Some organizations mistakenly believe that the public cloud is always cheaper than on-premises alternatives.To calculate the financial impact of moving a workload off premises, networking, workload variability and many other components come into play.
The latency of the network, for example, affects whether the cloud vs. on premises will be more financially sustainable. Low-latency workloads that organizations can easily move back and forth, and don't need to access frequently, should go into the public cloud rather than locally storing massive amounts of data.
"Public cloud is fairly cheap storage," said Fidacaro. "If you don't need access to that data at the moment for analytics, you can just pull that data from the edge or the enterprise up into a public cloud."
Consider how the workload's utilization impacts price. Sustained utilization might be cheaper to run on premises, for example, while a bursty or lightly used workload would be better to run in the public cloud, said Lowe.
Understand the nature of the application. For example, find the percentage of memory and CPU it typically consumes, and determine the size of the cloud instance it would need based on those figures to calculate potential cloud expenses.
"If you move an application to the cloud, all of a sudden, you're creating a tremendous amount of data at that location," said Eastwood. Many cloud models include a premium for the data storage, and it's expensive to move the data back on premises because of cloud expenses such as network taxes and fees.
Assess the financial risk of a potential cloud outage. If an airline's load-balancing application goes down, for example, the entire business is affected.
"There are a lot of places where you can focus your attention to get better returns on that attention rather than some of those high-value applications, where the biggest risk is the loss of access to those applications and the potential loss of data," said Eastwood. "These are things that are very core to the business that you can't afford to disrupt."
As applications become increasingly more distributed, it's essential to understand each of the different external and internal elements of the workload, said Lowe.
"You have to understand the dependencies, interconnections and components of the applications in order to understand what can or should be moved to another location," he said.