Introduction to AFM to cloud object storage

The AFM to cloud object storage feature enables placement of files or objects in an IBM Storage Scale cluster to a cloud object storage.

Cloud object services such as Amazon S3, IBM Cloud® Object Storage, Seagate Lyve Cloud, and Microsoft Azure Blob storage offer industry-leading scalability, data availability, security, and performance. AFM to cloud object storage supports Amazon S3, IBM Cloud Object Storage, Seagate Lyve Cloud, Microsoft Azure Blob, and Google Cloud Platform. Microsoft Azure Blob storage is supported by using two features.
  • AFM to cloud object storage direct Microsoft Azure Blob support: AFM to cloud object storage fileset connects to Azure containers without any intermediary application.
  • By deploying MinIO as an S3 gateway between AFM to cloud object storage and Microsoft Azure Blob storage.
  • AFM to cloud object storage supports S3 endpoints as backend also.

AFM to cloud object storage associates an IBM Storage Scale fileset with a cloud object storage bucket. Customers use cloud object storage to run workloads such as mobile applications, backup and restore, enterprise applications, and big data analytics. These workloads can be cached on AFM to cloud object storage filesets for faster computation and synchronized back to the cloud object storage server.

Object applications use an AFM to cloud object storage fileset as their data access point. Data exchange between the fileset and cloud object storage buckets occurs through AFM to cloud object storage in the background, maintaining high performance for object applications. Object applications can also span across AFM to cloud object storage filesets and cloud object storage. Both the fileset and the cloud object storage can be used as a copy of important data.

The following figure illustrates the AFM to cloud object storage:
Figure 1. AFM to cloud object storage
AFM to cloud object storage

The AFM to cloud object storage on an IBM Storage Scale fileset extends cloud object storage bucket access for high-performance or active objects. Depending on the AFM to cloud object storage fileset configuration mode, objects required for applications such as AI and big data analytics can be downloaded, worked on, and uploaded to cloud object storage. Objects that applications create can be synchronized to cloud object storage asynchronously. An AFM to cloud object storage fileset can cache metadata only, or both metadata and data.

The AFM to cloud object storage also allows data center administrators to free the IBM Storage Scale storage capacity by moving less useful data to the cloud storage. This feature reduces capital and operational expenditures. The AFM-based cache eviction feature can be used to improve the storage capacity manually and by using policies. For more information about the AFM cache eviction, see Cache eviction.

The AFM to cloud object storage uses the same underlying infrastructure as AFM. For more information, see Active File Management.

An AFM to cloud object storage fileset supports an access control list (ACL) on a file of up to 2 KB. When an ACL is assigned on a file of more than 2 KB, the ACL is discarded and only file data is synchronized with the bucket.

The AFM to cloud object storage is available on all IBM Storage Scale editions.

AFM to cloud object storage by using the Microsoft Azure Blob storage

AFM to cloud object storage fileset can be configured to use Microsoft Azure Blob storage by deploying MinIO. MinIO runs as an S3 gateway, and it converts S3 API to/from Azure Blob native. All communication between AFM to cloud object storage fileset and the bucket at the Microsoft Azure Blob storage goes through S3 gateway. All the operations, modes, and functions are seamlessly supported with S3 gateway that communicates all occurrences to Microsoft Azure Blob.

The following figure illustrates the AFM to cloud object storage by using Microsoft Azure Blob as backend through MinIO S3 gateway:
Figure 2. AFM to cloud object storage by using Azure Blob
AFM to cloud object storage by using Azure Blob