Enterprises are moving AI and analytics workloads off public clouds to cut costs and regain control without sacrificing performance. Cloud repatriation brings cloud-native design on-prem.
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SELinux will try to tag all files in the filesystem, causing the pod start to be delayed until all files are tagged, often when the PVC has a bigger amount of fies this will cause a timeout and the minio container will not even start.
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The data lake was once heralded as the future, an infinitely scalable reservoir for all our raw data, promising to transform it into actionable insights. This was a logical progression from databases and data warehouses, each step driven by the increasing demand for scalability. Yet, in embracing the data lake's scale and flexibility, we overlooked a critical difference.
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When it comes to storing and managing data, there is the modern, cloud-native way and there is the traditional, appliance oriented way. Needless to say, object storage is the modern, cloud-native way. While it would be simple to suggest that MinIO is hopelessly biased towards object storage (it is, afterall, the only thing we do), that would miss a key
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To support AI and analytics, a data lakehouse must be secure by design. This blog covers best practices for securing storage, metadata, and catalog layers including encryption, fine-grained IAM, audit logging, object locking, and multi-site replication without sacrificing performance.
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MinIO, the leader in high-performance AI storage, has once again raised the bar in the AI infrastructure industry with its groundbreaking MinIO AIStor platform. Leveraging next-generation AMD hardware, KIOXIA NVMe™ SSDs, and cutting-edge software optimizations, MinIO AIStor delivers unmatched performance, scalability, and efficiency for AI-driven and other data intensive workloads. Today, we are excited to share benchmark results that demonstrate
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It is hard to believe that it was 13 years ago that Marc Andressen penned his famous blog entitled “Software is Eating the World.” In it he spoke of the disruption that modern software organizations were inflicting on traditional businesses. Thirteen years later, even in the face of stratospheric valuations for Nvidia, software continues to eat the world. The evidence
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Ransomware attacks are nothing new. The first ransomware attack occurred 36 years ago in 1989, and it is known as the AIDS Trojan PC Cyborg Virus. Floppy disks infected with a Trojan virus were mailed to attendees of the World Health Organization’s AIDS conference and other individuals. The virus waited until the computer had been booted 90 times. Then
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MLOps, short for Machine Learning Operations, is a set of practices and tools aimed at addressing the specific needs of engineers building models and moving them into production. Some organizations start off with a few homegrown tools that version datasets after each experiment and checkpoint models after every epoch of training. On the other hand, many organizations have chosen to
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An abbreviated version of this post appeared on The New Stack on March 19th, 2024. In enterprise artificial intelligence, there are two main types of models: discriminative and generative. Discriminative models are used to classify or predict data, while generative models are used to create new data. Even though Generative AI has dominated the news of late, organizations are still
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Relationships matter, especially in your data. Explore graph analytics without moving data using PuppyGraph, Apache Iceberg, and MinIO AIStor. Quickly set up a cloud-native graph analytics stack that uncovers hidden patterns directly from your data lakehouse.
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Apache Iceberg is significantly transforming modern data lakes. Its introduction to object storage platforms has been celebrated for delivering ACID transactions, strong schema evolution, and warehouse-like reliability to data lake architectures. The Iceberg Catalog API standard is crucial to this transformation, as it ensures that various tools can consistently discover tables and execute atomic transactions once a compliant catalog service
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Large numbers of small files present big challenges for application performance.
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We were talking with a well-respected industry analyst the other day and he challenged us to articulate why Kubernetes is so important to Object Storage. It got us thinking that this was a topic worthy of our time, and yours. Why Kubernetes Demands More Than Just Stateless Apps At the most basic level, the value of Kubernetes lies in its
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Legacy systems drain budgets, slow innovation, and block AI progress. This article shows how phased modernization cuts costs, boosts performance, and builds a future-ready data foundation without disruption. Inaction is the real risk.
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While still in its infancy, it’s no secret that enterprise AI adoption is shaking up the entire technology landscape. Five years ago, CIOs were under immense pressure to figure out their cloud strategy and the answer was, put simply, migrate everything to the public cloud (AWS, Azure, GCP). Now, CIOs are under even more pressure to figure out their
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This is the story of how an enterprise cloud content platform architected one of the largest and most resilient SmartStore deployments in production using MinIO AIStor and Splunk SmartStore. One of the world’s largest content platforms faced a serious scaling issue. They were ingesting multiple terabytes of observability data per day, and that footprint was growing by multiple petabytes
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How a global manufacturer is cutting inspection labor by 10x with anomaly detection and edge-native object storage Overview On factory floors around the world, visual inspection remains one of the most labor-intensive and error-prone steps in the manufacturing process. At one global consumer goods manufacturer, this challenge is being redefined with AI at the edge. By replacing manual spot checks
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Edge computing is a hot topic and carries with it some confusion, particularly around storage. Handling data properly at the edge can ensure a scalable, cost-effective and secure infrastructure - but failing to set up the right architecture can lead to data loss, security vulnerabilities and sky-high costs related to the bandwidth needed to transfer data repeatedly to and from
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AIStor S3 Express is a high-performance object storage API designed for demanding data lakehouse workloads. Benchmarks show it outperforming AWS S3 Express on LIST operations and large object GETs.
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