The lifecycle of a workload can be broken down into four stages: Build, Secure, Manage, and Measure. Broadly speaking, workload management involves overseeing all four stages from workload design and creation to its real world deployment.
Given this model, we can define Intelligent Workload Management (IWM) in two ways. On the one hand, IWM refers to the intelligent management, either dynamically or by a process of human oversight, of the entire lifecycle of all relevant workloads in a secure and compliant manner. On the other hand, IWM can refer to the management specifically of intelligent workloads.
So what exactly makes a workload intelligent?
A workload becomes “intelligent” when, in addition to its own customized operating system, etc., it possesses the ability to manage itself, particularly with regard to identity, security, and compliance. By making the workload identity aware, one equips the workload with the controls as well as the monitoring and reporting capabilities needed for it to function safely more or less on its own in the “run-it-anywhere” world.
With existing workload management tools, one can allocate workloads to physical or virtual machines in an ad hoc fashion. When the workload becomes intelligent, it can, in effect, allocate itself to this or that environment through reliance on built-in security and compliance policies. This is important: Intelligent workloads are policy-driven. These policies tell it where it can run, where it can’t, who can access it, who can’t, etc., all the while creating an audit trail documenting where it has been and what it’s done.
The beauty is that, thanks to this policy-driven intelligence, these workloads enable the enterprise to make maximum, secure use of the full-range of current infrastructure options (physical, virtual, cloud) in a way that is cost-effective and, well, intelligent.
Posted
Jan 27 2010, 10:51 AM
by
JoelRichman