The 3 stages of cloud economics

Cloud computing promises to cut costs for businesses, but does switching to the service always save money? On the surface, the potential for savings is hard to argue, with costs like $99 (£61) per employee for SaaS applications and $0.08 (£0.05) per hour for virtual servers.

But, as HP’s Joe Weinman has stated, low unit costs alone are not what make public clouds cheaper. What matters most is the resource consumption pattern of your workload.

In reality, cloud costs add up quickly, as more people use the service or more elements are consumed. For example, high ongoing consumption costs are often hidden behind low costs per employee, which can ultimately create a large total bill.

Additionally, cloud prices don’t include the operational costs to use them, and the business continues to incur costs for managing, securing, monitoring, and backing up cloud deployments.

So when does an $0.08 per server per hour pay off?

When it’s not used all the time, and proactively manages the resource consumption of applications that the cloud bill remains low.

The key to cloud economics is using cloud computing optimally, understanding the behavior of the applications and services deployed by the business.

Although blindly buying cloud services won’t lead to substantial savings, understanding the business model can move cloud economics from a cost saver to a profit maker.

While business buyers may provision cloud services themselves, it takes developers and IT administrators to activate infrastructure and platform cloud services, and more importantly, a CIO to bridge understanding between IT and the business.

At Forrester, we’ve identified three stages of economic thinking when it comes to taking advantage of cloud platforms, which each deliver increasing benefits for the business.  Progressing through these stages sequentially and applying the learnings from each stage will help businesses pursue economic value from the cloud. See the chart below.

Stage 1: Scale up — cloud is a no-brainer for transient and elastic applications
The first determination every enterprise should make is which applications and services lend themselves to cloud economics.

Applications deployed for less than 12 months should be put in the cloud so the infrastructure will not induce cost once the program’s life has ended.

Other ideal candidates include transient applications like test and development projects, temporary promotional web pages, or applications supporting seasonal activities.

Any application that scales out is also a good fit for cloud platforms because it can be deployed at a small level and scaled up as traffic increases.

The more an application’s resource needs fluctuate, the better it fits to cloud models.

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