Automated Health Check for Workload Manager Goals
IntelliMagic Vision for z/OS leverages underlying knowledge about the Workload Manager to help you optimize goals and performance and alert you to otherwise hidden availability risks.
Optimize WLM Performance and Highlight Availability Risks
Dynamic workload management, which is performed by the Workload Manager (WLM), is an essential part of the z/OS operating system where multiple workloads run simultaneously.
Workloads are categorized into distinct service classes, for which a ‘goal’ and ‘importance’ is defined. The goal describes what performance a service class should get, and the importance defines how important it is that goals are met for this service class, relative to the other service classes. WLM uses this to make sure the most important workloads get priority at times when resources are scarce.
The performance index (PI) is the metric that measures whether WLM goals are met, by computing how high the response time was relative to the goal: PI = Measured Transaction Response Time / Response Time Goal. A value greater than 1 means the response time for the service class did not meet the goal.
With easy-to-use interactive data navigation, historical reporting, single-click data comparisons and report customizations, built-in recommendations and anomaly detection, and a comprehensive set of WLM reports, IntelliMagic Vision provides unrivaled visibility into your environment.
Clear Insights into WLM Goals
IntelliMagic Vision for z/OS makes a rating for how well goals were met, based on the height of the PI in combination with the importance. This gives clear insight into how well WLM manages to achieve its goals, and in case of missed goals, how severe problems are. These ratings are shown in the WLM dashboard.
Understand Internal Components with Deep Insights
When the dashboard shows yellow or red bubbles, it is important to be able to find out why the response time goals were not met. The “using” and “delay” components of the response time are shown by IntelliMagic Vision at various levels, such as per LPAR or per service class. This provides a very deep insight in whether CPUs are busy doing actual work, or whether there is any contention on the processors or on the DASD.
For instance, when the Using DASD component is significant, it is very worthwhile to investigate using IntelliMagic Vision drill-downs if I/O tuning or a (partial) storage system upgrade can make a difference. These are likely much less expensive than a processor upgrade.
Intuitive Visibility into SMF Data
In contrast to approaches today that require coding programs or mastering tooling siloed by technology to access various types of SMF data, a common, intuitive user interface eliminates effort spent mining data and instead frees up staff to focus entirely on high-value analysis.
This single interface used across the entire z/OS platform greatly expedites learning, promotes collaboration, and enhances analytical effectiveness.
Context Sensitive Drill Downs
Context sensitive drill downs enable an analyst to identify alternative analytical paths based on the data currently being displayed and quickly investigate each hypothesis with just a few clicks, greatly reducing lost time when exploring what ends up being a “dead-end” path.
When dealing with massive SMF data volumes, this capability to focus analysis on the desired subset of data becomes especially valuable.
Accelerated Root Cause Analysis
Highly flexible drill-down capabilities of IntelliMagic Vision enable data to be viewed at the processor, system, card, or address space level and specific migration activity. Built-in conditional filters can further be a customized for a set of reports on a focused dashboard.
Quickly investigate each hypothesis with just a few clicks and greatly reducing lost time when exploring “dead-end” paths.