Enterprises are under mounting pressure to manage infrastructure more efficiently as AI and distributed applications drive up cost and complexity. As a result, the industry is moving toward more adaptive systems that use intelligent data placement to respond automatically as demands change. Auto-tiering is often mistaken for older hierarchical storage management, but the newer approach ...

Shadow AI is emerging as one of the most dangerous enterprise risk vectors, eclipsing the shadow IT problem that plagued the cloud era. As employees experiment with generative AI tools, organizations face mounting compliance exposure, data leakage and regulatory penalties that dwarf the consequences of unsanctioned cloud instances. The urgency is compounding as agentic AI ...

As AI accelerates both innovation and risk, cyber resilience strategy has become an urgent business imperative — how can organizations protect critical data, detect threats before they spread and recover fast enough to stay operational? The answer lies in taking a more operational approach to resilience, according to Michelle Graff (pictured, right), senior vice president ...

Companies are under pressure to move faster on AI while keeping complex infrastructure and operations under control, making enterprise platform simplification a growing priority. As a result, many organizations are looking for ways to consolidate tools and strengthen security. On one hand, companies are trying to expand massive, capital-intensive AI projects, and on the other, ...

With Kubernetes becoming the bedrock of modern enterprise infrastructure, Kubernetes virtualization seems to be the next logical step forward. In fact, KubeVirt — an open-source project that brings container-native virtualization to Kubernetes — is enabling teams to run and manage virtual machines alongside containers from a single control plane. With the release of version 1.8 ...

Enterprises want to move beyond AI experimentation, but most still struggle to bridge the gap between promising proofs of concept and production-ready cloud-native AI platforms. The challenge is compounding as AI workloads converge with cloud-native infrastructure. European services company ITQ Consultancy B.V. is tackling that challenge head-on, using an AI-powered robot dog named Q9 to ...

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 ...