{
  "id": 15754933,
  "title": "How going dual-native means VM/container co-existence and sovereign security in the AI era",
  "url": "https://urgent.news/2026/10/20/how-going-dual-native-means-vm-container-co-existence-and-sovereign",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-20T15:00:00.000Z",
  "source": {
    "name": "The Register Science",
    "slug": "the-register-science",
    "url": "https://www.theregister.com/ai-and-ml/2026/10/20/sponsored-how-going-dual-native-means-vm/container-co-existence-and-sovereign-security-in-the-ai-era/5303862"
  },
  "original_language": "en",
  "account": "The growing adoption of artificial intelligence (AI) has led to a growing divide between virtual machines (VMs) and containers within enterprise computing environments. As companies transition critical business applications to containers, they continue to run existing data and applications on VMs, leading to a number of operational challenges.\n\nSeparately managed VM and container environments result in inefficiencies such as duplicate capacity planning, separate support contracts, and fragmented governance processes. This fragmentation can also lead to stranded capacity, where installed computing resources are left unused, and overprovisioned container pools that cannot share resources without manual intervention.\n\nThe complexity of the VM-container divide is further compounded by the diverse application landscape that many organizations now face. Alongside traditional VM-based applications, enterprises often operate containerized apps, distributed AI workloads, and intelligent agents across private clouds, public clouds, and edge locations. Each environment has its own management tools, operational processes, security rules, and governance models, making it difficult to maintain a consistent operational model.\n\nHowever, the solution to this challenge lies in adopting a unified operating model that allows for the seamless operation of AI workloads across both VM and container environments. This is where Nutanix's dual-native architecture comes into play, offering enterprises a consistent operating model to operationalize agentic AI across container-based inference and agent workloads, alongside existing VM-based applications and data.\n\nAlthough the trend of migrating from VMs to containers is slow, many enterprises are not starting from scratch with containers. Instead, they are prolonging their VM investment while building container-based applications on top of legacy architectures. Nutanix's dual-native approach enables enterprises to retain their existing investments while efficiently operating AI workloads across the heterogeneous computing landscape.",
  "summary": "SPONSORED FEATURE: Nutanix says running VMs and containers within the same operating environment shouldn’t be a brake on AI ambitions",
  "key_points": [
    "Enterprises face operational challenges with separate VM and container environments.",
    "Nutanix's dual-native architecture enables seamless AI workload operation across VMs and containers.",
    "Dual-native approach allows retention of existing VM investments while operating AI workloads."
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 2,
    "also_reported_by": [
      {
        "outlet": "The Register",
        "title": "How going dual-native means VM/container co-existence and sovereign security in the AI era",
        "url": "https://urgent.news/2026/10/20/how-going-dual-native-means-vm-container-co-existence-and-sovereign-15756417",
        "published": "2026-10-20T15:00:00.000Z"
      }
    ]
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}