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AI infrastructure introduces a new class of risk: interdependent data, models, identities, and pipelines can fail out of sync, leaving systems operational but no longer trustworthy. At the same time, a growing CIO/CISO disconnect is creating unclear ownership and slowing response when trust is lost. In this session, Commvault will show how to close that gap with a shared control plane approach: governing access, protecting the full AI stack, and recovering systems to a clean, coherent, and trusted state.
Commvault addresses these challenges by enabling the discovery and protection of entire AI applications as holistic entities, rather than individual workloads. Their Azure Discovery module, for example, identifies all resources that comprise an AI application (e.g., front end, vector database, AKS, data lake) and enables policy-based protection using rules or tags, ensuring consistent and scalable management. A critical component is the “Clean Room” feature, which creates isolated, ephemeral environments for continuous testing of recovery and patching processes. This allows organizations to build muscle memory for trusted recovery and test vulnerability fixes or compensating controls without impacting production. The core “run book” orchestrates these processes by defining foundational and custom steps, enabling recoveries to specific points in time, integrating threat scans, and offering full customization for scenarios such as patching or disaster recovery.
The presentation also highlights Commvault’s “ResOps” (Resilience Operations) framework, emphasizing that achieving resilience in AI infrastructure requires a concerted effort across people, processes, and tools. Commvault integrates its own AI assistant, Arlie, throughout its interface to enhance operational excellence. Arlie synthesizes insights, provides root cause analysis, offers advisory recommendations (e.g., for protection gaps), and guides users through complex recovery decisions to ensure the cleanest possible restoration, leveraging metadata and threat signals. Furthermore, Commvault’s platform (MCP) can interface with external large language model harnesses such as Claude or Copilot, enabling users to manage infrastructure deployment and Commvault protection policies seamlessly through these tools, effectively creating a “headless” operational experience. This comprehensive approach ensures that AI data, models, identities, and infrastructure are protected, access is governed, and recovery is consistently clean and trusted.
Personnel: Michael Fasulo
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