Apply Statistical Analytics to Your z/OS Performance Analysis
The days of having z/OS Performance and Capacity planning teams manually evaluate metrics to detect and resolve changes and risks are over.
Advanced statistical algorithms applied to the most meaningful RMF/SMF metrics will automatically identify significant changes to the z/OS workloads and applications and enable capacity planners to accurately forecast workload growth.
This statistical approach, combined with the predictive capabilities of Availability Intelligence, is the most advanced way to understand the performance and availability of the z/OS platform.
This webinar demonstrates how applying statistical algorithms to meaningful RMF/SMF metrics will result in benefits such as:
- Automatic detection of z/OS workload changes
- Quick notifications of service degradation
- Understanding workload peaks in context
- Accurately forecasting workload growth
- Feed cross-platform application monitoring
Stretched in 2020?
This year has certainly stretched everyone. Learn some ways to overcome some new and unexpected challenges that likely weren’t even on your radar in January.
Transparency in z/OS Infrastructure Performance Analysis
Discover how to easily break down the silos one application at a time to achieve greater transparency and collaboration.
Mainframe encryption causes higher demand in TCP/IP address space
Many shops are using IBM’s pervasive encryption to protect their mainframe's integrity, but how do we get in front of the mainframe impacts or know which encryption methods might meet security requirements at lower cost?
Experience firsthand the deepest visibility into your z/OS systems, processors, network, disk and tape environments. Whether you’re in the early stages of product research, evaluating competitive solutions, or trying to solve a problem, we’re happy to help you get the information you need to move forward with your IT initiatives.
Supported Areas in IntelliMagic Vision for z/OS Systems
Monthly License Charges (MLC)
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