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How to use intelligent automation to drive better cloud resource management

Ben Rosenberg, President, Advanced Systems Concepts | April 25, 2016
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.

This vendor-written tech primer has been edited by Executive Networks Media 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.

 

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