AIStor on ROSA

AJ AJ on AIStor |
AIStor on ROSA

Lately, there has been a trend in the industry to bring data “closer” to home. The result is that  organizations now want to keep their data on servers that they own, in their own datacenter or at a colocation provider.

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MinIO’s S3 over RDMA Initiative: Setting New Standards in Object Storage for High-Speed AI Data Infrastructure

MinIO’s S3 over RDMA Initiative: Setting New Standards in Object Storage for High-Speed AI Data Infrastructure

As the demands of AI and machine learning continue to accelerate, data center networking is evolving rapidly to keep pace. For many enterprises, 400GbE and even 800GbE are becoming standard choices, driven by the need for high-speed, low-latency data transfer for AI workloads that are both data-intensive and time-sensitive. AI models for tasks like large language processing, real-time analytics, and

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A Redesigned Global Console for AI-Centric Workloads

AJ AJ on AIStor |
A Redesigned Global Console for AI-Centric Workloads

The MinIO Console has been an evolving product for several years now. Every time we learn, we think about how to improve this incredibly important part of our interaction framework. First came the Console, which saw massive adoption within a year of its introduction. More than 10K organizations to be more specific.Next came the enterprise Console. That moved from

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Gone [to Prod] in 60 Seconds

AJ AJ on Cloud Operating Model |
Gone [to Prod] in 60 Seconds

In this post we’ll show you how quickly you can get a production grade of MinIO cluster up and running in just a few seconds. Not only that, but we’ll also show you how you can expand that cluster quickly in just a few seconds as well.

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The MinIO DataPod: A Reference Architecture for Exascale

The MinIO DataPod: A Reference Architecture for Exascale

The modern enterprise defines itself by its data. This requires a data infrastructure for AI/ML as well as a data infrastructure that is the foundation for a Modern Datalake capable of supporting business intelligence, data analytics, and data science. This is true if they are behind, getting started or using AI for advanced insights. For the foreseeable future, this

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