Transcript of "Intelligent workload management_opportunities_challenges"
WHITE P APER
Intelligent Workload Management: Opportunities and
Sponsored by: Novell
Mary Johnston Turner Sally Hudson
Over the next several years, IDC expects enterprises will continue to increase both
the percentage of virtualized datacenter workloads and the density of virtual
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machines (VMs) on physical servers while continuing to maintain many single-
purpose systems. Simultaneously, many organizations will add public and/or private
cloud services to their enterprise infrastructure mix.
To make the most effective use possible of this dynamic and heterogeneous
infrastructure environment, IT teams will need to shift to a more policy-based,
automated approach to managing the building, provisioning, migration, monitoring,
measuring, and securing of corporate workloads.
Intelligent workload management is an emerging market concept that addresses this
complex set of needs by integrating a number of important technologies, including:
Software appliances for intelligent workload packaging and deployment
Policy-based workload management automation
Configuration and performance monitoring, reporting, and analytics
Intelligent workload management solutions are evolving and being built on a number
of existing technologies, including software appliances, server and workload
automation, and identity and access management (IAM) solutions. IDC estimates
that in 2009, the server and workload automation market totaled approximately
$600 million worldwide, the identity and access management software market was
$3.5 billion, and the market for software appliances was $156 million.
IN THIS WHITE P APER
The workload management and security challenges created by dynamic, virtualized
datacenter and cloud service environments, along with continued use of physical
systems, are forcing datacenter managers to explore more automated, policy-driven
workload provisioning, migration, auditing, and access control capabilities in order to
maintain services levels and rein in operational costs. To use these technologies