IntelliMagic Vision for z/OS Systems Performance Management
IntelliMagic Vision optimizes z/OS Systems performance management using AI-driven analytics to enable your z/OS experts to proactively monitor and manage your z/OS environment, prevent disruptions, optimize performance, reduce costs, and preserve the reliability and availability that mainframes are known for. IntelliMagic Vision has extensive support for z/OS Systems, Processors, and Network.
View this brief video to discover how IntelliMagic Vision can optimize your z/OS Systems environment.
Optimize z/OS Mainframe Systems Management with Availability Intelligence
Through RMF and SMF, z/OS offers a richer source of infrastructure measurement data than any other computing platform. However, the potential to use this wealth of information to prevent service disruptions remains vastly underutilized. This data cannot simply be interpreted without the right intelligence.
IntelliMagic Vision enhances the RMF data and applies its built-in knowledge to understand how the z/OS architecture handles your workloads. This helps you tune z/OS to improve performance and protect availability, and can also help tuning your processor configuration to increase the MIPS you get out of your mainframe hardware.
See how this intelligence can help you in the use cases below:
Monthly License Charges (MLC)
Tune your processor configuration to increase the MIPS you get out of your mainframe hardware.Learn More
4HRA / R4HA
Reduce 4HRA / R4HA without impacting application performance.Learn More
Configure Coupling Facilities for optimal availability and proactively identify hidden health and performance risksLearn More
Ensure sufficient capacity and consistent performance for IBM zEDC availability.Learn More
Workload Manager (WLM)
Automated health check for workload manager (WLM) goals, improving performance and protect availability.Learn More
RMF 72 Transactions
Save CPU & Manpower with Reporting on Key Transaction Level MetricsLearn More
Health Insights and Change Detection
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.
CICS Max Tasks: Automated Change Detection Use Case 7
Change Detection and Health Assessments (based on pre-defined best practice conditions) play complementary roles, but there can be scenarios where they both flag issues. This use case with CICS Max Tasks is one such example.
Batch Job Elapsed Time: Automated Change Detection Use Case 6
Elapsed and CPU times can be of interest for batch jobs, especially those on the critical path for key business job cycles. This use case reflects an abnormally long run time for a daily batch job, and illustrates how potential causes might be investigated.