autonomous agents is forcing a rethink of enterprise security architecture. As AI agents take on real business tasks at scale, the industry’s long-held assumptions about access control, identity and trust are no longer sufficient. Instead, agentic AI security requires a new approach. A recent Cisco Systems Inc. survey of ...

The rise of agentic AI is forcing enterprises to rethink data infrastructure from the ground up. Instead of maintaining separate systems for observability, search and AI applications, organizations are now consolidating onto unified AI data infrastructure layers that can handle the speed and complexity of autonomous workflows. That consolidation trend is accelerating around open-source platforms ...

Open source has an acute people problem. As usage accelerates — fueled in part by AI — the contributor and maintainer base supporting critical cloud-native projects remains dangerously thin, making the push for cloud-native diversity both an equity imperative and a sustainability strategy. The Cloud Native Computing Foundation’s Merge Forward initiative is working to close ...

Enterprises racing to deploy AI are discovering that the biggest barrier to success is not the technology itself but the risk it introduces, highlighting the operational resilience needed to keep the business running when things go wrong. As the cybersecurity landscape shifts toward agentic workflows, expanding attack surfaces and regulatory pressure, that concept of operational resilience ...

Cloud-native AI infrastructure is gaining ground fast in the enterprise — but what separates deployment at scale from stalled ambition? The convergence of cloud-native and AI-native computing is pushing engineers and application developers to retool existing workloads to embed agentic services at scale. The gap between an enterprise’s AI ambition and its ability to deploy governed, ...

In public health, where sensitive patient data and urgent decisions collide, cloud-native scientific computing is becoming the antidote to slow, fragmented innovation. What is at stake is not just operational efficiency, but the confidence with which public health agencies can respond to emerging threats. The challenge is particularly acute for agencies that must run complex ...

As cloud infrastructure consolidates, AI identity controls are moving to the center of how enterprises secure and manage autonomous agents. That shift is being driven by a familiar but fast-growing challenge: managing non-human actors at scale. As AI agents spread across enterprise environments, identity is emerging as a foundational layer for controlling how those systems ...

The window between vulnerability discovery and exploitation is shrinking fast, with autonomous penetration testing emerging as the only way for defenders to keep pace with AI-powered attackers. As engineering teams ship software faster than ever and attackers probe systems continuously at scale, traditional human-led penetration testing can no longer keep pace. Xbow USA Inc., an ...

As enterprises move from AI experimentation into production, some see distributed AI infrastructure as a strategic advantage rather than just a technical foundation. This shift is pushing organizations to rethink how — and where — AI runs. With AI environments becoming multi-agent and multi-model, organizations are prioritizing choice and flexibility over commitment to any single ...