AWS EC2 Cost: Understanding and Reducing Your Costs

Amazon Elastic Compute Cloud (AWS EC2) provides AWS-based compute resources. EC2 provides a user-friendly web interface that lets you provision cloud-based virtual servers, called EC2 instances. EC2 offers nearly 400 different instance types, with a variety of configurations you can choose from. You can, for example, choose storage options, operating systems, networking, purchasing models and processors. EC2 instances are offered across 24 regions and 77 availability zones across the world. 

While EC2 is enormously flexible, AWS EC2 pricing is quite complex. It can be challenging to understand your costs, predict them, and make the most economical use of EC2 resources. We’ll provide some insights and best practices that can help.

In this article:

Amazon EC2 Cost and Capacity Optimization

AWS offers tools and services that can help reduce your compute costs and automate cost optimization. Here are some of the most popular ways to effectively manage and reduce EC2 costs.

Reserved Instances and Savings Plans

Reserved Instances provide discounts on Amazon EC2 resources. It is a billing discount you can apply to on-demand instances in your AWS account. However, your on-demand instances need to match certain attributes, such as the region and instance type, before you can benefit from this billing discount.

Savings Plans offer significant savings on Amazon EC2. It is a program that lets you commit to a consistent usage amount (measured in USD per hour). The program helps you reduce costs while using the instance configurations that suit your needs in return for your commitment. There is no need to commit to a specific instance configuration.

EC2 Spot Instances

Amazon EC2 Spot Instances enable you to leverage unused EC2 capacity available within the AWS cloud. The spare capacity instances can be stopped or terminated at any time, with little warning, should AWS need to allocate them elsewhere. This is why Spot Instances are offered at up to 90% off the on-demand price. 

Spot Instances are ideal for a wide range of cases. For example, you can leverage this capacity for fault-tolerant or stateless applications, as well as flexible applications used for big data, CI/CD, containerized workloads, web servers, testing and development workloads, and high-performance computing (HPC). 

Spot Instances can natively integrate with other AWS services, including Auto Scaling, Amazon Elastic Container Service (Amazon ECS), Amazon EMR, Data Pipeline, AWS Batch and CloudFormation. 

Learn more in our detailed guide to AWS spot instances

EC2 Auto Scaling

Auto Scaling enables you to maintain application availability by automatically adding or removing EC2 instances. This automated process occurs according to predefined conditions you specify. Here are several key features of this service:

  • Fleet management features—let you maintain the health and availability of an entire fleet. 
  • Dynamic and predictive scaling features—enable you to add or remove instances. Dynamic operations respond to changing demands while predictive scaling processes automatically schedule a correct number of instances according to predicted demand. You can use these features together to scale quickly.

Learn more in our detailed guide to EC2 auto scaling

AWS Cost Explorer

This service provides rightsizing recommendations generated to help you identify cost-saving opportunities. Usually, it involves either downsizing or terminating EC2 instances. The rightsizing feature analyzes your EC2 resources and usage and then displays cost reduction opportunities. It lets you view all underutilized EC2 instances across several member accounts in a single view. This can help you immediately identify cost-saving opportunities, which you can implement via the Amazon EC2 console.

Learn more in our detailed guide to the AWS Cost Explorer 

AWS Compute Optimizer

The Compute Optimizer service recommends AWS resources that can help reduce costs and improve the performance of your workloads. The service uses machine learning (ML) models to analyze several historical utilization metrics. 

AWS Compute Optimizer can prevent you from over-provisioning resources, which can help you avoid unnecessary infrastructure costs. The service can also prevent you from under-provisioning resources, so you can avoid poor application performance. 

The service can help you choose the optimal configurations for three types of AWS resources, including Amazon EC2 instances, AWS Lambda functions and Amazon EBS volumes.

6 Best Practices to Reduce Your EC2 Costs

To reduce your overall AWS EC2 costs, consider applying the following practices.

Determine Your Compute Requirements

It is not difficult to find affordable instances in the cloud. The challenge is to find affordable instances that can handle the demands of your applications and workloads. You can do that by assessing your scenario and clarifying your requirements. 

You should account for several aspects, including memory, network, SSD storage, CPU architecture and CPU count. Once you have this information, you should look for an instance that provides the best performance for your price range.

Store Cold Data in a Cheaper Storage Tier

Amazon S3 offers several tiers for non-frequently-accessed data, including S3 Deep Archive Glacier, aS3 Glacier and S3 Infrequent Access. You can use AWS services to automatically identify data once it is no longer needed during production. You can then move this data to a cheaper cold storage tier.

Use GPU Instances

CPUs and CPUs greatly affect both pricing and performance. You should determine which type is more suitable for your application. For example, if you want to run machine learning workloads in the cloud, you should use new GPU instances like the G3 or P3 series. GPU instances can significantly accelerate the training time and can provide cost-savings (compared to CPUs) even if GPUs incur a higher cost per hour.

Leverage Spot Instances for Stateless and Non-Production Workloads

Spot instances can offer significant savings for stateless and non-production workloads. You can get up 90% off the on-demand price, and reduce your EC2 costs. Note that Spot Instances are subject to changes, and can be taken before the instance is used. 

Target Your Cost Optimization Using Tags

You can reduce EC2 costs by targeting certain EC2 instances overothers. You can, for example, only target production, non-production, rogue and batch-processing instances. To locate and optimize instances via the AWS console and the AWS API, you can use tags. You can also use tags for compliance and security purposes.

Automate EC2 Cost Optimization with Spot by NetApp

The various AWS EC2 pricing models offer options for cloud spending optimization, but managing it all on your own is not so simple. Even the above best practices take time, effort and expertise to implement and maintain. 

To address the challenges of cloud infrastructure management, including EC2 cost optimization, Spot by NetApp offers a full suite of cloud management tools. These tools can help with everything from spend reporting and cost allocation, to running production and mission-critical workloads on EC2 spot instances, to maximizing utilization and ROI on EC2 reserved instances. 

Reliably run workloads on spot instances for up to 90% savings

While the spare capacity offered by cloud providers has the potential for massive savings on cloud compute, using spot instances comes with risk of termination, with little warning. Elastigroup from Spot by NetApp makes it easy to reliably leverage spot instances, enterprise-grade SLA, even mission critical and production workloads can benefit. Elastigroup provides every feature you’d expect from a standard cluster management platform, but raises the bar with predictive approaches to instance selection, auto-recovery and autoscaling, along with comprehensive dashboarding and advanced automation

Make the most out of your long-term cloud commitments 

For cost-conscious companies, reserved instances and savings plans can help reduce costs up to 72%. These commitment pricing models are often a good match for long-term deployments, and stable, predictable workloads. However, if your application needs change, or you no longer need the resources you’ve committed to, you’re locked in. Eco, from Spot by NetApp, manages and automates commitment lifecycles to offload unused capacity and automatically adjust capacity portfolios to maximum ROI.