Author

Ankur Mandal

March 11, 2024

AWS Cost Optimization Best Practices

Author

Ankur Mandal

5 min read
March 11, 2024

AWS is a leading provider of cloud computing services offering various compute, storage, and networking solutions as PaaS offerings, be it managed databases or container orchestrations.

Cloud providers account for a significant portion of IT budgets, underscoring the importance of embracing and using AWS cost optimization best practices.

While organizations diligently explore every avenue to minimize costs related to compute resources in their pursuit of efficient AWS cost management, many overlook an important factor influencing their overall AWS expenditures: Elastic Block Storage.

The goal of holistic AWS cost optimization can only be achieved when aspects of both compute resources and storage are considered and optimized.

Read this blog to learn some of the AWS cost optimization best practices that will help you cut down on the bill by optimizing both compute resources and storage.

Introduction To AWS Cost Optimization

The primary concern for organizations relying on cloud service providers like AWS is ensuring efficiency. While organizations consider numerous facets in their approach to optimize AWS cost, they ignore the storage cost despite it being a significant contributor to the overall cloud cost. 

An independent study by Virtana on the state of hybrid cloud storage revealed that 94% of cloud decision-makers responded that storage costs are rising, with 54% stating that compared to the overall cloud bill, storage spending is growing exponentially.

To further corroborate the impact of storage cost, Lucidity conducted audits on leading organizations such as KPMG, American Airlines, Vedanta, and Iris Mountain.

We found that, on average, these organizations spent 40% of their cloud costs on storage. Considering this number, it should not come as a surprise that your storage decision can significantly impact AWS cost and performance. 

What is even more important to note is that of all the storage aspects, EBS is one of the major factors that remain untouched, resulting in increased AWS costs. Our survey of over 100 enterprises revealed that the average EBS cloud accounts for 15% of the total cloud cost.

Moreover, despite overprovisioning, organizations faced at least 1 downtime per quarter, costing them dearly. 

Unattached idle volumes are one major contributor to increased EBS costs. Paying for storage that is not being used can add up to unnecessary costs.

Even if your EBS volumes are not attached to running instances, you will still be billed for the storage space they occupy. To optimize your expenses, it is important to efficiently manage your resources by detaching or deleting unneeded volumes.

The lack of live shrinkage further leads to inefficient optimization in EBS in AWS. If you decide to manually reduce the size of an EBS volume, there won't be an automatic decrease in costs since you still get billed for the original storage provisioned.

Additionally, to manually shrink the EBS volume, you usually need to create a new, smaller volume and transfer the data from the old volume to the new one. This process might require you to briefly pause your instance, detach the volume, create a snapshot, generate a new volume with the desired size, and reattach it to the instance.

Although this procedure is not complicated, it may result in some downtime and require effort.

reasons or ignoring EBS costs

Thus, if you do not actively manage and optimize your EBS resources alongside compute resources, databases, and other aspects, you can end up overspending and affecting the overall financial health of your organization.

Hence, it is essential to implement strategies that holistically optimize all the aspects of AWS. Amazon Web Services (AWS) cost optimization involves optimizing the cloud infrastructure while reducing costs and maintaining performance.

For cost optimization on Amazon Web Services, you must continuously monitor, analyze, and adjust your AWS resources and usage.

Considering the aforementioned, we have compiled a list of effective AWS cost optimization best practices, which will offer you comprehensive AWS cost optimization, from compute resource allocation, database cost, and data transfer cost optimization to EBS usage optimization.

AWS Cost Optimization Best Practices

Now that we know what leads to wasteful spending in AWS and how effective AWS cost optimization can benefit an organization.

Let us look into AWS cost optimization best practices that will help you save money while maintaining a profitable infrastructure.

Analyzing And Monitoring AWS Usage

Analysis

Analysis of AWS usage is one of the most important AWS cost optimization best practices as it allows you to identify underutilized and idle resources and set and manage budgets accurately.

Through a comprehensive analysis, you gain insight into your current and future cloud spending patterns, preventing unexpected cost overruns and better planning of your cloud investment.

This visibility is crucial as it helps understand which resources consume the most budget and where opportunities for cost-saving exist. To ensure efficient budgeting and optimization, we recommend analyzing the breakdown of AWS cost into the associated storage and compute resources.

Storage cost: Based on the volume of data stored and the storage class used, storage-related factors can contribute significantly to the overall cloud cost. When analyzing storage for AWS cost optimization, look for the following:

  • Perform an analysis of the costs associated with moving data into and out of AWS storage services inside and outside AWS regions.
  • Generate customized reports to focus on storage-related expenses using AWS Cost Explorer and AWS Billing and Cost Management reports.
  • Analyze EBS volume configurations and determine whether high-performance options, such as Provisioned IOPS volumes, are required. 

Compute resources: The cost of EC2 instances drives the price of Amazon's services because so many rely on compute resources provided by Elastic Compute Cloud (EC2). Costs associated with EC2 depend on the instance type, size, and region. Each instance type has a different computing ability and related costs. On-demand, Reserved, and Spot instances have different pricing models. Watch out for the following in your compute resource analysis. 

  • Inspect the types and sizes of EC2 instances you are using. Make sure their CPU, memory, and other specifications match your workloads.

Monitoring

Once done with a comprehensive analysis, monitor these factors to ensure accurate visibility and continuous cost optimization. Cost allocation tagging is one of the most effective ways to achieve this.

You can use AWS cost allocation tags to categorize and track your AWS cost. Aside from helping you with custom usage reports, it will help you identify the abandoned resources that no longer serve any value.

You can also remember underutilized or overprovisioned resources with tagged costs. This information will help you allocate resources more efficiently, optimize instances, and eliminate waste.

There are many other ways to monitor the various aspects, such as storage costs through manual discovery or monitoring tools.

However, we would suggest against that since they demand an extensive investment of time and effort from the DevOps team, resulting in performance degradation and downtime.

Understanding this difficulty, we at Lucidity designed a Storage Audit. With just a click of a button, our free-to-use Lucidity Storage Audit gives you comprehensive visibility into the areas leading to wastage and helps capture the risk of downtime.

Within 25 minutes of deployment, you will gain access to:

  • Overall disk spend: We will help you uncover how much you are spending disk-wise, what should be the optimized bill, and how you can save 80% on storage costs.
storage audit report using Lucidity
  • Disk wastage: We will help you find the primary cause of wastage, be it idle resources or overprovisioning so that you can take the necessary steps to eliminate them.
  • Disk downtime risk: We will help you prevent the possibility of any reputational and financial damage due to downtime by identifying when and where it could happen.

What makes Lucidity Storage Audit different?

Unlike manual discovery or deploying monitoring tools, which can significantly invest time, money, and effort, Lucidity Storage Audit is a ready-to-use executable tool that automates the monitoring process.

Rightsizing AWS Resources

Your provision resources should meet your requirements and needs for effective AWS cost optimization. It ensures that the resources are allocated so that they are neither overprovisioned nor underprovisioned. 

Rightsizing enables organizations to minimize waste, reduce costs, and improve the efficiency of their cloud infrastructure by matching the capacity and performance of resources, such as Amazon EC2 instances and Amazon RDS database instances, to the actual needs of their workloads. 

Identify And Eliminate Underutilized Resources

You can rightsize resources to gain comprehensive insight into their usage by monitoring CPU, memory, network, and storage metrics.

A closer look at these metrics will help you identify consistently underutilized resources, such as CPU instances that are consistently below a certain threshold or with ample available memory.

Eliminating these underutilized resources will reduce the AWS cost as you will no longer pay for unnecessary capacity.

You can leverage Lucidity’s Storage Audit to determine how much of your resources are underutilized or idle. Once deployed, it will give you much-needed insight into the disk spend and help you discover your storage wastage.

Being an agentless audit, it is designed to run with minimal DevOps intervention and takes only 25 minutes to onboard.

Utilizing AWS Trusted Advisor For Resource Optimization Recommendations

AWS offers two tools instrumental in resource optimization- AWS Trusted Advisor and AWS Cost Explorer. 

  • Using the AWS Trusted Advisor, you can identify idle or underutilized resources that can be optimized. Its real-time insights into service usage can help businesses identify cost-saving opportunities and enhance security.
  • The Cost Explorer console provides access to reservation recommendations and resource-based recommendations. It will enable resource optimization by offering insight such as:
  • Several recommendations are based on the quantity of resources.
  • The money you will save with each recommendation.
  • The potential savings are associated with the instances listed in the recommendation compared to standard On-Demand instance costs.

Implementing Auto-Scaling To Optimize Resource Usage

Another powerful strategy that can help optimize resource usage and, in turn, AWS cost optimization is auto-scaling. Using auto-scaling ensures that your application has the resources to meet its demands at any moment.

Auto-scaling eliminates manual adjustments and overprovisioning, leading to more efficient use of resources.

A cloud auto-scaling solution allows organizations to reduce their cloud costs by dynamically scaling up and down based on demand. Fewer idle or underutilized resources result in reduced cloud costs.

As mentioned above, in the pursuit of optimizing resource usage, organizations implement only auto-scaling strategies that can help compute resource optimization and overlook one of the significant contributors to AWS EBS cost.  

Another revelation pointing to cloud spend wastage was a mere 25% disk utilization. Using AWS storage inefficiently can result in higher AWS bills.

For instance, storing data in high-cost storage classes when lower-cost options are available can waste money and reduce your organization's cost-effectiveness.

Moreover, when you fail to optimize your storage, you may overprovision it, wasting resources and increasing costs. On the other hand, the low utilization of disks leads to overprovisioning, inefficient resource allocation, wasted expenses, and missed opportunities to optimize costs.

Understanding the severity of this ignorance and how it can impact the overall cost, we at Lucidity have designed an EBS Auto-Scaler. It sits atop your block storage and cloud service provider and automates the shrinkage and expansion of the storage resources.

Utilizing Lucidity for Storage Cost Optimization

As mentioned, EBS accounts for a significant portion of the overall cloud cost of all the storage options, yet organizations tend to overlook it.

This is because many cloud service providers (CSPs) lack the depth of features needed for fine-grained control; hence, optimizing storage necessitates the development of a custom tool.

Custom tool development, however, requires a significant amount of time and effort from DevOps. However, if you rely exclusively on the tools provided by CSPs, you may end up with suboptimal, labor-intensive, and manual processes that are hard to sustain.

Considering these factors that result in a lack of ROI, organizations tend to overprovision their storage resources to ensure uptime with the day-to-day operations.

This is why optimizing storage resources for a holistic AWS cost optimization is crucial. This is where we step in. Once Lucidity has all the data about storage wastage, we deploy Lucidity EBS Auto-Scaler, our industry-first, state-of-the-art, and autonomous multi-cloud block storage layer.

We aim to provide you with a comprehensive NoOps experience by making the block storage economical and reliable.

Hence, we have removed the hassle associated with capacity planning and overprovisioning through our automated live block storage scaling.

As mentioned above, with our EBS Auto-Scaler, you don't have to worry about underprovisioning or overprovisioning since we offer seamless expansion and shrinkage without downtime, buffer, or performance lags.

With our EBS Auto-Scaler, you get the following benefits:

  • Seamless expansion and shrinkage: There is no inherent understanding of the file system's structure or data organization in AWS since it primarily operates at the block storage level. Therefore, while it can expand Elastic Block Store (EBS) volumes, it cannot inherently shrink them.
    Previously, volume reduction had to be performed manually, but that's no longer true. 
    Whether there is a sudden surge in storage resource demand or when the demand is suboptimal, you can trust our EBS Auto-Scaler to expand or shrink automatically based on the requirement. 
  • Reduced storage cost: Our EBS Auto-scaler will ensure you no longer pay for underutilized or unutilized resources. With automated expansion and shrinkage removing the provisioning concerns, you will save a profitable 70% on your storage cost, and we will increase the disk utilization from 35% to 80%.

With our ROI Calculator, you can check how much you will save with Lucidity in your system. You should enter the details like disk spend, disk utilization, and annual growth rate. We will give you a clear idea of how much money Lucidity will help you save.

Lucidity ROI calculator to find storage saving opportunities
  • No downtime: The traditional approach to resource provisioning requires manual work with the DevOps team navigating through 3 different tools. This results in significant downtime and reflects decreasing productivity.
    Lucidity ensure that you always have the space that you require. This is made possible through automated shrinkage or expansion within minutes of the request's initiation. 
    Lucidity enables you to create customized policies to further ensure that downtime or performance lag is eliminated.
    You can add in your desired utilization, minimum disk, and buffer size, and Lucidity will ensure that the instances are automatically managed according to the policies. It is worth noting that you can create any number of policies with Lucidity.
    Hence, you can ensure that the storage resources scale as per your fluctuating demands.
custom policy feature in Lucidity to ensure continuous performance without any downtime

If you find yourself facing unexpected spikes in website traffic or are looking to optimize costs during quieter periods, our Managed Disk Auto-Scaler will make sure your applications are consistently performing at their best.

Within 1 minute of the requirement being raised, Lucidity's EBS Auto-Scaler expands the storage capacity and seamlessly shrinks it without any performance lag, buffer, or downtime.

Utilizing AWS Reserved Instances

Understanding The Concept Of Reserved Instances

AWS Reserved Instances are virtual servers that run in AWS EC2 and RDS. Organizations can purchase RIs at a contract price plus hourly rates. With Amazon RIs, you can leverage an instance for 1-3 years and save up to 70% as a discount.

There are two types of RIs: Standard and Convertible. Convertible RIs can harness upcoming instance families, albeit at a lower rate than Standard RIs. 

Choosing The Right Reserved Instance Type And Term

Before you decide to optimize your RI-based savings, you must understand whether or not you are using the suitable RI types and terms. This can significantly impact your overall cost savings and budget management.

By selecting an instance type that closely matches your workload, you can maximize the use of your RIs.

For example, Upfront RIs are typically the best choice for workloads with predictable and stable demand.

For dynamic or variable workloads, convertible RIs allow, for instance, type modifications, which leads to optimal cost savings and higher returns on investment.

Optimizing Savings With Reserved Instance Utilization Reports

While RIs can help you save costs, you can only leverage those benefits when you use them. To understand RI utilization, you need utilization reports, which you can get from Amazon Cost Explorer.

These reports will provide deeper insights into RIs for various services such as Amon EC2, Elastic Cache, RDS, Redshift, and more. 

You can use RI coverage reports on AWS to understand the reason behind your high RI costs.

You can use these reports to review your RI and understand their utilization status- checking whether any underutilized resources or ones that do not match your requirements. It will help you understand your potential saving opportunities. 

Using these reports, you can take the necessary steps, such as:

  • Adjust RI sizes and types for underutilized RIs using AWS Management Console to match your requirements.
  • In areas where you consistently need more capacity than you currently have RIs, consider purchasing additional RIs.
  • You can sell or buy unused RIs from other AWS customers using AWS's RI Exchange marketplace. Exchanging RIs or acquiring new ones can help you optimize your coverage on AWS.
  • Take immediate action when your RIs are underutilized by setting up monitoring and alerting systems.
  • Optimize RI utilization by auto-scaling based on usage patterns during peak and off-peak hours.

Leveraging AWS Spot Instances

Understanding The Concept Of Spot Instance

Spot Instances is one of three virtual servers of AWS only available for EC2, which can help save up to 90% compared to the on-demand prices by leveraging unused or spare Amazon EC2. They are suitable for workloads that can withstand interruptions or are flexible.

It is essential to understand that while leveraging spot instances can be profitable, they get easily interrupted by AWS with a mere two minutes of notification when AWS needs the capacity back.

Hence, to use Spot Instances effectively, you need to have profound knowledge of workloads and their tolerance for interruptions. 

Identifying Workloads Suitable For Spot Instances

Before implementing any spot instance strategy for cost-effective computing, it is essential to identify and understand the suitable workloads for Spot Instances.

For example, Spot Instances are ideal for workloads that can be interrupted or run at variable times. This flexibility allows you to use excess AWS capacity while paying less for computing capacity.

Moreover, when you match the right workloads with Spot Instances, you'll ensure you're using the most cost-effective instance for each job, eliminating over-provisioning.

Implementing Spot Instances For Cost-Effective Computing

Now that we know what a Spot Instance is and how beneficial it is in optimizing AWS cost let us look at some of the strategies we can implement for cost-effective computing.

  • It is recommended that workloads tolerant of interruptions be selected for spot instances, including batch processing, data analysis, rendering, testing, and simulations.
    On the other hand, mission-critical or real-time applications should not be selected for spot instances.
  • Consider Spot Blocks if your workload requires a longer runtime. They allow you to reserve a spot instance for a specified duration (1 to 6 hours) at a lower, predictable price.
  • Make your spot instances available across various instance types, sizes, and availability zones with AWS Spot Fleet. Instance types, sizes, and availability zones can be automatically diversified with Spot Fleet, resulting in substantial cost savings.
    Spot Fleet monitors the Spot Instance market for price changes and adjusts your fleet as needed.
  • Instance pools can be created that group instances with similar attributes (e.g., instance type, family, or OS). If one instance is disrupted, other instances can be used.
    AWS instance pools optimize costs by simplifying the scaling of workloads, providing a more efficient and reliable way to manage spot instances, and reducing interruptions.

Follow AWS Cost Optimization Best Practices To Save Costs

Following the above AWS cost optimization best practices will help organizations of all sizes in reducing cloud costs, improved resource utilization, and better alignment with business goals.

With the help of proactive cost management, continuous usage monitoring, and adoption of AWS cost management best practices such as right-sizing resources, leveraging AWS cost allocation tags, and automating, businesses can thrive in the cloud and maximize the return on their AWS investments while minimizing financial waste.

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