Introduction to metrics found in MQ Statistics records and how automated assessments of key metrics can facilitate proactive analysis and prevention of outages by identifying areas that may warrant investigation.
More MQ Statistics Videos
- Overview of MQ Statistics and Health Assessments
- Assessing MQ Buffer Manager Health
- Assessing MQ Log Manager Health
- MQ Message Manager Metrics Supplemented by Accounting Data
- Log Manager and Buffer Manager Metrics
- Sample MQ Statistics and Accounting Dashboards
All right. So let’s start our journey here of learning from the MQ statistics data. There are two primary types of MQ SMF records, Statistics and Accounting. And those of you that are familiar with Db2 will recognize parallel to Db2 that also has Statistics and Accounting. The MQ Statistics records, SMF 115, provide data at the queue manager level, as well as by buffer pool where applicable. These records are lightweight, and so they’re typically generated at all MQ sites on an ongoing basis. The data is generated at user-specified intervals, the default’s 30 minutes. If you specify the STATINT equals zero, then the records are cut at the SMF global accounting interval, which gives you alignment with the metrics coming from other subsystems in the environment. So that facilitates collaboration and so we certainly recommend that.
MQ statistics data is produced by all the key MQ components, including the buffer manager, and here are a couple of metrics, rather than me talking much about them, we’ll look, look at them in live data here in a minute. The log manager, and we’ll talk about those metrics as well. The message manager, and we’ll also look at that and then the storage manager. We won’t probably touch on that today, but its contractions and short on storage conditions are a couple of the highlights of that from the storage manager. And then the other components also all produce their own data.
So Brent talked about the value of health assessments and the MQ statistics data provides many metrics that lend themselves to being assessed as part of the overall health of a queue manager. You know, again, if the goal is to proactively assess key metrics for key critical components across the z/OS infrastructure, which for MQ would include every queue manager in buffer pool automation of those assessments is essential There’s just too many metrics and too many components to succeed at that task with a manual approach.
So the IntelliMagic Vision implementation of that assesses a little over 30 metrics, and they can be customized as needed. The views start from a high-level view by queue manager to present the assessments in a consumable manner that direct your attention to potential issues that might warrant investigation. And again, here are some of the metrics that are really suitable for assessments. And again, we’re going to look at examples of the buffer manager and log manager coming up.
Speak to a Technical Expert Today
Whether you are conducting product research, need support on a project, are experiencing downtime, or want to learn more about how IntelliMagic can support your business, our experts are here to help.
You May Also Be Interested In:
MQ: How to Extract Insights and Optimize Performance Using SMF Data | IntelliMagic zAcademy
This webinar will introduce you to best practices for enhancing your analysis of MQ Statistics (SMF 115) and Accounting (116) data.
Using zHyperWrite to Improve MQ Logging Performance
In this blog we examine before-and-after measurements of a recent zHyperWrite implementation for MQ logging in a large z/OS environment.
Selected MQ Accounting Data SMF Metrics – Part 2
Examples of various SMF metrics captured in MQ Accounting data that provide insights into detailed MQ activity.