The value of various factors will vary based on the organization. Security may be more important at one business than another; the speed at which you can add more capacity might be most important for another; and liability could be critical to others. "That question of value is complicated," Domicity's Brien says.
Valuing redundancy is one factor that many businesses struggle with when transitioning to the cloud.
There are two camps that don't build in redundancy when using cloud services like IaaS, says Mark Eisenberg, who formerly worked on the Azure team at Microsoft and now is a director at IT consulting company Fino Consulting. The first are businesses that simply don't know that, for instance, when moving a workload to AWS they must balance it across regions if they want to avert the repercussions of a regional outage. AWS has been good about releasing white papers and other advice on how to properly do this, Eisenberg says.
In fact, after an outage about a year and a half ago, AWS wasn't particularly sympathetic toward customers that suffered, Eisenberg says. AWS essentially reminded customers that it recommends they build in redundancy.
The second group of customers makes a conscious business decision not to shoulder the cost involved with building in redundancy. "It depends on what they stand to lose," Eisenberg says.
The costs of building in redundancy can be daunting. Take data storage. It costs twice as much to fully replicate data. But there are also architectural decisions to consider. Having two data stores separated by a long distance introduces latency when synching the stores. For many applications, that latency might not matter. But for some types of applications it could create problems.
Cost is a factor for compute redundancy too. Businesses that can tolerate the delay involved with spinning up new cloud-based servers -- usually around five minutes -- can wait until a problem occurs before they fire up backup instances, Fino Consulting's Eisenberg says. Others may run half as many additional servers instead, because they can tolerate some latency with their apps better than they can handle a complete outage for a few minutes.
The scale issues
Architecting scale also is a challenge that comes with cost repercussions. "Just as in the on-premises world where capacity is kind of an art more than a science, it's the same in the cloud," Eisenberg says. "It's easy to say 'I'll just have more capacity than I need,' until you find out the high costs associated with doing that."
SaaS deployments come with their own set of potential cost overruns. SaaS providers often offer their best deals to customers that sign on to multi-year contracts. "So now you have this three-year contract. Maybe you outgrow it or maybe you find another app that does a similar thing but better," explains Connor Sullivan, an analyst at IDC who follows cloud computing. Businesses then feel trapped with an app that's not the best fit or they end up "double dipping" -- signing up for a new service for additional cost, he says.
Businesses also should thoughtfully consider costs over time. It turns out that the price for SaaS apps in general aren't coming down the way that many people once predicted. Historically, the thinking was that with more users of cloud services, economies of scale would reduce costs for users, Sullivan says.
Some providers like Salesforce have true multitenant cloud services and are benefitting from scale. While Salesforce is passing those savings on to customers, it is also continually adding new features, which cost extra for users. "People want those new functionalities and so the cost to the end user hasn't gone down," Sullivan says.