MinIO Blog

MinIO Blog

Migrating MinIO Cluster Instances with Zero Downtime and Zero Data Loss

Migrating MinIO Cluster Instances with Zero Downtime and Zero Data Loss

With the advent of cloud computing, ephemeral compute instances have become ubiquitous. This introduces a whole set of challenges around managing the software, applying DevOps principles, addressing security vulnerabilities and ensuring automation. These are mission-critical in order to prevent data theft and service disruption. Addressing security vulnerabilities is particularly challenging as it frequently takes the form of updating and restarting

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Takeaways from Kubecon EU

Takeaways from Kubecon EU

Kubecon EU in Valencia, Spain was a welcome breath of fresh air for the Kubernetes community. While the Linux Foundation and the CNCF did great work in the pandemic, nothing is quite like seeing your “people” in person. That what Valencia delivered. I don’t know the attendance figures off the top of my head, but having been in Los

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Introducing DirectPV

Introducing DirectPV

DirectPV is a CSI driver for Direct Attached Storage. At the most basic level, it is a distributed persistent volume manager, and not a storage system like SAN or NAS. DirectPV is used to discover, format, mount, schedule and monitor drives across servers. Before we get into the architecture of DirectPV, let’s address why we needed to build it.

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Machine Learning Using H20, R and MinIO

Brian Costa Brian Costa on H20 |
Machine Learning Using H20, R and MinIO

I’ve been working with neural networks and machine learning since the late ‘80. Yes, I’m that old. The first product I bought was California Scientific Software BrainMaker Professional. I loved that product because it got me started with neural networks. I still have it: It was a 3 layer neural network product that came with source code in

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MinIO and Apache Arrow Using R

MinIO and Apache Arrow Using R

Arrow here, Arrow there, Arrow everywhere. Seems like currently you can't swing a dead cat without hitting an article or blog post about Apache Arrow. Most seem to be addressing a developer audience and are based on a Python and Spark style development platform. Today I’m going to write about using Apache Arrow with MinIO from the

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Building Performant Data Infrastructure with Apache Arrow and MinIO

Building Performant Data Infrastructure with Apache Arrow and MinIO

There is a lot of momentum around Apache Arrow these days. A favorite of developers and data practitioners, its use in business-critical applications has grown considerably and data driven organizations like Dremio, InfluxData, Snowflake, Streamlit, and Tellius are all heavily invested. The drivers of this adoption are superior interoperability, simpler data architectures, greater speed and efficiency, more choice of tools

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The Architect’s Guide to Using AI/ML with Object Storage

The Architect’s Guide to Using AI/ML with Object Storage

This post first appeared in The New Stack. With the constant evolution of the enterprise, machine learning and artificial intelligence have become board-level initiatives. Marketing claims aside, capabilities that seemed almost mythical a few years ago are now taken for granted as AI/ML becomes baked into every software stack and architecture. This is becoming known as AI-first architecture. In

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How to Install and Configure Kubeflow with MinIO Operator

How to Install and Configure Kubeflow with MinIO Operator

Kubeflow is a modern solution to design, build and orchestrate Machine Learning pipelines using the latest and most popular frameworks. Out of the box, Kubeflow ships with MinIO inside to store all of its pipelines, artifacts and logs, however that MinIO is limited to a single PVC and thus cannot benefit from all the features a distributed MinIO brings to

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Western Digital OpenFlex Data24 Performance Testing

Western Digital OpenFlex Data24 Performance Testing

We recently benchmarked MinIO S3 performance on the Western Digital OpenFlex Data24 using the WARP benchmark tool. Western Digital’s OpenFlex Data24 NVMe-oF Storage Platform extends the high performance of NVMe flash to shared storage. It provides low-latency sharing of NVMe SSDs over a high-performance Ethernet fabric to deliver similar performance to locally attached NVMe SSDs. Industry-leading connectivity, using Western

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