Theme: Use your Power9 IBM Power resources for AI data processing tasks
By now, most have heard the saying:
“If you are not using AI, you are behind.“
For companies using IBM Power, especially Power9, which is commonplace throughout the industry, here is an idea of how you might use your existing or easily accessible cloud-based Power resources to help you jumpstart your journey to AI.
My company provides the ability to host IBM Power AIX and IBMi application workloads in the cloud. We partner with two of the world’s largest technology companies to provide this service. During my daily activities as a Cloud Solutions Architect (aka Pre-Sales Engineer), I listen to many customers tell us about their “hopes and dreams” regarding moving legacy workloads to the cloud. These are definitely “Cloud Stubborn”. But when it comes to legacy applications based on IBM Power one of their common responses is:
“It is impossible to move my IBM Power-based application to the cloud.”
Of course, that begs the question “Why not?” The answer is often one of these:
Beyond having checklists and runbooks, what else can you do to test your backups?
In the comprehensive article called “How to Prove Your IBM i is Recoverable without a Real DR Test,” Tom Huntington from HelpSystems details all the IBM i Save Commands and system objects that should be included within a comprehensive backup. By performing an audit of your backup process, you might identify missing components that prevent you from doing the worst-case scenario, a full system restore. It is a great article that IBM i administrators should review.
Continue readingIntroducing “Cold Storage” of complete application systems in the Cloud.
Traditional application archiving is often described in one of two ways:
1) Archiving – this is where you have an application that has accumulated large amounts of historical data that exists on Tier 1 primary storage within the data center. The basic concept is that you take some of the older, infrequently accessed data and “archive” it or move it to some other read-only data warehouse that utilizes less expensive storage. The idea is to save money by reducing the pressure to expand more expensive storage and potentially reduce those costs over time. The application system remains “active” but with only newer relevant data.
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