Pre-paid cloud services allow organizations to take advantage of preferential pricing in exchange for an early financial commitment. With the current economic disruption, IT leadership must ensure that the promise of prepaid services is delivered in cost savings. Depending on a few factors (services within your infrastructure and terms of those services), there are ways to find more savings, which is essential in the current economic climate.
Across most major cloud service providers, there are pre-paid discounts for virtualized computing services. Accessing these rates requires committing to a certain amount of time for a lower rate (e.g. AWS’s Reserved Instances). Depending on the terms you agree to (term length, initial pre-payments), there can be multiple lower rates to choose from.
Some of these discounts are very flexible and can be converted to different types and sizes that fit a cloud infrastructure with changing instances (once again, AWS EC2 instances and their RIs come to mind). Specifically with AWS RIs, if you change the service related to the RI, you can convert the RI to the new service to maintain the coverage of the discount. This leads to one tactic that any FinOps team can investigate if looking for ways to save on cloud costs.
Running an elastic, dynamic cloud can result in changing the types of services your teams need as the requirements for those workloads change. While you can optimize for how you utilize cloud services, this can leave a gap between what’s actually used and the pre-paid reservation. What good is a pre-paid, discounted set of cloud services hours if there’s no service to apply it to?
If no one’s job is to ensure that pre-paid discounts are converted to new services or re-applied to like services elsewhere in the infrastructure, it can end up being a sunk cost. Pre-paid discount analysis, such with AWS Reserved Instances, can be a burdensome, error-prone manual task. Instead, use a data analytics tool, like a cloud cost management platform, to help your teams ensure that every pre-paid discount is being applied to an active cloud service.
PRO TIP: Check out this waterline strategy by a popular Australian IT company, where they ensure that their AWS Reserved Instances cover at least 90 percent of their active instances. With their infrastructure changing all of the time, having an automated way of reapplying or adjusting discounts ensures they aren’t paying the full, non-reserved rate for a majority of their services.
There also might be the case where a previously purchased reservation simply doesn’t make sense anymore. It could be a case where services no longer being used sit idly by, or engineers have determined that they no longer need those services. Instead of letting them lapse, try converting those instances into different service sizes or types that your infrastructure actually uses. You can also inform cloud management teams to sell excess reservations on the AWS Marketplace to gain back some of those costs.
Before making any new reserved instance purchases, work with engineering teams to create a process where net new services must find a home within the discounted services portfolio. Much like the example case study linked to above, these kinds of policies ensure that reservations are applied to net new services and help keep coverage levels high.
Note that in small infrastructures, it might be easy to manually report on and convert discounts and reservations as services change. At scale, doing this activity manually can take weeks and be very error-prone. This is where a cloud cost management platform comes in. Use one that has a feature focused on Reserved Instance recommendationsand adjustments using the AWS API. This removes manual changes while ensuring that recommendations and adjustments are backed by real cost and usage data.
If your infrastructure runs multiple cloud services, managing pre-paid discounts gets a bit more complicated. Finding insights manually from these large complex sets of data is also quite challenging.
While AWS has its own set of pre-paid discounts via Reserved Instances, Microsoft Azure has its own system, called Azure Reserved Virtual Machine Instances. Google Cloud Platform users can purchase “Committed Use Discounts” across their compute services. Every platform has a different type of committed usage discount and they must be tracked, analyzed, and adjusted in their own way to map to an ever-changing multi-cloud infrastructure.
The best way to reduce the amount of manual analysis across clouds and to get accurate analytics and recommendations is to find a multi-cloud cost management platform that can ingest and more importantly retain cloud cost data from multiple services and serve them to your teams from a FinOps efficiency perspective.
Just as the cloud leaders continue to innovate on services provided to the masses, they also innovate on their discount programs. The latest alternative to individual pre-paid discounts by service are larger pre-paid plans, like AWS’s Savings Plans. This strategy caters to teams that know they’ll spend a significant budget on cloud with a very elastic and changing infrastructure.
If your teams want to reduce the complexity of how they save on EC2 instances and AWS Fargate setups, the relatively new AWS Savings Plan model might be the way to go. By agreeing to pay a particular rate per hour for a selected term (either one or three years), users can save on EC2 and Fargate services, similar to Reserved Instances.
These discounts may not be as high as normal RIs or as granularly adjustable, but Savings Plans cater to teams that know they’ll use specifically EC2 and Fargate but without knowing how their infrastructures might change or scale. This savings strategy might be the way to go if your teams expect changes in workload and infrastructure needs, but don't want to constantly do the legwork of adjusting or converting RIs, or reconciling unused ones to other services.
Even with an AWS Savings Plan, making sense of those cloud costs requires an additional layer of data and analysis. Use a cloud cost management platform to help your teams understand where each dollar within those Savings Plansare going—by team, department, project, or more—and attribute these costs to real business metrics that your organization might be using.
To ensure that proper information is utilized across your teams, it’s critical to rely on a data analytics-driven cloud cost management platform. Take the manual work out of seeking out efficiency and savings and rely on a proven platform to help you find these opportunities to save and to conquer cloud costs moving forward.
The less time your FinOps experts (technologists, finance, and operations) spend on manually counting costs and building charts, the more time they can spend responding to times of uncertainty to help put your business back on the track toward success.