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How to Optimize Your AWS Costs, Step-by-step

How to Optimize Your AWS Costs, Step-by-step

Efficiently managing cloud expenses is not just an option, it's a necessity. The complexity of AWS and the need to continuously adapt your cloud infrastructure to the ever changing business needs can often lead to cloud costs spiraling out of control. AWS cost optimization is about extracting the maximum value from AWS services for every dollar spent. It requires a comprehensive understanding of the consumption of AWS services, identification of the primary cost drivers, and strategic implementation of different measures to minimize costs without affecting availability or performance.

Identifying Inefficiencies

Analyzing Cloud Usage

The first step in identifying inefficiencies in your AWS bill is to analyze your usage. AWS Cost Explorer is an essential tool for that: it provides a set of detailed reports that break down your costs and usage, letting you view your data graphically or tabulated and dive deep into specifics. It's particularly useful for visualizing your cost patterns over time, analyzing them in detail, and identifying cost spikes.

Cost Explorer also lets you group and filter cost and usage information by various dimensions, such as service, linked account, or custom cost allocation tags. This is critical for identifying which resources or services constitute the largest proportion of your AWS bill, letting you understand where to focus your cost-optimization efforts. It will also allow you to track the effectiveness of your cost optimization strategies and efforts over time, by letting you compare current costs usage patterns with historical data, and see how your changes impact your costs.

Examining Resource Utilization

The first step for identifying inefficiencies is to understand how resources are being used. It's common to analyze usage data and find that some resources are over provisioned. For example, an EC2 instance might be sized based on peak load, leaving it underutilized during off-peak hours. Another common case is resources being intentionally over provisioned when creating the environment, because speed of development was prioritized over cost optimization, and the plan is to perform cost optimization later. This is a sound choice when starting out, but more often than not usage is never analyzed later, and instances are left over provisioned by omission.

AWS CloudWatch, a monitoring and observability service, can help identify such situations. CloudWatch enables you to monitor resource utilization in real-time, allowing you to view graphs of utilization and performance. AWS also offers the Compute Optimizer service, which makes recommendations for your EC2 instances and Auto Scaling groups based on historical utilization data, analyzed with machine learning algorithms.

Monitoring and Adjusting Costs

Cloud cost optimization is not a one time activity, it requires continuous monitoring and analysis. You can use Cost Explorer to periodically review your AWS costs and understand how they change over time, viewing the impact of your infrastructure changes and your cost optimization efforts. You can also use AWS Budgets to set custom cost and usage budgets that alert you when your costs or usage exceed or are forecasted to exceed the budgeted amount.

Cost Explorer can also help you track the usage of your Reserved Instances and Savings Plans. Reserved Instances and Savings Plans are purchase options that offer significant cost savings compared to On-Demand pricing, but require an upfront commitment from you and careful planning. Monitoring their usage ensures that you're getting the most out of your investment.

Taking Action

Scaling Resources

The ability to scale resources to match demand is one of the key benefits of the cloud, and one of your best tools for cost optimization. By configuring resources to scale based on usage metrics, you can avoid unutilized or underutilized resources, and only pay for the capacity that you actually need.

With AWS Auto Scaling, you can configure clusters of EC2 instances to automatically scale out (create more instances) or in (terminate unused instances) as needed. Auto Scaling can be done based on different usage metrics, for example average number of requests received by the cluster, or average CPU usage across all instances.

Serverless is another option, where the scaling is done automatically by AWS, and you only pay for the resources you're actually using. You can build applications to be natively serverless and use Lambda functions for their compute capacity, or you can migrate non-serverless native applications from EC2 instances to Fargate. Databases can also be made serverless, either with Aurora Serverless with compatibility with Postgres and MySQL, or with a native serverless database like DynamoDB.

Implementing Cost Optimization Strategies

These are some cost-optimization strategies that will help you reduce your cloud costs:

  • Applying different purchase options, such as Reserved Instances and Savings Plans, can result in significant cost savings for predictable workloads.
  • Turning off resources when they're not needed, such as development environments that won't be used after office hours, can result in cost savings of approximately 70% compared to keeping those resources on at all hours.
  • Applying cost allocation tags to resources helps you more easily allocate costs to specific projects or departments. This way you can identify where the costs are coming from, and better understand where cost-saving strategies will be most effective.

If you're interested in a detailed analysis of Cost Optimization strategies, read our article How to Optimize Your AWS Costs: 5 Best Practices 

Utilizing Cost-Saving Services

AWS provides several services and features that help users save costs and reduce their bill. One of them is AWS Trusted Advisor, an automated tool that provides you with real-time guidance to help you follow AWS best practices, and can give you insights and recommendations for cost optimization. Another tool is AWS Compute Optimizer, which uses machine learning to analyze historical usage data of your EC2 instances and Auto Scaling groups, and make purchase recommendations tailored to your usage patterns.

An alternative and sometimes more efficient way to save costs is to use a third-party service. Pump uses group buying & AI algorithms to automate cost savings in AWS, with zero engineering input and financial risk to you. It's the fastest way to save 60% on your AWS bill, at $0 cost to you.


AWS cost optimization is not a one-time task, but a continuous process of monitoring and analyzing cost and usage data, and adjusting parameters and implementing cost-saving strategies. By applying cost-optimization strategies and best practices, you can keep your AWS costs as low as possible, and stay on top of your cloud spending. You can do so manually, but the easiest way to do it is with an automated tool such as Pump, which can reduce your AWS bill by up to 60% with zero engineering effort and zero cost to you.

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