How To Optimize AWS Costs: 8 Best Practices For Reducing Costs

Amazon web services (AWS) is the most popular cloud in the world. Its widespread adoption has led to a lot of unoptimized and cost inefficient systems, causing money loss. AWS cost optimization has become an important step in AWS systems development and support. In this article we share best cost reducing practices for AWS systems and cost reducing approaches to AWS design.

Reasons For Optimizing Costs On AWS

  1. Increase cost efficiency: One of the primary reasons for cost optimization on AWS is to save money. By optimizing their AWS resources, companies can avoid paying for unused or underutilized resources. This includes right-sizing instances, choosing appropriate storage solutions, and efficiently managing data transfer costs.

  2. Improved resource management: Cost optimization helps in better resource management. By analyzing and understanding their AWS usage, companies can identify inefficiencies and redundancies, leading to more effective use of resources.

  3. Scalability and flexibility: Cost optimization ensures that the scalability benefits of AWS are utilized efficiently, allowing businesses to adapt quickly to changing needs without incurring unnecessary expenses.

5 Cost Reducing Approaches to AWS Design

Preventing a problem is always better than treating it. Before developing an AWS-based system, consider implementing cost-saving approaches to AWS design from the get-go.

  1. Elasticity: Design your system to scale resources up or down automatically in response to demand. This principle helps you pay only for the compute resources you need at any given time, avoiding over-provisioning and underutilization.

  2. Use the Right Pricing Model for the Job: AWS offers a variety of pricing models like On-Demand, Reserved Instances, Savings Plans, and Spot Instances. Understanding and selecting the right pricing model for each component of your system can result in significant cost savings.

  3. Benefit from Multi-Tenancy: By leveraging multi-tenant architectures on AWS, you can share resources across multiple users or services. This allows for better utilization of resources, leading to cost reductions, especially in environments like Amazon RDS or Amazon ECS.

  4. Cache to Reduce Costs: Implement caching to reduce the load on backend systems and decrease the cost of database reads and writes. Services like Amazon ElastiCache or using Amazon CloudFront for content delivery can effectively reduce costs.

  5. Incorporate Cost-Aware Architecture: Design your architecture with cost in mind from the beginning. This includes selecting the most cost-effective resources and services, designing for deletion (like automatically deleting old snapshots or unused volumes), and architecting for serverless solutions where appropriate.

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How To Choose An AWS Pricing Plan For Reducing Costs?

AWS offers several pricing models, allowing users to choose the best option based on their specific needs and usage patterns. Understanding these models can help in optimizing costs effectively.

  1. On-Demand Pricing: This is the most flexible pricing option. You pay for compute capacity by the hour or second (depending on the instance type) with no long-term commitments or upfront payments. It's ideal for applications with short-term, irregular workloads that cannot be interrupted.

  2. Reserved Instances (RI): RIs offer a significant discount (up to 75%) compared to On-Demand pricing, in exchange for committing to use a specific instance type in a specific region for a term of one or three years. There are different types of RIs:

    • Standard RIs: Offer the most significant discount and are best for steady-state usage.

    • Convertible RIs: Provide flexibility to change the attributes of the RI as long as the changes result in the creation of RIs of equal or greater value.

    • Scheduled RIs: Allow you to reserve capacity within a specific time window on a recurring basis.

  3. Savings Plans: This is a flexible pricing model that offers lower prices than On-Demand, in exchange for a commitment to a consistent amount of usage (measured in $/hour) for a 1 or 3-year period. AWS offers two types of Savings Plans:

    • Compute Savings Plans: Provide the most flexibility and help save up to 66% over On-Demand. They apply to any EC2 instance regardless of region, instance family, operating system, or tenancy.

    • EC2 Instance Savings Plans: Apply to a specific instance family within a region and can save up to 72% over On-Demand.

  4. Spot Instances: This pricing model offers the ability to purchase unused EC2 capacity at a significant discount (up to 90% off the On-Demand price). Spot Instances are ideal for flexible, fault-tolerant, and stateless applications like big data, containerized workloads, CI/CD, and other test & development workloads.

  5. Pay-As-You-Go: This applies to other AWS services (like S3, RDS, Lambda) where you pay only for what you use with no upfront costs. Pricing depends on the service and the specific usage like the amount of data stored, the number of requests, or the duration of resource use.

  6. Dedicated Hosts: This pricing model is for physical servers fully dedicated for your use. It can help in reducing costs by allowing you to use existing server-bound software licenses and can also meet compliance requirements.

Which Tools To Use For AWS Cost Management

To reduce and monitor AWS costs effectively, there are several tools provided by AWS, as well as third-party options. These tools help in understanding, managing, and optimizing cloud costs. We suggest using native AWS native tools as they tend to be more accurate.

AWS Cost Explorer

This is an intuitive and user-friendly interface that enables you to visualize, understand, and manage your AWS costs and usage over time. You can view detailed cost breakdowns, forecast future costs, and identify trends and cost-saving opportunities.

AWS Budgets

AWS Budgets allows you to set custom budgets to track your cost and usage from the simplest to the most complex use cases. You get alerts when your costs or usage exceed or are forecasted to exceed your budgeted amount.

AWS Trusted Advisor

This tool provides real-time guidance to help you provision your resources following AWS best practices. It offers recommendations to optimize your AWS infrastructure, increase security and performance, and reduce overall costs.

AWS Price List API

The AWS Price List API gives you programmatic access to pricing information for all AWS services, enabling you to model and forecast your costs using your own tools and systems.

AWS Cost and Usage Report (CUR)

This delivers the most comprehensive set of AWS cost and usage data available, providing you with detailed insights into your spending patterns and the ability to perform complex cost analyses.

AWS Cost Optimization Best Practices

Identify Amazon EC2 Instances with Low Utilization

Identifying Amazon EC2 instances with low utilization is a crucial AWS cost optimization practice. This process involves monitoring and analyzing your EC2 instances to determine if they are underutilized, meaning they're not being used to their full capacity.

Low utilization typically refers to EC2 instances that have low CPU, network, or disk I/O activity over a significant period. This can be a sign that the instance is oversized for its workload, leading to unnecessary costs. Here a 5 steps to identify low utilization:

  • Monitoring and Metrics: Use Amazon CloudWatch to monitor metrics such as CPU utilization, disk I/O, and network throughput. Setting up the right metrics is crucial for accurately assessing whether an instance is underutilized.

  • Analysis Period: Analyze these metrics over an appropriate period. A short period might not give an accurate picture, especially for instances that have variable workloads. A longer duration, like a week or a month, can provide a more comprehensive view.

  • Utilization Thresholds: Establish utilization thresholds to define what "low utilization" means for your context. For example, you might consider an instance underutilized if its CPU utilization is consistently below 10-20%.

  • AWS Trusted Advisor: Utilize AWS Trusted Advisor's "Low Utilization Amazon EC2 Instances" check. This feature automatically reviews your EC2 instances and identifies those running at low capacity.

  • Cost and Usage Reports: AWS Cost and Usage Reports can also help identify underutilized instances by correlating cost data with usage metrics.

Once the instances with low utilization, you can:

  • Downsize them to to a smaller instance type or terminating the instance if it's no longer needed,

  • Implement autoscaling to adjust the number of instances automatically based on demand,

  • Consider purchasing Reserved Instances for predictable workloads, or use Spot Instances for flexible, interruptible tasks.

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Use or Sell Underutilized Reserved Instances

The practice of using or selling underutilized Reserved Instances (RIs) is a significant aspect of cost optimization in AWS. Reserved Instances provide a substantial discount (up to 75%) compared to On-Demand pricing in exchange for committing to a specific instance type and usage for a 1 or 3-year term. However, if these RIs are not fully utilized, it can lead to unnecessary costs.

Regularly monitoring the utilization of your Reserved Instances using AWS Cost Explorer and other AWS tools can help you track how much of your RI capacity is being used and determine if there are Reserved Instances that are consistently underutilized. This could be due to changes in your application needs or overestimation of required capacity at the time of purchase.

Strategies to Optimize RI Utilization

  1. Modify RIs: AWS allows you to modify certain attributes of your Reserved Instances, such as the instance family, size, Availability Zone, scope (regional or Availability Zone), and network platform. These modifications can help align your RIs more closely with your actual usage.

  2. Consolidate Workloads: Adjust your workloads to make better use of underutilized RIs. This might involve consolidating smaller workloads onto reserved instances or re-architecting applications to fit the RI specifications.

  3. Autoscaling with Reserved Instances: Combine autoscaling with your Reserved Instances to ensure that your baseline capacity is covered by RIs while allowing for scalability.

If you find that you have excess Reserved Instances that you're unable to utilize effectively, AWS offers the option to sell them on the AWS Reserved Instance Marketplace.

Set Up Cost Alerts

Setting up cost alerts is a proactive AWS cost optimization practice that can significantly help in managing and controlling cloud expenses. These alerts notify you when your costs exceed or are projected to exceed predefined thresholds, enabling timely intervention to prevent budget overruns.

Alerts can help you identify unexpected increases in usage or costs, allowing for quick action to address the issue.

AWS Budgets allows you to set custom cost and usage budgets. You can define the amount you expect to use or spend, and then get alerts when your costs or usage exceed (or are forecasted to exceed) your budgeted amount. When setting up a budget, specify parameters like the total cost or usage, the period (monthly, quarterly, or annually), and the services or accounts to be monitored.

Decide on the thresholds for your alerts. For instance, you might want to receive an alert when you've reached 50%, 80%, and 100% of your budgeted amount. Customize alerts based on different criteria, such as specific services (e.g., EC2, S3), tags, or even by individual resources.

Use DynamoDB Instead of RDs

Opting for Amazon DynamoDB instead of Amazon Relational Database Service (RDS) can be a strategic cost optimization practice in certain AWS use cases. While RDS is a great option for traditional relational database needs, DynamoDB, a NoSQL database service, offers a different pricing model and scalability features that can lead to cost savings under the right circumstances.

RDS is a relational database service that supports various database engines like MySQL, PostgreSQL, Oracle, SQL Server, and Amazon Aurora. It's ideal for applications that require complex transactions, joins, and other relational database operations.

DynamoDB is a fully managed NoSQL database service known for its fast and predictable performance. It's suitable for applications with large-scale, low-latency requirements, such as mobile, web, gaming, ad tech, IoT, and many others.

Cost Benefits of Using DynamoDB

  1. Pricing Model: DynamoDB offers a pay-per-request pricing model for read and write requests, making it cost-effective for workloads with unpredictable traffic patterns. You pay for the storage and the throughput you consume without the need for upfront capacity planning.

  2. Scalability: DynamoDB scales automatically to accommodate high throughput with minimal latency, which can be more cost-efficient than manually scaling an RDS instance.

  3. Managed Service: Being a fully managed service, DynamoDB eliminates the overhead of managing a server and performing database maintenance tasks, potentially reducing operational costs.

  4. Data Storage Costs: For applications requiring large amounts of data with infrequent access, DynamoDB can be more cost-effective due to its storage pricing structure.

When to Choose DynamoDB Over RDS

  • Applications that require rapid access to large amounts of data, such as real-time bidding systems or online gaming platforms, can benefit from DynamoDB’s performance model.

  • If your application experiences highly variable workloads, DynamoDB’s ability to automatically scale and its pay-per-request model can lead to significant cost savings.

  • When your application doesn't require complex joins, transactions, or other relational database features, and can work with a simpler, key-value or document data model.

  • Projects that prioritize development speed and simplicity might benefit from DynamoDB’s managed nature and straightforward data model.

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Use CloudFront

Using Amazon CloudFront, AWS's Content Delivery Network (CDN) service, is an effective cost optimization practice for distributing content with high efficiency and low latency. CloudFront works by caching content in edge locations closer to the end-users, which can lead to various cost benefits.

Key Benefits of Using CloudFront for Cost Optimization

  • Reduced Data Transfer Costs: CloudFront can lower the cost of delivering content by caching it in edge locations. This reduces the need to repeatedly fetch data from the origin server, which is often more expensive in terms of data transfer costs.

  • Improved Performance and Reduced Load on Origin: By caching content at edge locations, CloudFront reduces the load on your origin resources (like Amazon S3 or EC2 instances). This can decrease the need for scaling these resources to handle peak loads, thereby reducing associated costs.

  • Pay-As-You-Go Pricing: CloudFront offers a pay-as-you-go pricing model. You pay only for the data transfer and the number of requests that CloudFront handles, which can be cost-effective for many usage patterns, especially when compared to maintaining a global infrastructure for content delivery.

  • Bandwidth Optimization: CloudFront’s intelligent routing optimizes data transfer paths, reducing the amount of data transferred and potentially lowering costs.

  • Free Tier Usage: AWS offers a free tier for CloudFront, which includes a certain amount of data transfer and request handling each month. For small-scale or new applications, this can significantly reduce costs.

Use Autoscaling

Setting up Auto Scaling in AWS is a strategic cost optimization practice that ensures you are only using and paying for the resources you need. AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost.

Auto Scaling automatically adjusts the number of resources in response to demand. This includes scaling resources up during demand spikes to maintain performance, and scaling them down during quieter periods to reduce costs.

AWS Auto Scaling can manage scaling for multiple AWS resources such as Amazon EC2 instances, Amazon ECS tasks, Amazon DynamoDB tables and indexes, and Amazon Aurora Replicas.

Benefits of Auto Scaling for Cost Optimization

  1. Pay for What You Use: By automatically scaling resources to match demand, you only pay for the resources you need, when you need them.

  2. Improved Efficiency: Auto Scaling improves resource utilization, ensuring that you're not over-provisioning (thus overspending) or under-provisioning (which could affect performance).

  3. Responds to Changing Demands: It dynamically adjusts capacity in response to real-time changes in application traffic, making it ideal for applications with variable workloads.

Best Practices

  • Before implementing Auto Scaling, ensure your instances are right-sized for your workload to avoid unnecessary scaling.

  • Use cost-effective instance types and consider using a mix of On-Demand, Reserved, and Spot Instances for your Auto Scaling groups.

  • Choose scaling metrics that accurately reflect your application's performance and load.

  • Implement scaling in a way that minimizes disruptions to your service. This includes considering application startup times and dependencies.

  • Use lifecycle hooks to perform custom actions as Auto Scaling launches or terminates instances.

Terminate Sessions

The practice of terminating idle or unnecessary sessions in AWS is a straightforward yet effective cost optimization strategy. This approach involves identifying and discontinuing sessions that are not actively being used, thereby reducing unnecessary resource consumption and associated costs. This is particularly relevant for services where costs are incurred based on session duration or resource usage, such as Amazon EC2 instances, RDS instances, or other services that maintain session states.

Idle sessions are those where the resources are running but not actively being used. This could be due to users forgetting to log out, applications not releasing resources, or processes that have completed their tasks but remain active.

These idle sessions continue to consume resources and incur costs, even though they are not contributing any value to the business operations.

Benefits of Terminating Sessions

  1. Cost Savings: By terminating idle sessions, you stop incurring charges for those resources, leading to direct cost savings.

  2. Resource Optimization: Freeing up unused resources allows for better utilization of your AWS environment, ensuring that resources are available for active and critical workloads.

  3. Improved Security: Terminating sessions, especially those that are idle or have been inactive for an extended period, can also enhance security by reducing the attack surface.

Implementing Session Termination

  1. Monitoring and Identification: Use monitoring tools like AWS CloudWatch to identify idle sessions. Set up metrics and alarms to detect when a session becomes inactive or remains idle for a predefined period.

  2. Automated Termination Policies: Implement automated policies to terminate sessions after a certain period of inactivity. For example, auto-terminate EC2 instances or RDS instances that have been idle for a specific duration.

  3. User Education: Educate users and developers about the importance of manually terminating sessions when they are no longer needed.

  4. Scheduled Termination: For predictable workloads, schedule session termination at times when the resources are known to be idle, such as after business hours or on weekends.

  5. Lifecycle Hooks and Scripts: Utilize lifecycle hooks and automation scripts to gracefully terminate sessions, ensuring no critical operations are interrupted.


Effectively managing and reducing AWS costs is a multifaceted approach that requires a combination of strategic planning, continuous monitoring, and utilizing the right tools and services. 

Remember, cost optimization in AWS is not a one-time task but an ongoing process. Regular reviews and adjustments to your AWS environment, aligned with changing business needs and technological advancements, are crucial for maintaining cost efficiency. By staying informed and proactive in managing your AWS resources, you can ensure that you're maximizing the value of your cloud investments while keeping costs under control. This balance is key to leveraging the full potential of AWS in supporting your business goals in a cost-effective manner.

How To Choose An AWS Development Partner

Choosing the right AWS development team is crucial for the success of your cloud-based projects. The team’s expertise, experience, and approach can significantly impact the efficiency, cost-effectiveness, and overall quality of the deployed solutions.

  1. Assess their experience in handling AWS projects, especially those similar to your requirements. Experience in a diverse range of AWS services and solutions is a strong indicator of their ability to handle complex cloud challenges.

    Businessware Technologies has a vast portfolio of AWS projects, from simple in-cloud apps to complex systems with sophisticated cloud infrastructure.

  2. The team should have a deep understanding of AWS architectural best practices, including serverless architectures, microservices, and containerization, to ensure scalable, reliable, and efficient solutions.

    We at Businessware Technologies have years of experience in developing complex AWS applications. We create in-cloud apps that are both efficient and cost-effective.

  3. Given the critical importance of security and compliance in the cloud, ensure that the team is well-versed in AWS security best practices, compliance standards (like GDPR, HIPAA), and has experience in implementing secure and compliant solutions.

    Businessware Technologies is compliant with GDPR, ISO 9001, ISO 27001 standards.