Focusing analysis by authorization ID can be particularly helpful for insights into managing DDF work which is often challenging since it lacks many of the controls in place for other types of workloads.

 

More Db2 Accounting Videos

  1. Exploring Analysis by Connection Type
  2. Exploring Analysis by Correlation ID
  3. Exploring Elapsed Time Profiles
  4. Exploring Analysis by Authorization ID
  5. Exploring Prefetch Activity and Suspension Events
  6. Exploring Analysis by Plan or Package Name
  7. Exploring Database Sync I/O Activity
  8. Exploring Other Metrics in Accounting Data by Plan
  9. Accounting Data: Customized Dashboard Recap

 

Video Transcript

Another primary way to explore analysis of accounting data is through the authorization ID. Auth ID is captured for all connection types, but it can be particularly helpful for insights into DDF work, which often lacks many of the controls in place for other types of work. So we will initially here work from this report set of views that are specifically focused on DDF work. So one thing we learned right away from this aggregate view is that much of the CPU is executed on zIIP engines in yellow so that it doesn’t incur software license charges. And that’s of course, a key benefit of DDF work. So one, you know, initial right off the top, we might want to explore which auth IDs are the top CPU consumers. And so here they are, and we’re going to continue to collect these views on our dashboard and we’ll come back and look at that later. And as we explore the at time of day profile for this top consumer follows a typical online profile, so indicating, and may be invoked as part of some standard business transaction processing.

And one of the challenges of managing DDF work can be in user-submitted tasks, inadvertently turning into rogue runaway work, consuming, large amounts of CPU. So here, when we view the CPU over time and I’ll extend it to this entire weekend, the demo database, there’s no major outliers, which is good news, but there is a daily spike here that’s worth exploring. So let’s go ahead and customize this view. We’ll focus on the general-purpose CPU time. We will view it by authorization ID. We’ll kind of narrow it down to the top 10, so that gets rid of some of the noise. And so now when we do that, we can correlate the spikes to a particular auth ID, which appears to kick off a daily process early morning, each day.

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