Cloud spend is anticipated to continue its massive growth trajectory for the foreseeable future. However, the spend does not have to match that same growth curve! To help our Clients maintain sound Cloud Optimization programs, we've assembled a series of articles and tips called: 12 for '21 Cloud Optimization Series (note: request a download of all 21 here).
Today we review the fourth installment in the series: Reserve Your Instance
In exchange for an upfront commitment of 1 or 3 years, AWS (“ Reserved instances”), Microsoft Azure (‘Reserved Savings’) and GCP (‘Commitment Price’] offer significant cost savings (anywhere from ~29% up to 72%) on cloud compute resources compared with on demand instances.
Reserved Instance Introduction
Since AWS marketed EC2 in 2006, developers rapidly took advantage of the ease of spinning up and down a wide variety of EC2 instances which, for periodic usage (development and testing) were economically sound. While this ‘pay as you go’ flexibility helped drive adoption by start-ups, steady usage was still expensive at on-demand rates. In 2009, AWS launched a reserved instance pricing model to facilitate and further expand adoption within the enterprise segment. Additionally, a predictable EC2 demand - in the form of instance reservations - makes it reliably easier for AWS capacity planning and financial forecasting. It took several years before other cloud providers would offer a similar pricing model.
The reality of using Reserved Capacity
To a large degree, you are financially locked-in for the term and amount of your reservation commitment. As such, if your workload and compute requirements spend were to evolve and change downward (or your projections were grossly overestimated), you will have to pay for the committed capacity you agreed to, or figure out how to best recycle the committed capacity across other activities. All this implies careful projection planning of future cloud compute usage across your environments. This is a time consuming task whereas you should make best use of your native analytics tools to size the reserved capacity and ensure the right investment.
AWS, Azure and GCP providers offer a large range of instance types with different performance characteristics (CPU, network, memory). AWS offers the widest range with 300 different instances grouped into families that offer specific abilities for your workloads: General Purpose; Compute Optimized; Memory Optimized; Accelerated Computing; Storage Optimized. One of the critical tasks to perform before you lock into a reserved capacity is to pick the right instance type. In order to maximize your capacity investment, the chosen Virtual Machine (‘VM’) should accurately meet the demands of your workloads without over sizing the VM hence, spending more than necessary.
While reserving your instances has clear economic benefits over on-demand, it necessitates a detailed assessment of actual cloud compute usage across your workloads and careful planning of future usage . Only with such planning processes in place, will you maximize the long-term benefits of reserved capacity.
As with any strategic technology issue, problem, question, or concern, give NET(net) a call to help you better understand and optimize your supplier agreements, relationships, and investments. Contact us today, and we’ll get you in touch with the appropriate subject matter experts to help you.
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