Enhance Search with AIStor and OpenSearch
In this post we look at how search, and specifically OpenSearch can help us identify patterns or see trends in our ever growing data.
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AIStor on RedHat OpenShift for Local development
Running AIStor on OpenShift enables enterprises to achieve cloud-native elasticity on their hardware or cloud instance of choice, balance cost, capacity and performance.
Read moreAIStor 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.
Read moreAIStor Best Practices for Updates and Restarts
Deep dive into AIStor mindset on how we do and recommend updates and restarts with AIStor.
Read moreNetwork configurations to make the most of AIStor
We’ll dive deep into the network configurations with which you can configure AIStor to the different replication strategies and network topologies that can be used to ensure your data is stored and accessed efficiently across multiple AIStor deployments.
Read moreAI/ML’s Sous-Chef: Why your Second Hire should be a DevOps Engineer
Your DevOps Engineer’s customer should be your AI/ML Engineering Team. The DevOps Engineer is there to ease the friction points in infrastructure so AI/ML folks can focus on the task at hand. Any issues that come with the infrastructure should be the responsibility of the DevOps Engineer.
Read moreBuild a CI/CD Pipeline for your AI/ML infrastructure
In this tutorial, we’ll bake the MinIO binary and the service dependencies, such as the username and group required for MinIO. We are baking this instead of frying because these will remain the same no matter how we configure and launch our image.
Read moreAI/ML Continuous Integration and Continuous Delivery Foundations
Have you ever wondered how the big dogs with hundreds of apps and millions of users manage their Continuous Integration (Builds) and Continuous Delivery (Deployments) workflows?
Read moreA 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
Read moreAI/ML workflows with AIStor and Metaflow
AIStor and Metaflow can be deployed anywhere on any type of infrastructure. In fact more often than not we have folks deploying AIStor and metaflow alongside each other as part of the deployment pipeline.
Read moreManaging AI workloads with Tagging and Policies
Object tags give you greater power. You now have the ability to categorize by up to ten dimensions. If you want to add the diagram to a project, then all you have to do is tag it appropriately.
Read moreAI Data Workflows with Kafka and MinIO
AIStor is a foundational component for creating and executing complex data workflows. At the core of this event-driven functionality is MinIO bucket notifications using Kafka.
Read moreWorking with Small Objects in AI/ML workloads
Cloud-native AI/ML workloads push storage to the limit with many small files. AIStor combines metadata and data to optimize small file operations.
Read moreTame the AI beast with Monitoring and Alerting
In this post we’ll show you how you visualize the cluster metrics in a web browser and also we’ll set up alerting so that when something like a drive needs to be replaced or drive runs out of space we can get alerted for it.
Read moreGit-like versioning for your AI Data
You’ve surely version controlled code in the past. But have you version controlled your data? Did you ever want to collaborate on large sets of data with various teams without committing a large chunk?
Read moreWe Tried the Dell ObjectScale Community Edition, It Wasn’t Pretty
Dell generally focused on the filer game, but they dabble in object storage and have a very old offering, ECS. That makes sense, it was a step up from tape and wasn’t suited for dynamic workloads like HDFS modernization or database workloads. Needless to say, AI was out of the question. For a few years now, Dell has been
Read moreACID Transactions with Iceberg on AIStor
Pairing the Iceberg table format with AIStor creates a powerful, flexible and extensible lakehouse platform. The Iceberg Table Spec declares a table format that is designed to manage “a large, slow-changing collection” of files or objects stored in a distributed system.
Read moreMigrating from HDFS to AIStor
Take advantage of cloud native, Kubernetes-oriented, microservices-based architectures with object storage.
Read moreGone [to Prod] in 60 Seconds
![Gone [to Prod] in 60 Seconds](/content/images/size/w600/2024/09/gonetoprod-in60seconds-noeyes.jpg)
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.
Read moreBenchmarking AIStor with WARP and Perf test
MinIO is the fastest object storage available, but how do you know that underlying infrastructure is free from bottlenecks?
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