Workload Automation Manages the Cloud
Cloud computing is transforming just about every facet of enterprise IT. Yet one of the stalwarts of IT—workload automation— may actually hold the key to making the most of this revolutionary innovation.
While the cloud offers the one-two combination of limitless resources and pay-as-you-go pricing, its cost-efficiencies are still governed by an IT organization’s internal guesswork. Plan for too many resources and the economic value can be diminished or lost. Anticipate too few, and performance (increasingly defined by SLAs) will suffer—perhaps precipitously.
Moreover, resource requirements are a moving target. What might be needed this month, this day, this hour or even this minute may vary depending on unexpected changes in processing needs. Such external resource decisions must be made based on the amount of internal resources that happen to be available at that particular time.
It would seem that workload automation applications would be an ideal solution to this important problem. After all, these platforms have evolved in recent years and now are designed to analyze, assemble and monitor the exact amount of limited computing resources needed to simultaneously execute tens of thousands of computing jobs within the enterprise.
The problem is, most conventional workload automation solutions rely on a reactive model for decision-making. Their specialty is managing a finite number of computing resources to meet the needs of discrete, individual tasks occurring on a schedule or under well-defined dependencies. To effectively leverage a system in which storage, processing power and other resources are without limit, a decision engine must be in place that can accurately predict the capacity needed.
To accomplish this, workload automation must have not only historical information necessary to plan for sufficient cloud resources, but also the analytical power to decide exactly how many and when those resources will be needed on a just-in-time basis. This is where the advent of a powerful new concept —intelligent automation— will determine the ultimate value of computing in the virtual/cloud age.
Intelligent Automation Optimizes IT
Intelligent automation, comprised of both predictive and reactive forms of resource management, provisioning and scheduling, can transform the use of cloud assets. By employing two internal databases —one transactional, the other analytical— intelligent automation can predict the computing capability needed at a given moment.
Think of it this way. A fast-food manager, operating under a reactive model, might wait until a noontime lunch crowd buys up all of his hamburgers before grilling more—say at 12:10 pm. Predictive management, by contrast, based on a knowledge of past lunch hour demands, would require that the grill start cooking more burgers at 11:45 am, anticipating the rush and then adjusting during the rush as needed.
Intelligent workload automation platforms with the ability to provision internal, distributed and cloud resources on-the-fly and in real time are just now entering the market. With SLAs becoming the focus of many enterprise’s IT management strategies, it’s clear that efficient resource planning and utilization are core issues in the cloud computing era. Intelligent workload automation, effectively integrated into the enterprise, can address and resolve these thorny challenges.
