Have you tried any in-memory optimization techniques since transitioning to Tailored Fit Pricing? With the adoption of Tailored Fit Pricing comes new opportunity. Under the traditional Rolling 4 Hour Average (R4HA) model, the focus for optimization was solely on the peak 4 hours of the month. However, with Tailored Fit Pricing, there are suddenly ~740 other hours in the month that are ripe for optimization. It’s time to look into the dark corners of your environment.
Many solutions exist to help eliminate inefficiencies and control MSU consumption. Clients can leverage application modernization approaches, use the latest compiler technologies, or ensure zIIP-eligible workloads are utilized properly. Another potential solution exists in the form of high-performance in-memory processing. Clients have used high-performance in-memory processing to maximize their Z investments and drive capacity for new workloads in both batch and online scenarios. Results vary widely depending on when, where, and how in-memory methods are used but we’ve seen customers save up to 90% of CPU on mission critical jobs. Crazy right?
This is all about drastically improving your mainframe performance while lowering total cost of ownership. It’s about modernizing your applications in place and squeezing every bit of value out of them. If Db2 tables and/or VSAM files represent significant sources of data processing in your environment, then we invite you take a deeper look.
Contact your IBM rep and ask about IBM Z Table Accelerator. We’ll collect some data, analyze it for you, and tell you where the best cost savings opportunities lie.
Originally published on the IBM Z Community Blog