Blog Archives

Can Current Storage Infrastructure Meet the AI at Scale Demand?

In our last blog we covered the challenges that AI at scale creates for storage infrastructures. To support the coming wave of AI applications, storage infrastructures need to deliver a tremendous amount of storage capacity with the ability to retain

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File Servers; Is It Time to Say Goodbye?

Unstructured data is the fastest-growing segment of data in the data center. A significant portion of data within unstructured data is the data that users create though office productivity and other specialized applications. User data also often represents the bulk

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Complexity is Killing Secondary Storage

Most organizations only use their secondary storage infrastructure as protection storage. In some cases, this is because the secondary storage hardware only supports the backup use case. Even if the organization selects more flexible secondary storage hardware, it still primarily

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Understanding the Challenges That AI at Scale Creates

Artificial Intelligence (AI) is in its infancy and the requirements it places on the storage architectures that support these workloads are not widely understood. As a result, an organization starting an AI initiative can initially get away with using an

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How to Create a Cloud File Server – LucidLink Briefing Note

Most enterprises have invested in several, if not dozens of file servers or network-attached storage (NAS) systems to distribute and share data. The cost to purchase, upgrade, and eventually replace these systems is expensive. Also, the typical user, while often

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Purpose-Built Backup for Unstructured Data

Unstructured data has grown dramatically in terms of total capacity, the number of files, and criticality to the organization. Home directories now represent the bulk of the organization’s creative output, and losing or not being able to find that data

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Is Your Storage Architecture Ready for the Coming AI Wave?

Artificial Intelligence (AI) is a broad term that can apply to various computing tasks, including machine learning, deep learning, and big data analytics. Many AI projects are in a proof of concept stage, but CIOs and IT Managers need to

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