MQ Statistics and Accounting SMF data provides extremely useful insights into MQ management and operation. Unfortunately, extracting those insights from the SMF 115 and SMF 116 record types is challenging – and raw data pulls lack context or accessibility.
Our learning journey will include:
- How to proactively identify risks to MQ availability and performance
- Introducing the many types of metrics provided in the MQ Statistics data, including requests by MQ command, buffer utilization and write thresholds and various logging metrics
- Introducing metrics available in the MQ Accounting data, including command elapsed and CPU times, message lengths, persistent message counts, and queue depth
- Examining the differing profiles of work generated by the various callers of MQ services (“connection type”), including elapsed and CPU times
More IntelliMagic zAcademy Sessions
From CPU MF Counters to z16 Invoices: Thoughts on the Impact of Processor Cache Measurements | IntelliMagic zAcademy
The z16 introduced substantial processor cache design changes. Learn how this impacts the operation and efficiency of your workloads.
Insights into New XCF Path Usage Metrics | IntelliMagic zAcademy
Gain a better understanding of how XCF operates in general, tips about how to optimize their environment for the new paradigm, and information about what can be learned from the new Path Usage metrics.
Closing the Gap on Mainframe Application Profiling | IntelliMagic zAcademy
Break down the barriers between z/OS and distributed systems and communicate specific methods both sides can use to classify workloads properly.