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.
CPU by WLM Importance Level: Automated Change Detection Use Case 2
Leveraging context-sensitive drilldowns, based on an unanticipated finding of a spike in CPU consumption for the highest importance “Systems” work, this video investigates the address space(s) driving that.
CPU by System: Automated Change Detection Use Case 1
One common use case for Change Detection is identifying significant variances in key metrics at the system level including: CPU usage, zIIP usage, percent utilization of the CPC, etc.
Introduction to Automated Change Detection for z/OS Performance Management
To help enhance the value you can derive from that SMF data, IntelliMagic Vision provides two complementary types of automated anomaly detection: Health Insights and Change Detection Views
Deriving Insights from SMF 116 MQ Accounting Data
MQ Accounting records are often considered to be too expensive, both in CPU overhead and SMF record volume. However, we believe that these concerns may be overstated.
MQ Accounting - Learning From SMF
This article is designed to introduce you to the types of insights that are available through SMF data with a focus on the SMF 116 MQ Accounting data.
AI: Too Much of a Good Thing
Solution providers will continue to entice us with bigger and better real-time analytics. Some of these should be employed, but first try to understand the logic you may be activating when you implement.
Understanding How Logical Workloads Behave On Physical Hardware
If you find elevated response time on a logical volume, how do you know which physical drives may be causing it?
Troubleshoot High CPU and zIIP Utilization in WebSphere Application Server
A common problem performance analysts encounter is high CPU utilization on a server or application without the ability to identify the root cause of the problem quickly and easily.