Agility and Management of Large Enterprise Workloads.. the IZWS Story
Project and Program:
Enterprise Data Center,
Data Center Management
Tags:
Proceedings,
2019,
SHARE Pittsburgh 2019
IBM Z Workload Scheduler recently introduced strong improvements to optimize batch workload execution through the built-in analysis and prediction of the timing of workload submission, keeping care of SLA attainment. Leveraging this optimization feature, you will be able to reduces the CPU consumption while running your batch. Moreover, the latest release of the product enables batch resources prompt analytics leveraging the out of the box integration with IBM Common Data Provider for Z Systems to stream workload automation data to the most commonly used analytic platforms (Splunk and Elastic Stack). Come and learn about these exciting capabilities and the value these can bring in your organization.-Domenico D'Alterio-IBM
Back to Proceedings File Library