On February 18, 2020 IBM announced IBM Z Performance and Capacity Analytics V3.1, an complete solution for performance analysts and capacity planners to track key performance metrics and make informed decisions about future workload and Z environment changes.
The new release builds upon significant updates delivered throughout 2019 including new reporting based on Cognos Analytics and new capabilities that support Tailored Fit Pricing strategies such as managing MSU usage against the defined baseline, forecasting future consumption and identify optimization opportunities.
In this article, we’ll share a brief overview of some of the new features delivered in the new release:
Addressing the question of “What If” in capacity planning
For capacity planners, a major part of their responsibilities is to provide informed judgement on the future needs of the mainframe environment to support current and future workloads. This may include providing guidance on future hardware upgrades and other capital expenses to support business goals. This is aim around the new “What If” capabilities built into IBM Z Performance and Capacity Analytics. Current performance can be measured accurately with the existing configuration but what benefit might be we see if we were to change this environment or make a decision to upgrade our processors to a newer model – can we forecast the potential benefit before making the investment decision?
A brand new Cognos dashboard shows how CEC and LPAR capacity varies when:
(a) the number of physical processors is increased or
(b) a processor model is upgraded.
From here, we can visualize in an easy to digest fashion the effect of upgrading to new processors by showing how much additional capacity would be available on an overall system level as well as an individual LPAR level.
Lowering the cost with additional zIIP-eligible capabilities
Processing SMF data in near real-time is essential to get timely insight into data. In previous releases, the automatic data collectors that move the data from the spoke LPAR systems to the hub and the forecasting modules were defined as zIIP-eligible. In the new release, the continuous collector process has also been updated so that it now can be executed on zIIP engines if available. Internal testing has indicated this can save up to 70% of the processing by the continuous collector will consume less MSUs when curating data, which is especially applicable under enterprise consumption Tailored Fit Pricing model through reduced resource consumption.
“Smart Path” LPAR MIPS Usage Profiling
As a performance analyst, tracking performance over an extended period of time is critical for understanding trends and establishing if there is a change in behavior, either in the short-term due to spiky or unpredictable workloads, or a long-term change in performance.
The new Smart Path report builds an LPAR-level profiles of expected hourly behavior based on historic usage, providing insight to LPAR hourly MIPS usage, for every day of the week.