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Designing Shared Storage for Hadoop, Elastic, Kafka, TensorFlow

As analytics environments like Hadoop, Elastic, Kafka and TensorFlow continue to scale, organizations need to find a way to create a shared infrastructure that can deliver the bandwidth, flexibility, and efficiency that these environments need. In a recent Storage Intensity

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Posted in Podcast

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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Posted in Blog

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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Posted in Briefing Note

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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Posted in Briefing Note

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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Posted in Blog

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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Posted in Briefing Note

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