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3 Compute Strategies for AWS Cost Optimization That Work

3 Compute Strategies for AWS Cost Optimization That Work

Friday November 16, 2018,

4 min Read

AWS enables its users to gain a significant edge in terms of operational costs over the traditional hosting modes. While Amazon has been constantly cutting down the costs to encourage long-term adoption of the cloud, however, it has not resulted in any reduction in the cost spend. Organizations are still struggling to reduce their cloud overheads and capitalize on resource efficacy. AWS cost optimization must be the priority with every organization big or small. There are many ways to achieve this goal although the best practices may vary from one organization to another. The following tips will work across all regions and help in accomplishing the objectives of cost reductions.

Is the supply and demand identical?

AWS is highly elastic and allows on-demand availability. Unlike in the traditional model, AWS offers an automated up and downscaling mechanism. To achieve AWS cost optimizationevaluate your Amazon Elastic Compute cloud (AWS EC2) needs and spend.


EC2 are virtual machines were first initiated in the year 2006 and over the period brought in services that improve efficiency, resiliency, and serverless computing. These are being achieved by features like Auto Scaling, AWS EC2 Container Service, Elastic Load Balancing and AWS Lambda. Optimization in costs will be realized only when you use the most appropriate instance for each of your workloads.

AWS EC2 instance Types delivers a wide range of plans and sizes to match the needs of different users. You can choose from a variety of plans with different capacity of storage, memory, CPU, networking etc. Choosing the right combination will benefit you enhance performance in a cost-effective way. Analyze and understand your workload requirements.

Look at different options to maximize the benefits that Spot Instances and Reserved Instances allow. You can reduce AWS costs anywhere between 30% to 90% cost savings. It is necessary that pick an Instance type that is nearest to your workload compute requirement and start benchmarking.

Reserved Instances (RI):

Reserved instance is an upfront commitment that the clients make. It makes sure the resources in the Availability Zones are always accessible. This will bring down the hourly rate billing and maximize cost efficiency by continuing to use the same instance for different workloads that are time-dependent. You could start the RI for a project that works in the day hours and rather than shut it down, continue using the RI for another workload that runs after peak office hours and requires similar instance type. 

RI is offered on annual contracts. Your needs will change and one way of achieving AWS cost optimization is to re-model your instance type. AWS allows you to change the initial instance configuration without applying any penalties

Auto Scaling

The AWS EC2 capacity can be moved up and down to match the evolving workload conditions. In the traditional models, the customers determine the hardware requirements taking into consideration the maximum usage. It is not possible to scale down which creates wastage when you do not require the full capacity. This does not happen in the cloud. Auto-scaling achieves AWS cost optimization by allowing you to increase or reduce the instances and capacity as per demand. You can configure the resource according to the workload peak and off-peak by adjusting the instance utilization. Scaling is one of the best features of the cloud as it helps you have greater efficiency since you pay only for what you consume.

Spot Instances:

Spot Instances means bidding for the unutilized EC2 capacity. They are often available at a lower price when you compare it with the On-Demand pricing. Users can grow their application’s throughput and compute capacity. Leveraging the Spot Market can accomplish AWS cost optimization and reduce operational costs significantly. 

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