Complete Guide to AWS Cost Optimization
Updated: Apr 3
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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 by 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
1. 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 of the requirements
2. Utilizing Reserved Instances to Save
Reserved Instances (RI) can guarantee cost savings of up to 75%. By agreeing to pay for certain resources over time, organizations can save money by using RI. 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.
3. Increasing Elasticity
Elasticity is the main benefit of using a public cloud. Services can be turned off when not in use . This makes the application flexible. AWS Instance Scheduler's custom start-stop plans for EC2 and RDS instances can be very useful. Setting alarms and tracking metrics using AWS CloudWatch enables on-the-fly resource optimization.
4. Increasing Accountability and Measuring, Monitoring, and Improving
Resource utilization must be continuously measured, monitored, and improved in order 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
1. Leveraging Cloud Financial Management (CFM)
Organizations should invest in building a robust cloud financial management system. To incorporate the idea of becoming 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.
Organizations should pay only for the resources being used with a keen eye on the idle ones. This pricing should go up or down based on the active/inactive resources.
3. 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.
4. 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.
5. 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
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 side, resizing EC2 instances automatically is also a capability of the AWS Operations Conductor.
Both of these tools operate in accordance with the Cost Explorer report's recommendations. You can also find instance type recommendations that might not be amenable to shrinking with the aid of the AWS Compute Optimizer. 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 parts 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 practise 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, however, you might also choose to use S3 Intelligent-Tiering.
3. Purchase Reserved Instances
Use of Reserved Instances is one of the methods frequently used to lower AWS bills (RI). Costs for RDS, Elasti 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, there are a few actions you must do 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, 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 in recognizing these volumes. To save money, you should also take a picture of a specific volume before deleting the volumes. Before deleting EBS volumes, snapshots of those volumes can be automatically created with the aid of the Amazon Data Lifecycle Manager.
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 a few examples of 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 distinct 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 this method of reducing your AWS cost.
Make sure that all of your current tables have Auto Scaling enabled. The on-demand option, on the other hand, lets you make read and write requests on a pay-per-request basis. You can thereby strike the ideal balance between performance and expense.
8. Optimization of EC2, Lambda, and Fargate Costs
Users of AWS should also check out the Compute Savings Plans, which are automatically applied to the utilization of EC2 instances. In the case of compute savings plans, factors like family, size, location, AZ, tenancy, or OS are not taken into account. Additionally, Lambda and Fargate usage are covered under the plans.
When compared to on-demand pricing for a year without advance payments, the Compute Savings Plan can provide savings of about 54%. The charges of compute utilization would be based automatically at 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.
1. Reduction Of Networking Costs
It's important to include network cost optimization while considering the well-known best practices for AWS cost optimization. You can locate a report of load balancers with Request Count less than 100 over the course of the previous 7 days using the Trusted Advisor Idle Load Balancers check tool. 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.
2. 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.