IBM Z Performance and Capacity Analytics

Key features that support reporting and capacity planning

Automated data gathering

IBM Z Performance and Capacity Analytics selectively traps SMF data is soon as the record is available on each LPAR and transports it to a hub for processing, allowing you to quickly find and resolve issues and balance resource consumption to meet business SLAs.

Continuous curation of key performance metrics

Continuous curation of data improves the timeliness of your access to information and analytics so that you can better manage system availability and resolve problems with quicker insight into performance and capacity anomalies within minutes and hours of data collection, whilst lowering the processing overhead impact of data curation.

Consumable out-of-the-box dashboards

A comprehensive set of dashboards are provided across multiple reporting platforms, including Cognos Analytics, to deliver easy to adopt insights for multiple user needs from performance analysts to IT operations management and capacity planners. Curated data can also be streamed to off-platform analytics platform of choice, such as Splunk or Elastic Stack directly or leveraging IBM Z Common Data Provider, enabling IBM Z data to be visible and analyzed within enterprise-wide platforms.

Forecasting capabilities to predict future resource needs

The built-in Forecaster function provides the means to use your historical data usage trends (plotted against existing capacity) to determine when additional resources will be required in your IT strategic planning process.

Extensible data framework

New data sources can be added to your collection to supplement and expand upon the product-provided sources. You can configure data collection to suit your specific needs including annotating data collections to provide application-level context to workloads.

Enhanced reporting for your R4HA and Tailored Fit Pricing

Whatever pricing model you follow to license software on IBM Z, enhanced reporting is provided to help performance and cost management to identify products and workloads that contribute to the either the rolling 4-hour average or enterprise consumption models.

Integrate Db2 Analytics Accelerator to optimize analysis

Take advantage of IBM Db2 Analytics Accelerator (IDAA) to deliver insight at lower performance cost by storing data directly to IDAA. This reduces data storage on Db2 for z/OS, and allows CPU work to move from z/OS to the IDAA appliance, leveraging high-speed query performance.

'What If' analysis for accurate upgrade decision planning

Understand how CEC and LPAR capacity varies when either the number of physical processors is increased or a processor model is upgraded. Assists in visualizing the effect of upgrading to new processors by showing how much additional capacity would be available on an overall system level as well as an individual LPAR level.

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