How Hybrid Cloud Costs Are Redefining The Role Of A Cloud Engineer

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How Hybrid Cloud Costs Are Redefining The Role Of A Cloud Engineer

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A key technology trend we’ve seen recently in enterprise organizations is the increasing adoption of multiple clouds and hybrid cloud environments, combining on-premises private clouds and public cloud services. IDC predicts that “by 2020, over 90% of enterprises will use multiple cloud services and platforms.” We have a prediction too: that a lot of these enterprises are in for a rude shock—a cloud cost shock.

Multi and hybrid cloud adoption has made it harder to predict cloud spend accurately. The benefits of using multiple private and public cloud platforms seem to be obvious when you start the journey – meeting diverse IT needs, avoiding vendor lock-in, right cloud for the right application, etc. However, some of the harsh truths of a multi-cloud environment only start to hit home when the monthly bills start to come in. Cost optimization and containment become top priorities for enterprises if they want to utilize multi-cloud benefits truly. However, whose problem is it anyway? Traditional IT admins, finance or cloud infrastructure and operations teams? who is really responsible for keeping cloud spending in check?

Traditionally, engineering teams have had to create large capital expenditures (CapEx) justifications for the purchase of on-premises hardware and software. Without a crystal ball to help them, they had to predict the outcomes of a technology investment in clear financial terms for a period of several years. The advent of multi-cloud environments enables IT teams, to balance CapEx spending and infrastructure consumption on-premises versus OpEx spending in the cloud. This turns multi-cloud cost into something potentially unexpected: an engineering problem.

Financial Modeling of Cloud-Based Technology Costs

Hybrid cloud cost optimization requirements have created a shift in the way IT teams think about technology costs. In a world of unlimited resource capacity that can be made available and scaled up with a single click, it can be difficult to predict or control OpEx spending on cloud consumption. Variability in the use of cloud computing resources has pushed ownership of cloud cost management onto engineering teams, making them fully accountable for what they consume. It’s not a buffet where you can help yourself freely and someone else picks up the tab; engineering teams need to plan for and be accountable for the cloud resources they consume.

As hybrid cloud adoption increases, the skills and time involved in cloud cost optimization continue to grow. Unused public cloud instances or workloads running in the public cloud that are better suited for private cloud can result in large, unnecessary costs that could then start to weigh on the company’s bottomline. Cloud operations teams may be unable to avoid cloud wastage without tools that help them analyze data granularly, identify the cost drivers quickly and make intelligent recommendations to right-size cloud resources.

Some of the most essential multi-cloud cost management use cases are:

  • Save and reserve: Engineering teams must track usage and expenditures to optimize cloud costs. 

  • Budget and chargeback: It’s a difficult animal to track cloud costs when users can just swipe a credit card with no controls or tracking.

  • Forecasting and trend reporting: Engineers and IT teams need trendline data to forecast their cloud usage and make informed choices about each new project and application. 

Cloud Cost Optimization with Multi-Cloud Governance

In a multi-cloud world, managing cost becomes just another engineering problem to be optimized. Beam provides the business-level insights necessary to deliver both governance and cloud cost savings. With granular, multi-cloud visualization, your teams can identify cost drivers and optimize cloud decisions for each business unit—and your entire organization.

cloud cost management ,cloud cost ,cloud costs ,cost optimization ,financial modeling

Published at DZone with permission of Riyaz Hyder . See the original article here.

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