5 Point Guide For Today’s CFO to AWS Cloud Cost Management

We’ve seen a sharp increase in the use of cloud infrastructure over the last couple of years. There’s a range of useful services, various pricing structures with added options for saving costs by various cloud providers like AWS, Azure, Google etc. Because of this, enterprises have the elasticity to scale their existing IT infrastructures in order to match the performance and workload SLA requirements. Whether it’s for enterprise applications, testing, and development, data analysis or building  ecommerce platforms, companies have a number of choices regarding costing options and choosing the specific services that best suit for their work.

However, cloud costs can quickly increase without governance processes in place as team members can spin up infrastructure at will and with so many features and services and if companies don’t optimize their spending, avoidable and unnecessary bills can quickly pile up. Without an adequate understanding of your enterprise cloud spending and IT usage, most companies end up with a bill that is significantly higher than it normally would be. Although selling more products and services allows for bigger profits, but for now, we’ll focus more on reducing the costs associated with managing and operating a cloud infrastructure.

Understanding the various usage and cost structures

Although it may seem to an average person that every cloud infrastructure company offers unique pricing options, there are some similarities and generalized cost classifications, such as user-licensing, resource-by-the-hour (which is offered by almost all IaaS models) and an all-inclusive site license. But even resource and user licensing have a plethora of different tiers, including small vs. large virtual machine or specific functionality license vs. a full access license. It’s important for companies to figure out which tier suits them best early on and which one is most likely to suit them later, as the business continues to grow.

Maximizing cloud efficiency with multi-platform environments

Reducing cloud costs can also be accomplished by using just the right networks, servers and storage to handle your particular application workloads. Multi-platform environments like AWS BeanStalk are ideal for this type of work, as they can automatically scale-up or scale-down workloads which are best suited based on your scaling parameters like application usage or traffic or visitors or system parameters like CPU/Memory/Network etc. This workload-specific approach allows specific tasks to run significantly better and faster. As requests are being assigned and handled automatically,  you focus only on the most pressing task in order to maximize efficiency through the auto-scaling approach and, in turn, reduce the costs required to operate them.

AWS and Reserved Instances

Since Amazon Web Services are currently dominating the marketplace, most CFOs are looking for new ways to optimize it in order to tip the scale regarding cost and profit margins. When it comes to AWS, the Reserved Instances can actually be re-purposed to suit different workloads in your business without suffering a penalty. Reserved Instances are basically discounts that companies get for their upfront commitment. They have lower costs of usage per hour, but RI’s will only work if the instances are going to be consistently used.

AWS and Spot Instances

The single most overlooked feature that truly differentiates AWS from many cloud infrastructure solutions is the Spot Instances and Spot Market. These represent the spare capacity usually available at rather large discounts and operate in an auction-based model pricing. They are best used once the company has determined exactly what kind of task it needs to execute and simply run it using a Spot Instance. By using AWS API’s, you can automate the procurement and usage of Spot instances for your enterprise batch workloads, data cleaning workloads or even use spot instances as part of auto-scaling strategy for enterprise workloads that can tolerate instance failures.

Get the most out of AWS

The average AWS instance uses only around 30% of CPU based on 1000’s of instances analyzed by Botmetric. This means that companies have two-thirds or their operating power sitting idly. Categorizing workload as either memory or CPU intensive is one of the first steps in utilizing instances effectively. Once you’ve realized what your company’s utilization patterns are, identifying the type of instances that push the utilization to a higher percentage becomes easy. Don’t worry about pushing the limits of AWS utilization. Even if the hardware fails, all you have to do is provision another instance using AWS console or API’s through automation.

What most business leaders and IT owners fail to realize is that most cloud providers, including the AWS, offer incremental discounts which are proportionate to the increase in use, these volume discounts are available for Compute, Storage and Network Bandwidth etc. In other words, the more you use, the bigger the discount. Fortunately, these can be used in a myriad of ways and incorporated into existing discounts for an even larger margin for savings. AWS also offers Enterprise Discount Program for large customers that spend over $1 million per annum on their Cloud.

Are you a CFO who is awaiting a complete cloud cost control and governance management on a single platform? Then log onto Botmetric now!