In an era when artificial intelligence (AI) and other resource-intensive technologies demand unprecedented computing power, data centers are starting to buckle, and CIOs are feeling the budget pressure. To address these issues, IT organizations are increasingly migrating workloads to the cloud to gain operational efficiency and agility.
There are many challenges in managing a traditional data center, starting with the refresh cycle. Server equipment, power infrastructure, networking gear, and software licenses need to be upgraded and replaced periodically. Purchasing, deploying, provisioning, and maintaining all of these pieces is expensive, creating a complex budgeting puzzle that’s difficult to manage.
In addition, enterprise IT must build its infrastructure to manage a maximum load. Unfortunately, for most of the year, a significant portion of equipment may go unused — waiting for peak usage times — such as when an auto manufacturer launches a new model.
How cloud eases IT challenges
When organizations migrate their workloads to cloud platforms, this burden shifts dramatically. In this new paradigm, the underlying hardware becomes transparent to users. Hyperscale cloud providers upgrade and replace equipment behind the scenes without affecting workloads. Just as important, IT pays only for the resources it’s using, and when it needs to scale up, it can easily burst to accommodate dramatically higher loads.
Then there’s the cost of supporting servers.
“For every kilowatt-hour of required server power, traditional data centers may require up to 80% more power for cooling and peripherals,” says Matthias Schorer, head of the Research and Insights Platform at Google Cloud.
Because cloud providers operate at such a massive scale, they can achieve significantly better power usage effectiveness. Not only does this reduce costs but it also translates to a reduced carbon footprint, helping organizations meet sustainability goals.
Migrating workloads to the cloud can also accelerate new development. Take, for example, IT’s plans to deploy a new AI-powered application, which, like many other AI workloads, is hungry for highly performant hardware. IT must determine the resources required; send requests for proposals; negotiate with suppliers; await delivery; and, finally, deploy and provision the new gear. This could take weeks or, more likely, several months to accomplish.
Cloud platforms eliminate these delays, empowering IT to spin up new infrastructure rapidly without complex negotiations or capital expense approvals. This agility is particularly valuable for AI initiatives, especially since they often require rapid scaling.
Making cloud even easier
The partnership between Broadcom and Google Cloud has made it simple to achieve these goals. IT can nondisruptively extend its on-prem environments to the cloud and run its VMware workloads in Google Cloud VMware Engine without downtime or rearchitecting. In addition, the partnership enables VMware license portability between on-prem and Google Cloud environments, providing the enterprise with significant flexibility to move VMs wherever they’re needed.
Admins can maintain a consistent operational view, using the same tools IT has already deployed for on-premises management, which eliminates the need to retrain on new management systems. Additionally, when new updates or patches are available for accessing new functionality, Google manages these requirements for customers as part of the service.
“By moving from a do-it-yourself model to a service model in the cloud, IT frees itself from the burden of managing and maintaining a data center,” says Schorer. “This enables the enterprise to apply the operational savings to future innovations, such as actually determining how to take advantage of AI — instead of spending so much time and money deploying and supporting it.”
Find out how easy it is to migrate your virtual workloads to the cloud to achieve greater operational efficiency with Broadcom and Google Cloud. Find more information by clicking here.
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