Infrastructure performance and capacity planning professionals gathered last week in Hollywood, Florida for another exciting IBM TechU event filled with great opportunities to meet and hear from enterprise IT professionals and industry leaders.
IntelliMagic was there as a proud Bronze sponsor of the event and presented on three topics during the week that touch on the latest in infrastructure analytics for performance and capacity analysts.
For those of you who made it out to Hollywood, Florida, hopefully you were able to attend one (or all) of our technical sessions, but if not, and for those who were unable to attend, we have compiled all of our presentations for you to review at your convenience.
More Performance and Capacity Predictability out of RMF and SMF
The good news is that SMF and RMF/CMF are the most robust machine-generated operations data in the data center. The problem is in how hard it is to correlate and understand all the data and what it really means for the performance and cost-efficiency of your workloads on your specific z/OS infrastructure configuration.
This session explored new approaches to analyzing the operational data and in particular how predictability can be dramatically affected with an additional type of artificial intelligence automatically applied to the data.
Watch our recorded webinar: Predictive Analysis from RMF/SMF for Enhanced z/OS Performance and Capacity Planning
Easy CICS & Db2 Transaction Profiling
In this session we demonstrated the benefits of modernizing how you understand and leverage your SMF data for CICS and Db2 performance analysis. We highlighted how the IntelliMagic approach, with automatic health checks and dashboard technology, identifies potential performance and availability issues before they impact production. The power of context-sensitive drilldowns to provide enhanced visibility and facilitate effective analysis was also showcased.
Watch our recorded webinar: CICS & Db2 Performance Analytics Based on SMF Data
Optimizing Processor Cache on z13 and z14 Processors
Attendees of this session learned how to interpret the SMF 113 metrics to optimize their environment and potentially reduce CPU and thus MLC software expense. Based on the analysis of multiple z14 case studies, attendees gained an understanding of what they can expect from a z14 migration in their environments, whether to anticipate their capacity increase to be at the upper or lower end of the published ranges.
Overall, the presentation incorporated findings and case studies gleaned from reviewing detailed processor cache data from more than 50 sites across 5 countries. This core content has recently been recognized with SHARE Best Session and CMG Best Paper awards.
Watch our recorded webinar: Achieving CPU (& MLC) Savings on z13 & z14 Processors by Optimizing Processor Cache
CICS Max Tasks: Automated Change Detection Use Case 7
Change Detection and Health Assessments (based on pre-defined best practice conditions) play complementary roles, but there can be scenarios where they both flag issues. This use case with CICS Max Tasks is one such example.
Db2 Getpage Rate: Automated Change Detection Use Case 4
“Getpages” are a primary indicator of Db2 activity, reflecting the count of operations to access data in a page. This use case illustrates the identification of a significant increase of Getpages.
CICS CPU Per Transaction: Automated Change Detection Use Case 3
This example identifies significant increases in CPU per transaction for selected transactions, isolates it to specific CICS regions, and investigates that further.
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