When your organization’s bean counters look at the spreadsheet showing mainframe costs, they’ll find that somewhere around 30% to 40% of the budget is going on Monthly License Charges (MLCs). The question your CFO is going to ask is whether there’s any way that this figure can be reduced? And how can you prevent it increasing each year as new versions of the software you’re using are installed?
Basically, how much you pay for software depends on the actual MSUs (Million Service Units) and the 4-hour rolling average MSU utilization. A million service units is a way of measuring the amount of processing work a computer can perform in one hour. It reflects how IBM rates the machine in terms of charging capacity. Most software vendors use a licensing and pricing model in which their customers are charged per MSU consumed. This is in addition to hardware and software installation costs. Some vendors charge by total MSU system capacity. Each mainframe model has its own MSU rating, and newer mainframe models have a 10% lower MSU rating, for the same level of system capacity, than their predecessor model.
Many sites use DefCap (defined capacity) and GCL (Group Capacity Limit) to reduce the risk of avoidable peaks. But this doesn’t allow them to optimize their system. They can try manually adjusting caps, but the problem is that doing this is time consuming, error-prone, and risky. And, all too often, it just doesn’t work because the users cannot look at all the influencing factors. What’s needed is some way to monitor all of the relevant pricing in real time, and adjust the values automatically to control costs.
What most sites need is software that can analyze and automatically manage defined capacity settings on z/OS Logical PARtitions (LPARs) as well as group and subgroup limits on groups of LPARs. They need some software that can effectively cut mainframe MLC costs while minimizing risks to their business. View Software Diversified Services’ mainframe performance and optimization solutions that can analyze, simulate, and manage changes to capacity settings based on a site’s workload profiles. These solutions can eliminate manual work and optimize capacity usage across LPARs. And they can align workload allocations based on utilization needs, workload importance, and customer policy profiles.
Certainly, these cost saving solutions provide a way for mainframe users to get control of their costs, and, hopefully, keep the CFO quiet for a little while!