It’s important for cloud customers to understand cloud economics. Cloud costs are dynamic – and hopefully, optimized. However, that’s not always the case. Since optimizing cloud infrastructure is a “technological problem”, there are a number of human biases at play that are not always accounted for.
What is Cloud Economics?
Some articles you’ll find jump directly to the idea that “cloud economics” is a synonym for “saving money”. And while the economies of scale and infrastructure on demand mean that public cloud can save you money over traditional infrastructure, the two terms are not interchangeable.
Shmuel Kliger (founder of our parent company, Turbonomic) explains in this video that cloud economics “is the ability to deliver IT in a scalable way with speed, agility, new consumption models, and most importantly, with a high level of elasticity.”
He further explains this idea in another video – that it’s microservices architecture taking the place of monolithic applications that allows this elasticity and rewrites the way cloud economics works.
Rational vs. Behavioral Economics in the Cloud
The concepts described above are exciting – but before assuming these benefits of speed, agility, etc. will be gained naturally upon adopting any type of cloud technology, we need to remember the human context. Taken from the perspective of rational economics, cloud users should always choose the most optimized cloud infrastructure options. If you’ve ever seen a whiteboard diagram of the cloud infrastructure your company uses, or taken a peek at your organization’s cloud bill, you’ll know this is not the case.
To understand why, it’s beneficial to take a behavioral economics perspective. Through this lens, we can see that individuals and businesses are often not behaving in their own best interests, for a variety of reasons that will vary by the individual and the organization… and perhaps by the day.
Economics of Cloud Costs
Cost is particularly dependent on where you sit within an organization and the particular lens you look through. For example, the CFO might have a very different view from the engineering team. Here’s a great talk and Twitter thread on the cultural issues at play from cloud economist Corey Quinn.
Examples of cognitive biases impacting cloud cost decision making include:
- Blind spots – there are always going to be higher priorities than costs – including but not limited to speed of development and performance. Additionally, many engineering and development teams don’t believe it’s their job to care about costs. Or at least, engineering departments are seen less as cost centers and more as profit centers by generating value. Cost optimization is tacked on at the end of a project and doesn’t receive much attention until it spirals out of control.
- Choice Overload – the major cloud providers now offer an enormous number of services – AWS had 190 at our last count – more than any one person can easily evaluate to determine if they’re using the best option. Similarly, most users have a poor understanding of the total cost of ownership of their cloud environment and don’t actually know what cloud infrastructure exists.
- The IKEA Effect – people place a disproportionately high value on products they partially created. Developers may hang on to unoptimized infrastructure, because they created it, and it would hurt to let it go, even if it’s unnecessary to keep.
(There are plenty more, but perhaps we’re falling prey to the bias bias and some of these decisions are perfectly rational.)
The point is that despite the automated buzz of AI and robotic process automation, the cloud doesn’t inherently manage itself to optimize costs. You need to do that.
Cloud providers’ management environments are confusing, and do not always encourage users to make good decisions. Luckily, the wind has started to blow the other way on this front, as cloud providers realize that providing cost optimization options provides a better user experience and keeps them more customers in the long run. We’ve started to see more options like Google’s Sustained Use discounts and AWS’s new Savings Plans that make it easier to reduce costs without impacting operations. However, it’s up to the customer to find, master, and implement these solutions – and to know when cloud native tools don’t do enough.
How to Set Yourself Up for Success & Start Saving
The good news is that being aware of natural tendencies that impact cost optimization is the first step to reducing costs.
Determine Your Priorities
First, determine what your goals are. What does “cost saving” mean to you? Does it mean reducing the overall bill by 20%? Does it mean being able to allocate every instance in your AWS account to a team or project so you can budget appropriately? Does it mean eliminating unused infrastructure?
Understand Your Bill
No matter what your goal, you need to understand your cloud bill before you can take action to reduce costs. The best way to do this is with a thorough tagging strategy. All resources need to be tagged. Ideally, you will create a set of tags that is applied to every resource, such as team, environment, application, and expiration date. To enforce this, some organizations have policies to terminate non-compliant instances, effectively forcing users to add these essential tags.
Then, you can start to slice and dice by tag to understand what your resources are being used for, and where your money is going.
Review Cost Saving Options
Once you have a better picture of the resources in your cloud environment, you can start to review opportunities to use pricing options such as Reserved Instances or Savings Plans; places to eliminate unneeded resources such as orphaned volumes and snapshots; schedule non-production resources to turn off outside of working hours; upgrade and resize instances; etc.
Designate a Cost-Responsible Party
While engineering teams can do these reviews as part of their normal processes, many organizations choose to create a “cloud center of excellence” or a similar department, solely focused on cloud expertise and cost management. Sysco shared a great example of how this worked for them, with gamification and a healthy dose of bagels as motivating factors for users throughout the organization to get on board with the team’s mission.
Automate Where You Can
On the flip side, there’s only so far food bribery can go. Since, as we’ve outlined in our cloud economics model, changing user behavior and habits is difficult, the best way to ensure change is by sidestepping the human element altogether. Those on/off schedules for dev and test environments? Automate them. Governance? Automate it. Resizing? Automate.