AWS Cost Optimization Strategies – A Comprehensive Guide

Cloud service providers like Amazon Web Services (AWS) have completely changed how companies do business. The increasing shift toward AWS shows the reliance of industries on the cloud provider’s scalable, secure, and efficient resources for operational efficiency and growth. In fact, according to the Statista’s Sales Revenue Report 2023, AWS generated a net sales revenue of 131 billion U.S. dollars internationally. 

AWS is one of the world leaders in Gartner’s new Magic Quadrant for Strategic Cloud Platform Services report. Despite that, its extensive infrastructure can confuse many. The pay-as-you-go pricing model can result in unexpected costs from unused resources, thereby affecting your bottom line. Hence, it is necessary to implement AWS cost optimization strategies to manage expenses effectively. 

Doing so will build a capability across your enterprise to develop business-wide programs and processes for efficient management of finances in a way that keeps your agility intact. It will also contribute positively to your journey for growth and modernization. 

What Causes High AWS Costs?

Before implementing AWS cost optimization strategies, you should know the root causes of increased spending. Companies worldwide experience this issue for various reasons. These include:

Unused or Idle Resources

Limited visibility into your AWS resources leads you to overlook underutilised ones. IT teams commonly provision AWS resources but do not use them actively, which increases overall costs. 

For example, unused Amazon EBS volumes reflect on the total AWS costs. The lifecycle of EBS volumes and Amazon EC2 compute instances is different. So, even if you stop using the EC2 instance associated with the EBS volumes, the EBS volumes will not cease to exist. It will terminate only when you choose the Delete on Termination option at launch. 

Thus, your dedicated development team must actively identify the places where unused or over-provisioned resources are and eliminate them. 

Resources Launched Through AWS Services

Many AWS services open different resources and affect your charges. Take Elastic Beanstalk as an example. It relaunches the services you pause or stop, affecting the AWS costs. In order to counteract this, terminating the Elastic Beanstalk environment before terminating resources that Elastic Beanstalk has made is essential. 

Similar is the case with AWS OpsWorks environment. When your teams create AWS resources with this environment, they should terminate those resources with AWS OpsWorks. Otherwise, the resources will restart, leading to a steadily increasing cost.

Improper Configuration of NAT Gateways

Network Address Translation gateway connects instances within a private subnet of an Amazon Virtual Private Cloud to the internet. Through NAT, your private network can communicate with the World Wide Web. 

However, transmitting data through this gateway is expensive because of the numerous fees involved. These include charges by hour, data processing fees for the gateway, and regular EC2 data transfer charges. 

If you are operating a high-traffic website, NAT Gateway data transfer costs will be high. But if you run a simple application, the costs should not be high. If they are, it means the way NAT Gateway is configured is incorrect. 

Over usage of AWS Snapshots

AWS snapshots were for data backup and restoration before the functions were automated by AWS. If your cloud architecture design has an accumulation of old and outdated snapshots, they are directly impacting your AWS costs.

Over-provisioned snapshots do not disturb an application’s operation. However, AWS Cloud bills you for the storage that snapshots use. So, when snapshots accumulate, the total cost increases.

Selecting the Wrong Instance Model

You can purchase instances in three ways. On-demand instances let you pay a preset price for every hour without any commitment. Reserved Instances have a capacity reservation. They provide huge discounts over on-demand rates when you go with long-term instance purchases.

With spot Instances, you offer your rate for instance capacity. This model optimises costs for companies whose solutions have flexible starting and ending periods and can handle service interruptions when instances at the offered price are not unavailable. 

If enterprises choose an instance model without factoring in potential changes in resources or components of workload, it will cause unwanted expenses. 

Wrongly Configured Autoscaling

AWS Auto Scaling adjusts the cloud infrastructure automatically. This happens when demand fluctuates. Auto Scaling is free but the resources scaled through it, like E2 instances are billed according to their use. Thus, when Auto Scaling is not set properly, its effect on resource usage negatively influences the overall AWS bill. 

Not Reviewing Expenses and Usage Reports

The need to implement AWS cost saving strategies becomes pressing when an organisation does not have any arrangement to review the cost and use of AWS resources. When IT teams are unaware of resource usage, spikes, cost drivers, and inconsistencies in spending, your AWS budget goes through the roof. In turn, it makes stakeholders skeptical of continuing with their cloud journeys and modernisation. 

Also Read : Exploring The Various Challenges Of Cloud Computing

Actionable AWS Cost Optimization Strategies for Enterprises

The AWS cost reduction strategies mentioned below will help combat the major causes of increasing expenses mentioned in the previous section. If your expenses are becoming difficult to manage, using the techniques below will aid in budget control.

Assess Your AWS Costs and Usage

Understanding your current AWS costs and usage is imperative to cut expenditures on unwanted services. One of the best AWS cost optimization strategies is using AWS Cost Explorer. This fully AWS managed services allows infrastructure and operations teams to visualise, understand, and manage AWS expenses. 

You can build tailored reports, evaluate data over specific periods you set and forecast future expenses. In order to understand your rising AWS costs and balance them, leverage AWS Cost Explorer as follows:

• Find the major accounts where you are incurring the most costs through the ‘Monthly costs by linked account report.’
• Now, locate the major services that are causing those costs within those accounts through the ‘Monthly costs by service report.’
• Discover the main AWS resources that incur costs using the Hourly and Resource level granularity on Cost Explorer. 
• Group data by account, region, or tags to determine the types of usage that are driving AWS costs.

This process will give you deep visibility into your cloud spending and uncover areas for improvement, which is necessary to reduce costs.

Set Budgets for Each AWS Service

Setting cost budgets is essential to prevent undesired expenses. You can enforce a budget for every cloud services and solutions through AWS Budgets. After configuring it, you will be notified of the following:

• When predicted or real-time use and cost of the service surpass the set budget point.
• When actual Reserved Instances and Savings Plans usage goes below the optimal threshold. 

After this, configure actions in AWS Budget Actions in response to utilisation and cost status. If a threshold is exceeded, the actions you have set will commence to reduce overspending. 

Stop or Right-Size EC2 Under-Utilized Instances

EC2 instances that are sitting idle or have low utilisation lead to unnecessary expenses. So, one of the effective AWS cost optimization strategies is stopping or downsizing them. 

An EC2 instance that is underutilised corresponds with the following criteria: 

• The average CPU usage is under 60% for the last seven days (one week). 
• The average memory usage is under 60% for the last seven days. 

Follow these steps to identify idle EC2 instances and downsize them:

• Use AWS Cost Explorer Resource Optimization to determine the underutilised instances. 
• Use the AWS Instance Scheduler to stop EC2 instances.
• Alternatively, idle EC2 instances can be resized according to the recommendations provided by Cost Explorer through the AWS Operations Conductor.
• Use AWS Compute Optimiser to know which EC2 instance will be suitable for a specific workload. It gives suggestions on how to downsize EC2 instances across groups and how to upsize them to address performance issues.

Lower Your Amazon EBS Costs

Amazon Elastic Block Storage or EBS offers disk storage for every EC2 instance. There are different kinds of EBS volumes, which are the storage for your EC2 instance. If you want to reduce your AWS costs, it is best to locate orphan EBS volumes and unused EBS snapshots and do away with them. 

Orphan EBS volumes are not linked to EC2 instances. So, their data is no longer required. Follow these two steps to delete them as well as unused EBS snapshots. 

• Using the AWS Console, detect orphan EBS volumes and delete them. Do this for every region where you are deploying EBS.
• Use the Snapshots page in the AWS Console to find and eliminate all the snapshots that are not employed. As one of the AWS Cost Optimization best practices, delete snapshots when new ones are created.

Provision Resources Through Cost Allocation Tags

A complete view of units and cost centres generating the most expenses is crucial to managing cloud costs. This is achieved through AWS cost saving strategies like resource tagging. 

In AWS cloud, two specific cost allocation tags are present:

• User-defined AWS Tags: These tags can be about the metrics or projects you want to assess and monitor.
• AWS-generated Tags: AWS makes these tags automatically, which users can turn on in the AWS Management Console.

Use the above tags on AWS Cost Explorer for a comprehensive breakdown of your AWS spending. It will give details on the business units, customers, or projects with the highest costs. As a best practice, create a set of standardised tags to track costs by project, department, or metric of your choice. Also, configure AWS Billing Alarms to monitor costs and get alerts when your resources exceed the preset cost thresholds. 

Transition to Reserved and Spot Instances

Opting for the correct purchasing models significantly minimises the overall expenses of running a workload, making it one of the salient AWS cost reduction strategies. 

If your workload has consistent resource needs, purchasing reserved instances or savings plans saves around 72 per cent more on the cost than the same resources brought using the on-demand instance model. The discount given by Reserved Instances is as per the size of the instance, its region and type. For example, a one-year reserved instance can provide a 10% discount, while a three-year reserved instance can give up to a 15% discount.

Many companies have intermittent workloads or run CI/CD pipelines and containerised workloads. For such cases, investing in Spot Instances is cost-effective. They do not need long-term commitment and are ideal for non-critical applications. 

Sometimes, licensing affects the purchasing models. If your license is not transferable to an instance, invest in Amazon EC2 Dedicated Host. It gives visibility over the instance placement and allows you to launch and run instances on specific hosts you set.

Also Read : Ultimatе Guidе to Cloud Migration Stratеgy

Use Flexible Compute and EC2 Instance Savings Plans

AWS Savings Plans allow you to pay less for using Amazon EC2, AWS Lambda, and AWS Fargate if you commit to using the services fairly consistently for one to three years. The two most economical Savings Plans are: 

• Compute Savings Plans – Compute Savings Plans result in AWS cost reduction of 66%. It is for all EC2 instance usage, including serverless compute engines like Fargate or Lambda. When using it, you can change instances, shift a workload to any location and move it to any serverless compute engine while paying the Savings Plans price.
• EC2 Instance Savings Plans – This plan offers the greatest discount (72%). However, you should use EC2 instance family in a specific region to use it. It saves your expenses on that instance family, no matter the size, operating system (OS) or tenancy. You can pay for a dedicated tenant if there is a need for particular licensing, security, and performance. Unlike Reserved Instances, you can modify the size of your EC2 instance size and OS. 

Combine Autoscaling with Spot Instances & Reserved Instances

Autoscaling, or adjusting the resources according to demand, is one of the effective AWS cost optimization strategies. Cloud Application Development with fluctuating workloads should employ it to set target utilisation levels for different resources. These include Amazon EC2, Amazon ECS, Amazon DynamoDB, Amazon Aurora and Amazon EC2 Spot Fleets.

Autoscaling eliminates your spending on idle resources. It becomes even more potent for cost-saving when combined with Spot Instances and Reserved Instances. For example, you can use Reserved Instances for the minimum usage level and Spot Instances for scaling up. 

The example below will make it clear how AWS Autoscaling with Spot Instances lowers your cost.

Suppose your app operates on twelve instances of C5.xlarge On-Demand instances around the clock (24/7). You give $0.20 each hour for every instance. The monthly cost will be (12*24*30*0.20 = $1,728) $1,728 monthly. 

Spot Instances are offered by AWS at a much lower price. You can configure your Auto Scaling group to employ twelve C5.xlarge Spot Instances and twelve On-Demand instances.

The Spot Instance rate for C5.xlarge in the US-West-2 region comes to around $0.057/hour. Suppose that the Spot Instance rates remain similar, the total monthly cost will be (12*24*30*0.057 = $492) $492. Thus, your AWS cost will be 60% less than using On-Demand Instances. 

Optimise Your Elastic Load Balancing (ELB) Costs

ELB are networking services that deliver application and infrastructure resiliency. They allow you to modify your cloud infrastructure along with the costs they incur as per demand. Hence, you can alter the targets based on the upcoming load.

Implement the following AWS cost reduction strategies with regard to ELB:

• The load balancers are billed on an hourly basis, as well as your LCU usage. So, minimising the number of load balancers and sharing one between several applications can help cut costs. You can utilise target groups and listener rules to shift the traffic to the right application.
• The LCU-hour cost for Network Load Balancers (NLBs) is 25% lower than Application Load Balancer (ALBs). Thus, the decision to use NLB is cost-effective.
• Both ALB and NLB support the reuse of TLS sessions. So, if your organisation supports TLS session reuse, you can configure a previously established TLS session so it is easy to reconnect to the TLS endpoint without transferring many bytes. As a result, there will be significant latency and cost deduction. 
• NLB does not enable Cross-Zone Load-Balancing (CZLB). If you turn on CZLB for NLB, you will incur fees for data transfer charges between zones. This is not true for ALB, which enables CZLB and lets you disable it for target groups.
• Delete the load balancers without any recent usage. Use Trusted Advisor Idle Load Balancers check to find load balancers with RequestCount of less than 100 in the past week and delete them.

Employ a Cloud Cost Observability Framework

Gaining deeper visibility into AWS costs helps you cut unwanted expenses. It is the premise for employing a cloud cost observability framework. Adopting it is one of the effective AWS cost saving strategies primarily because it helps you identify underutilised resources and enhances transparency. 

A cloud cost observability framework is in the form of a platform. It has the following elements:

• Data collection: It gathers comprehensive cost data from cloud service providers like AWS and Kubernetes.
• Monitoring cost patterns: Continuous usage and cost patterns tracking across your teams, resources, and organisational units leads to quick identification of inconsistencies. 
• Cost analysis and recommendations: The platform uses tools to analyse and interpret cost data and derive valuable insights. Also, it gives suggestions for making the cloud infrastructure more efficient.
• Reporting: You can find all your AWS spending trends and cost optimizations that have been implemented in comprehensive reports and dashboards. 

Reduce Data Transfer Costs

Data transfer expenses can be reduced in many ways. One of the salient AWS cost saving strategies is using AWS AppSync, a GraphQL API service. This AWS serverless services streamline application building by providing a central endpoint to query or update data from various sources, such as Amazon DynamoDB and Amazon Aurora RDS. 

The service supports subscriptions. So, you can launch compelling real-time application experiences by publishing data updates to subscribed API clients automatically. This happens through serverless WebSockets connections. AWS AppSync reduces overfetching and, as a result, data transfer out. Alternatively, you can use it incrementally for new updates or app features. 

AWS AppSync cost is according to the pay-as-you-go model. You are charged for each query performed against your GraphQL API, data modification operation against your GraphQLAPI, and real-time updates sent to the clients.

Publishing data is way more inexpensive than pulling data in the AppSync service. AWS only charges you for the size of the published data. But when pulling data, you are charged for the data size that is pulled and the amount of time it takes to pull it. 

Yet another strategy to reduce data transfer costs is to ensure that your Object Storage and Compute Services are in a single region. This will make your data transfer free. However, if inter-region transfers are necessary, a cost-effective approach will be to duplicate your Object Storage bucket to another region, followed by downloading each between regions every time. To test it, use the cross-region replication feature built into Amazon S3. 

Finally, using an AWS cloud delivery network will help you save immensely while reducing your application’s latency. AWS cost optimization strategies like using CDNs also benefit your application’s performance. Cloudfront is essentially a content distribution layer for solutions hosted outside of AWS. 

It is one of the effective AWS Cost saving strategies to optimises the cache hit ratio (percentage of the requests served from the content cached at the edge regions) and saves the expenses of origin request submission. In fact, Arc XP, the Enterprise Agile CMS Solution, minimised data transfer costs by $500k yearly using the CloudFront CDN. 

Minimise AWS Database costs

AWS Relational Database Service (RDS) is central when using the cloud for data management needs. Having a sound understanding of RDS’s expenses is essential to implementing effective AWS cost reduction strategies.

The cost of operating AWS RDS depends on the following: 

• Instance costs – Instance costs are based on the type and size of your chosen database instance. 
• Storage costs – It refers to the storage taken up by your database. It comprises general SSD, Provisioned IOPS SSD and magnetic storage and each has its specific rates. 
• Data transfer costs – Data transfers from AWS RDS to the internet incur charges. Also, as mentioned in the point above, data transfers between AWS services in varying regions incur fees. Contrarily, those within the same region are free.
• Optional features – Features like provisioned IOPS, database snapshots, and multi-AZ deployments have costs associated with them.

You can implement various AWS cost optimization strategies after understanding the cost structure above. These are listed below.

• Analyse your AWS RDS configuration and delete unused or outdated snapshots. 
• Track the utilisation of your resources by tagging RDS instances on Amazon RDS Console.
• Assess the metrics about resource utilisation sent to Amazon CloudWatch to gain insights about AWS cost optimization strategies. 
• Unused RDS instances are without any data connections and have less than 5% CPU usage. Find such instances and delete them immediately. 
• Right-size under-utilised primary RDS instances. These are those instances with CPU usage below 30% and I/O below 30%. 
• Reduce instance costs by half by disabling the Multi A-Z deployments. It duplicates the database in a different Availability Zone but, in doing so, it increases the hardware for database instances and storage. In turn, it replicates your cost. 

Optimise Costs by Selecting the Right Region

You must select a region before using the AWS Management Console and SDK. The right region impacts your operations’ cost and compliance. A region is a geographic area with AWS Data Engineering centres. 

Each region has two or more Availability Zones, which refer to independent data centres located near one another. Availability Zones are used for redundancy and data duplication. The pricing of every AWS region is substantially different. There can be a 30% or 70% price variation for some regions compared to the most inexpensive AWS region. 

In order to get a correct price estimate, use AWS Pricing Calculator. It lets you group AWS services by region and compute the cost estimates for running a specific workload in every region. Also, you can calculate the expenses of running a distributed workload across several regions. After that, select regions in proximity to your target audience to minimise latency for your application.

AWS offers various instances and services in every region. You must assess the specific services and resources that are needed to meet your project requirements. Also, finding a region that supports all AWS services eliminates unwanted inter-region data transfer costs. It is crucial to frequently assess and re-assess every region so you can adjust to the dynamic needs and AWS pricing modifications.

Leverage Cloud Cost Optimization Services

Global enterprises can seek the assistance of professional cloud cost optimization services to lower their AWS bills. The experienced architects and developer teams provide custom solutions to optimise costs after a thorough assessment of your infrastructures. 

Moreover, the professional teams advice on the best practices and provide training to your teams for controlling costs. Continuous 24/7 infrastructure monitoring ensures that enterprises continue to benefit from an optimised and cost-effective cloud environment.

Harikrishna Kundariya

CEO, eSparkBiz

Harikrishna Kundariya, a marketer, developer, IoT, chatbot and blockchain savvy, designer, co-founder, Director of eSparkBiz @Software Development Company where you can Hire Software Developers. His 14+ experience enables him to provide digital solutions to new start-ups based on Web app development.