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Writer's pictureALIF Consulting

Complete Guide to AWS Cost Optimization

Updated: Jul 12

Cost Optimization is a business-focused, ongoing discipline that helps to increase business value while driving spending and cost reduction (as defined by Gartner Inc. in their glossary). Businesses using the AWS cloud can control their cloud expenses within budget and prevent waste using AWS Cost Optimization. In this article, we go over AWS cost optimization strategies and best practices to aid businesses in getting the most out of their cloud expenditures.


AWS Cost Optimization Pillars


AWS Cost Optimization Pillars

Optimizing Size for Efficiency

AWS has more than 60 different instance sizing options that may be tailored to perfectly match each demand with a given supply. Understanding the demands and objectives is crucial so that firms select the smallest instance that satisfies all requirements.

Utilizing Reserved Instances to Save

Reserved Instances (RI) can guarantee up to 75% cost savings. Organizations can save money by using RI by agreeing to pay for certain resources over time. Here, the requirements need to be carefully examined. A keen eye on CPU usage, RAM usage, storage usage, and network usage aids in identifying instances that can be reduced.

Increasing Elasticity

Elasticity is the main benefit of using a public cloud. Services can be turned off when not in use, making the application flexible. AWS Instance Scheduler's custom start-stop plans for EC2 and RDS instances can be useful. Setting alarms and tracking metrics using AWS CloudWatch enables on-the-fly resource optimization.

Increasing Accountability and Measuring, Monitoring, and Improving

Resource utilization must be continuously measured, monitored, and improved for a cloud architecture to be reliable. This increases accountability and transparency while optimizing cloud deployment. This procedure is tracked by establishing KPIs and metrics to benchmark usage. The team needs to be inspired to work toward the success of the cloud.


AWS Design Principles

Leveraging Cloud Financial Management (CFM)

Organizations should invest in building a robust cloud financial management system. To become more profitable, the entire cloud system needs to be modernized in terms of acquiring knowledge, resources, and processes. This takes time because it takes time for people and systems to become accustomed to the cost-effective mode. Each dollar spent here increases the overall savings.

Pay-as-you-go

Organizations should pay only for the resources being used, keeping a keen eye on idle ones. Pricing should increase or decrease based on the active/inactive resources.

Embrace managed services

Through managed services, AWS reduces the operational burden of managing AWS workload. AWS-managed services should be well-established within organizations. This aids in keeping the operations and services in focus.

Tagging – Track, analyze, and attribute expenditure right

The cloud makes it simple to recognize the services and associate them with the relevant business unit. This makes it clearer how IT expenses should be allocated to each distinct business unit and makes calculating ROI easier.

Track efficiency

To determine the amount of money spent and the profits made, the overall effectiveness of the AWS workload should be monitored.


Top 10 AWS Cost Optimization Best Practices

AWS cost Optimization best practices

1. Identify EC2 Instances with Low Utilization

Finding the Amazon EC2 instances with low utilization is the first step in reducing AWS expenditures. You can locate EC2 instances that are idle or have very low utilizations using the AWS Cost Explorer Resource Optimization tool. You can decide to halt or scale back these instances. You can stop instances automatically with the aid of the AWS Instance Scheduler. On the other hand, resizing EC2 instances automatically is also an AWS Operations Conductor's capability.

Both of these tools operate in accordance with the Cost Explorer report's recommendations. The AWS Compute Optimizer can also help you find instance-type recommendations that might not be amenable to shrinking. The tool can assist you in locating suggestions for downsizing inside or across a group of families, for example. Additionally, there are suggestions for EC2 instances that act as part of an Auto Scaling group and suggestions for reducing performance bottlenecks.

2. Monitoring the use of Storage

Monitoring S3 consumption is mentioned as the second crucial best practice for reducing AWS costs. It is advised to utilise the S3 Analytics tool for at least 30 days to evaluate the storage access patterns on a particular object data set.

It can, therefore, offer trustworthy advice on when to use S3 Infrequently Accessed (S3 IA) storage to cut expenses in particular circumstances. Through Life Cycle Policies, users can automate the movement of things into a low-cost storage tier. To analyse and transfer things to the appropriate storage tier automatically, you might also choose to use S3 Intelligent Tiering.

3. Purchase Reserved Instances

Reserved Instances is one of the methods frequently used to lower AWS bills (RI). Costs for RDS, Elastic Cache, Elastic Search, and Redshift can be decreased with its help. When compared to on-demand pricing, RIs can save you 42%, and you can use them for a whole year with no up-front costs.

You may find assistance in the RI purchase recommendations offered in the AWS Cost Explorer documentation. The suggestions are determined by how you use RedShift, Elastic Search, Elastic Cache, and RDS. Additionally, you must make sure that the parameters are changed to a year with no upfront payments. To ensure efficient AWS cost optimization, you must take a few actions before buying RIs.

4. Identify Low-Utilization Amazon RDS and Redshift Instances

You must utilize the Trusted Advisor Amazon RDS Idle DB instances check to determine the use and cost of Amazon RDS and Redshift instances. You can use it to find database instances that haven't connected in the past week. The Trusted Advisor Underutilized Redshift clusters check for Amazon Redshift can be used to find clusters that haven't connected over the past week.

5. Locate EBS Volumes with Low-Utilization

Finding Amazon EBS volumes with low utilization is the next crucial point to be made in relation to AWS cost optimization best practices. It is obvious that EBS volumes with limited activity, or less than 1 IOPS per day for at least 7 days, are no longer in use.

The Trusted Advisor Underutilized Amazon EBS Volumes Check can help recognize these volumes. To save money, you should also take a picture of a specific volume before deleting it. The Amazon Data Lifecycle Manager can automatically create snapshots of EBS volumes before deleting them.

6. Use Spot Instances

Using Amazon EC2 Spot Instances to manage your AWS costs is unquestionably a solid choice. Spot instances can save expenses by up to 90%, particularly for fault-tolerant applications. Big data, web servers, test and development workloads, containerized workloads, high-performance computing (HPC), and CI/CD are some generic workloads in this context. Additionally, you can launch on-demand and spot instances in accordance with the intended capacity by using EC2 Auto Scaling.

7. Analysis of Amazon DynamoDB Usage and Cost Reduction

Amazon DynamoDB is the most important part of a company's AWS cloud infrastructure. Consumed Read Capacity Units and Consumed Write Capacity Units are two metrics in CloudWatch that you should utilize to analyze DynamoDB. Through automatic scaling of the DynamoDB table, the Auto Scaling function can assist you in reducing your AWS cost.

Make sure that all of your current tables have Auto Scaling enabled. On the other hand, the on-demand option lets you make read and write requests on a pay-per-request basis. Thus, you can strike the ideal balance between performance and expense.

8. Optimization of EC2, Lambda, and Fargate Costs


AWS Lambda Monitoring

Amazon EC2


AWS Fargate








AWS users should also check out the Compute Savings Plans, which are automatically applied to the utilization of EC2 instances. In the case of computing savings plans, factors like family, size, location, AZ, tenancy, or OS are not considered. Additionally, Lambda and Fargate usage are covered under the plans.

Compared to on-demand pricing for a year without advance payments, the Compute Savings Plan can provide savings of about 54%. The charges of computing utilization would be based automatically on discounted prices in the plans after signing up for Savings Plans. Any user who does not sign a contract will be charged at standard on-demand rates.

9. Reduction Of Networking Costs

It's important to include network cost optimization while considering the well-known best practices for AWS cost optimization. Using the Trusted Advisor Idle Load Balancers check tool, you can locate a report of load balancers with Request Count less than 100 over the previous 7 days. To save money, you must now deactivate the load balancers before using Cost Explorer to analyze the data transfer procedure.

In order to allay worries about increased prices for data transport from EC2 to the open internet, Amazon CloudFront can be a dependable option. Any image, static online content, or video might be cached at AWS edge locations all around the world with the use of the Amazon CloudFront Content Delivery Network (CDN). Additionally, CloudFront eliminates the need for over-provisioning capacity to handle a potential increase in traffic.


10. Review and Modification of EC2 Autoscaling Groups Configuration

The evaluation and change of the EC2 Auto Scaling Groups setup is covered by the final recommendation among the best practices for AWS cost optimization. The EC2 fleet can grow and contract as needed with the use of EC2 Autoscaling groups. Through the console or the describe-scaling-activity CLI command, users must review their scaling activity.

You should also assess the outcome in light of the scaling strategy that can be modified to account for the addition of instances. Users should check their settings to ensure that they are using the fewest possible configurations. They can, therefore, respond to end-user demands with smaller fleet sizes.

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