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.
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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.
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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?
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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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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.
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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.
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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.
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Cloud-native AI/ML workloads push storage to the limit with many small files. AIStor combines metadata and data to optimize small file operations.
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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.
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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?
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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
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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.
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Take advantage of cloud native, Kubernetes-oriented, microservices-based architectures with object storage.
Read more...![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.
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MinIO is the fastest object storage available, but how do you know that underlying infrastructure is free from bottlenecks?
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We often talk about how good, fast and reliable access to data is paramount if you want to have an upper hand in your AI/ML game. Why is this the case? This is because hardware failures happen at different levels.
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In this post we explain how to use Splunk's advanced log analytics to help understand the performance of AIStor and the data under management.
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The Load Balancer in MinIO Firewall solves the network bottleneck. In a cloud-native environment like Kubernetes, MinIO Firewall can be fairly easy to enable the Load Balancing without any modification to your application binary or container image.
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Observability is all about gathering information (traces, logs, metrics) with the goal of improving performance, reliability, and availability.
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Simply put, OperatorHub to OpenShift is what App Store is to Apple. With a web console interface, an Operator can be pulled from its off-cluster source, installed and subscribed on the cluster, and made ready for engineering teams to self-service manage the product across deployment environments.
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Replication
Versioning
Observability
Encryption
Key Management Server
S3 Compatibility
Object Immutability
Catalog
Object Prompt
Identity + Access Mgt
Firewall
AIHub
Lifecycle
Cache
Events and Lambdas
Console
Erasure Code Calculator
Reference Hardware
Integrations with MinIO
Download MinIO Object Store
Events