Is Your Car or Mainframe Better at Warning You?
Early warning can help avoid problems before they occur or impact production, and help fix a minor issue before it gets worse.
John Baker Joins IntelliMagic to Help Customers Optimize their z/OS Mainframe Application Performance
Jan 28, 2019 | IntelliMagic announced the return of John Baker to the IntelliMagic team to assist customers operate more efficiently and modernize their data analysis and infrastructure performance.
z/OS Performance Monitoring Best Practices for 2019
For z/OS performance management, a stormy holiday season can mean excessive application downtime, lost revenue, customer frustration, and more.
IntelliMagic Vision: Intelligent Storage Performance and Capacity Management at DATEV eG
DATEV eG relies on IntelliMagic Vision for performance analysis and capacity planning for disk storage and virtual tape systems.
Medavie Blue Cross Proactively Ensures Availability of HPE 3PAR and Brocade Fabric
Medavie Blue Cross uses IntelliMagic Vision to help maintain a reliable infrastructure in their two data centers comprising over 1 PB of HPE 3PAR Storage and Brocade Fibre Channel SAN switches.
AIOps, Mainframe Monitoring, MLC Optimization, Oh My: Hot Mainframe Topics of 2018
As 2018 nears its close, I wanted to reflect on the world of RMF/SMF performance analysis and provide an ode to the topics that resonated most within the industry.
Anatomy of an Anomaly – Finding the Root Cause of a CONNECT Time Increase
Recently a situation occurred at one of our cloud services customers that was a real head-scratcher. One of the disk storage systems saw a sudden jump in CONNECT time. What had changed?
Reporting on z/OS Mainframe Application Performance
Intelligent reporting on mainframe applications is very helpful to understand application performance and behavior on the mainframe, and how the applications are using your systems.
Integrating z/OS Performance Management with Splunk & Enterprise Dashboards
IntelliMagic Vision can export data into a Splunk-ready format, after which it can be imported into Splunk. This means not much data is ingested into Splunk, which can be a significant cost-saver.