Architecture & Design Patterns

In this post we look at how search, and specifically OpenSearch can help us identify patterns or see trends in our ever growing data.

In this post we’ll talk about Erasure Coding and Erasure Sets, and then dive deeper into how to use the Erasure Code Calculator when designing deployments to make the most out of MinIO by opting for the right hardware configuration setup from the get go.

Let's review some of the tools available to get data out of S3, local FileSystem, NFS, Azure, GCP, Hitachi Content Platform, Ceph, and others, and into MinIO clusters.

In this blog post, we will build a Notebook that uses MinIO as object storage for Spark jobs to manage Iceberg tables.

GitLab can use MinIO as its object storage backend to store large files such as artifacts, Docker images, and Git LFS files. Given the right underlying hardware, MinIO provides the performance and scale to support any modern workload, including GitLab.

You must have heard of different data formats like Parquet, ORC, Avro, Arrow, Protobuf, Thrift and MessagePack. What are they and how to choose the right one?

We will set up a geographically distributed infrastructure where we have a multi-node multi-drive MinIO cluster in multi-sites across vast distances. This will allow us to truly appreciate replication working at scale to help us understand the infrastructure needed for high availability.

Versioning, S3 Object Locking, Encryption at Rest and in Transit, Identity Providers, Replication, CVE Monitoring for a secure cloud-native object storage foundation.

This blog post will show you how you can migrate your existing MinIO Gateway setup to a MinIO Server deployment.

Do you need to find a way to replace Hadoop in your data lake and add cloud-native capabilities?

This post focuses on how Iceberg and MinIO complement each other and how various analytic frameworks (Spark, Flink, Trino, Dremio, and Snowflake) can leverage the two.

Learn how to monitor and alert on metrics using Grafana Mimir and save data to MinIO for persistence.

Learn how to build a cloud-native analytics and visualization stack backed by MinIO.

Learn how Reed-Solomon erasure coding provides data protection for distributed object storage at scale.

Lay the best foundation for cloud-native object storage and give developers and their apps the performance they need.

Learn how to secure data in transit, data at-rest and establish role-based access control policies in the first of a series of blog posts about securing MinIO.

Protecting blocks is not the same as protecting objects. Learn where block-level RAID falls short compared to erasure coding in distributed object storage.