How to use intelligent automation to drive better cloud resource management

This vendor-written tech primer has been edited by Network World to eliminate product promotion, but readers should note it will likely favor the submitter’s approach.

Cloud computing has dramatically improved scalability, accessibility and flexibility, but low costs and on-demand availability can result in the misue of cloud assets, either inadvertently or because of improper controls.  What’s needed is an intelligent automation solution that can automatically spin up and down resources.  But before we discuss automated options, let’s more closely examine the challenges of cloud resource management.

When departments rely on manual provisioning of cloud resources, inefficiency and higher costs often occur. For example, if unscheduled processes suddenly arise to compete with scheduled tasks, it’s easy for IT to set up virtual machines on the fly—and then forget to turn them off when they are no longer needed. It’s understandable, since off-premise resources are less visible. But virtual machines left running long after they are needed produce unnecessary costs and wasted resources.

Without intervention, IT will apply the same utilization principles to virtual machines as they do to  physical machines. This creates a proliferation of virtual machines left running and forgotten without any benefit to the business, a condition known as VM sprawl. Organizations that don’t address VM sprawl can incur thousands of dollars in needless cost overruns every month.

But the challenges don’t stop there. Even with the flexibility of the cloud, IT needs to balance resources to ensure critical business workflows (e.g., transaction processing) are prioritized and executed on a timely basis alongside less critical processes such as database imports or file transfers. It’s easy for critical workflows and jobs to be delayed—or to fail altogether—when on-premise, cloud and virtual resources are mismatched or spread too thin.

To address these issues, many enterprises are turning to intelligent workload automation solutions.  While these tools have been around for years, the debut of intelligent automation is a major shift that allows enterprises to manage and coordinate virtually every aspect of IT—especially cloud utilization.

One of the most valuable benefits in this regard is just-in-time provisioning, allowing organizations to automatically scale resources on a moment-by-moment basis according to preset business rules. When workloads are heavy and more computing power is needed, automation can spin up more machines and then spin them down during idle times. Just as a smart thermostat raises and lowers the temperature to fit current needs, an intelligent automation solution can add computing power when needed, then de-provision the resources immediately after.

The JIT aspect is enhanced by the use of reactive and predictive analytics. Predictive analytics leverages historical usage information to anticipate future needs. If an upcoming “rush” in computing resources is foreseen, the automation platform can order up an exact amount of capacity to satisfy the demand. If the cloud is a power outlet, analytics can ensure that the organization pays only for what power it uses.

Intelligent automation can create a hybrid IT environment that is optimized in real-time. It reduces potential bottlenecks and eliminates the need for manual intervention. It can also monitor SLAs by automatically changing job priorities and cordoning off servers so that essential workflows can be executed.

Intelligent automation also makes it possible to simplify IT management by building relationships between tools. Most large IT organizations have anywhere from three to eight job schedulers or automation tools, most of which come from one or more of three categories: applications; operating systems; and infrastructure, virtualization and grid platforms.

While it’s not necessary to abandon these schedulers, one comprehensive, cross-platform automation solution allows IT to develop unified job strategies as well as coordinate execution of mission-critical tasks. Just as important, end-to-end automation provides a single point of control for overseeing and tracking the multiple applications, operating systems, and mix of physical and virtual resources involved.

For organizations seeking to transition to an intelligent automation solution, a variety of migrating strategies are possible. One is to use the automated tool that comes with most packages to transfer jobs, plans and objects. Another is the start-from-scratch approach, wherein the IT staff builds all jobs and workflows anew; this approach is appropriate when old workflows no longer fit the organization’s current or future business needs.

The third migration option, and one that’s preferred for most larger operations, is a hybrid approach. Starting with the transfer of existing processes using the new application’s migration tool, the organization builds out new processes on a forward basis, reconstructing or rebuilding existing processes only as needed. In most cases this is the best choice because it enables IT to not only mitigate the risk of losing critical workflows and processes, but also reduce errors caused by manual transfer. At the same time, it provides more flexibility to adjust and improve processes where appropriate.

No one would disagree that the introduction of cloud computing has given enterprises greater capabilities and opportunities than ever. Using this vast new resource efficiently, however, is something most IT departments are still learning to master. With intelligent IT automation as a key management tool, it’s possible to maximize the benefits and minimize the risks of such a powerful innovation.

Ben Rosenberg is President and founder of Advanced Systems Concepts, Inc. (ASCI), an IT automation leader serving nearly 2,000 enterprise customers in 47 countries. To learn more, visit

Copyright © 2016 IDG Communications, Inc.

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