Compute services make up the largest share of AWS costs, with EC2 being one of the most significant contributors. Designed for scalability, Amazon EC2 allows users to run applications via virtual servers known as EC2 instances.
Its flexibility and wide range of configurations make it a critical part of most cloud architectures, but managing EC2 Instance costs effectively requires a clear understanding of its pricing models and influencing factors. Without this understanding, cloud waste can increase rapidly, without delivering proportional business value.
EC2 pricing isn’t one-size-fits-all. From On-Demand to Reserved Instances and Spot Instances, each pricing model serves different workloads and cost strategies. Additionally, factors like instance types, regions, and usage patterns play an important role in determining the final bill.
In this article, we discuss EC2 instance pricing, including how it works, considerations that influence pricing, cost optimization tips, and more.
What Are AWS EC2 Instances?
EC2 instances are virtual servers in Amazon’s Elastic Compute Cloud (EC2) that provide scalable computing capacity in the AWS cloud. These instances allow you to run applications, host websites, process data, or perform other computational tasks without needing to manage physical hardware yourself.
Each EC2 instance is a combination of virtual CPU (vCPU), memory, storage, and network capacity, all tailored to specific workloads. A hypervisor manages this environment, which allows multiple virtual servers to operate on a single physical machine. AWS’s hypervisor is called “Nitro.” The beauty of virtualization is users can easily create, modify, and delete the virtual guests (instances), enabling immense flexibility and scalability.
However, this flexibility also means costs can vary significantly depending on the instance type, pricing model, and usage patterns.
What Are the Different EC2 Instance Types?
Amazon offers a variety of EC2 instance types optimized for different use cases, including:
- General purpose instances: These instances provide a balance of compute, memory, and networking resources. They are ideal for a variety of diverse workloads, such as web servers and code repositories. AWS specifically designed general purpose instances for applications that use these resources in equal proportions. Examples: m8g, m7a
- Compute Optimized instances: These are specifically designed for compute-bound applications that can benefit from high-performance processors. They offer a higher ratio of processor to memory for compute-intensive workloads. Examples: c8g, c7i
- Memory Optimized instances: AWS built these instances for workloads that require a high amount of memory relative to compute power. They’re ideal for tasks like in-memory databases, real-time big data analytics, and large-scale cache services. Examples: r8g, u-1, x2idn
- Storage Optimized instances: This option is ideal for workloads that require high sequential read and write access to large datasets on local storage, such as NoSQL databases, in-memory databases, and data warehousing. Examples: i3, d3, i8g
- Accelerated Computing instances: These benefit from hardware accelerators or co-processors and work well for tasks that require parallel processing, such as graphics processing or data pattern matching. Examples: p5, g6
- HPC Optimized instances: High performance computing (HPC) instances are purpose built to offer the best price performance for running HPC workloads at scale on AWS. HPC instances are ideal for applications that benefit from high-performance processors such as large, complex simulations and deep learning workloads. Examples: Hpc7g, Hpc7a
- Burstable instances: These are for workloads that require a small amount of consistent CPU resources and can burst CPU capacity when additional cycles are available. They’re suitable for low-traffic web applications, small databases, and development environments. Examples: t4g, t3
How Does Amazon EC2 Instance Pricing Work?
AWS provides a range of pricing models. Each EC2 instance type comes with its own pricing, and the platform offers multiple discount mechanisms to reduce costs and optimize billing. Here’s what the different EC2 cost models look like:
1. AWS Free Tier
The AWS Free Tier is a promotional offering that helps new AWS users get started with cloud services without incurring costs. It provides a set amount of free usage, allowing users to explore, learn, and experiment without financial commitment.
The Free Tier varies for the services you are choosing. Here’s what it looks like for EC2 free tier:
- Duration: Available for the first 12 months after creating an AWS account
- Usage limits:
– 750 hours per month of Linux, RHEL, or SLES t2.micro or t3.micro* instance dependent on region
– 750 hours per month of Windows t2.micro or t3.micro* instance dependent on region
– 750 hours per month of public IPv4 address regardless of instance type
- Operating systems: Supports both Linux and Windows operating systems
- Unlimited mode: t2.micro and t3.micro instances launch in Unlimited Mode by default, which may incur additional charges if CPU usage exceeds the Free Tier baseline for long enough.
The AWS Free Tier is limited in its capacity but still useful for entry-level applications in the following use cases:
- Beginners: Those new to AWS (or cloud services in general) can use the Free Tier to learn the ropes without financial risk.
- Students: Individuals in educational settings can experiment and work on class projects without incurring costs.
- Startups: New businesses with limited capital can prototype and launch their initial products on the Free Tier, scaling up as they grow.
- Developers: They can test new ideas, run small applications, or learn about new AWS services without a financial barrier.
- Small projects: Personal projects, blogs, or small websites that don’t require significant resources can often run within the Free Tier limits.
2. Amazon EC2 On-Demand Pricing
On-Demand instances are one of the most flexible and straightforward pricing options Amazon EC2 provides. They allow users to run instances (virtual servers) without any long-term commitments. Unlike some other pricing models, on-demand instances don’t require upfront payment. This means users can start or stop their instances at any time and only pay for what they’ve provisioned.
AWS bills users on an hourly basis or by the second, depending on the specific instance characteristics.
On-Demand EC2 instances are most suited for:
- Short-term tasks: Temporary projects like a week-long promotional campaign where you use the resources for the duration and then terminate
- Unpredictable needs: Sporadic or unpredictable workloads, such as startups or new apps with uncertain traffic patterns — scale based on real-time demands
- Development and testing: Where you quickly spin up for testing and shut down post-use, ensuring cost efficiency
- Flexibility: Ideal for businesses not wanting long-term commitments, allowing adaptability to changing scenarios
3. Amazon EC2 Reserved Instances
EC2 Reserved Instances are a billing mechanism where users receive discounts up to 75% compared to on-demand pricing in exchange for commitment of either one or three years. By committing to longer-term usage (one- or three-year terms), users can optimize costs and optionally reserve capacity for their applications.
Users can choose from different payment options, including All Upfront, Partial Upfront, or No Upfront. The choice affects the discount level, with All Upfront offering the highest savings.
There are two types of Reserved Instances:
- Standard RIs: Standard RIs are ideal for predictable, steady-state workloads and offer the highest discounts, often up to 72%, but come with limited flexibility for changes in instance attributes.
- Convertible RIs: These provide more flexibility, allowing you to change instance families, operating systems, or tenancies during the reservation term. However, this flexibility comes at the cost of slightly lower discounts, typically up to 54%.
Note: ProsperOps’ discounts are instance type- and OS-agnostic, with the ability to perform exchanges with Convertible RIs in real time.
4. Amazon EC2 Savings Plans
AWS Savings Plans are a horizontally flexible pricing model designed to help reduce EC2 Instance costs in exchange for a commitment to a consistent amount of usage (measured in USD per hour) over a one-year or three-year term.
Unlike Reserved Instances, Savings Plans are not tied to a specific service, instance type, size, or region, offering greater flexibility while still delivering substantial cost savings — often up to 72% compared to On-Demand pricing.
There are two types of Savings Plans in Amazon EC2:
- Compute Savings Plans: These offer the maximum flexibility between the two types of Savings Plans. Users commit to a consistent amount of hourly compute usage, irrespective of the instance family, size, region, or operating system. This means they can change the characteristics of their EC2 instances, or even move workloads to AWS Fargate or AWS Lambda and still benefit from savings.
- EC2 Instance Savings Plans: These are more restrictive than Compute Savings Plans but offer a higher discount. Users commit to using specific instance families in a particular region. However, they still have the flexibility to change the size of the instance within that family or switch between different operating systems.
Here’s a comprehensive look at the distinction between EC2 RIs and SPs:
For more information, our detailed blog on AWS Savings Plans vs. Reserved Instances can help.
5. Amazon EC2 Spot Instances
Spot Instances are the most cost-effective pricing model for Amazon EC2 that allows users to take advantage of unused EC2 capacity at significantly reduced prices — often up to 90% less than On-Demand pricing. These instances are ideal for workloads that are flexible, interruptible, or time-insensitive, such as batch processing, big data analytics, and stateless applications.
Spot Instances are available on a capacity-available basis, meaning AWS can reclaim them with short notice (typically a two-minute warning) if the capacity is needed for On-Demand or Reserved Capacity workloads. This makes Spot Instances less suitable for critical workloads that require continuous availability.
However, when strategically integrated with workloads that can handle interruptions or are distributed across multiple instances, Spot Instances can deliver substantial cost savings and resource efficiency. Here are some use cases that spot instances support:
- Flexible workloads: Tasks with flexible start and end times are ideal for Spot Instances — for example, data analysis jobs that can pause and resume without significant disruption.
- Batch processing: You can execute large-scale batch jobs that process vast amounts of data at a fraction of the cost using Spot Instances. These jobs often run in parallel, and even if AWS terminates some instances, others can pick up the slack.
- High-performance computing (HPC): You can also run non-time-sensitive simulations and complex calculations that require massive amounts of compute power on Spot Instances.
- Testing and development: Developers can use Spot Instances to test their applications under high-load scenarios without incurring high costs.
How Do I Estimate My Amazon EC2 Costs Before Launching an Instance?
Before launching an instance, you can configure a cost estimate using the AWS calculator to help determine the contract terms and instance types that best suit your model. Here’s a step-by-step guide on how to use the calculator:
Step 1: Go to AWS Pricing Calculator and click on Create Estimate. Under Find Service, type in Amazon EC2 and click on Configure.
Step 2: Configure by entering the details of your usage, including EC2 specifications such as tenancy, OS, or monthly workload (constant, daily spike traffic, weekly spike traffic, or monthly spike traffic). To get an accurate cost prediction, you must input factors like instance type, region, storage, and data transfer.
Step 3: Save and click on View Summary to view the estimated cost.
Key Factors that Influence EC2 Pricing
There are multiple factors other than the chosen pricing models that can influence EC2 Instance pricing, including:
Instance type and usage pattern
AWS offers multiple EC2 instance types optimized for different workloads. The cost of an instance depends on:
- Instance family: General Purpose (e.g., t3, m7i), Compute-Optimized (e.g., c7i), Memory-Optimized (e.g., r7i), and Storage-Optimized (e.g., i4i). Choosing the right family ensures you’re not overpaying for unnecessary resources.
- Size and scaling: Selecting the right vCPU, RAM, and networking capacity can prevent under- or over-provisioning.
- Usage pattern: Instances that run continuously (always-on) may be better suited for Savings Plans or Reserved Instances, while unpredictable workloads benefit from Spot Instances or Auto Scaling.
Storage costs (EBS volumes & snapshots)
EC2 instances primarily use Elastic Block Store (EBS) for storage. The right choice of EBS volume type significantly impacts costs:
- EBS Volume Types:
- General Purpose SSD (gp3): Recommended for most workloads; offers a lower price per GB than gp2. Migrating from gp2 to gp3 can cut costs by up to 20%.
- Provisioned IOPS SSD (io1, io2): High-performance volumes for databases and latency-sensitive applications but are 5x-20x more expensive per GB than general-purpose SSDs. Use only when necessary.
- HDD (st1, sc1): Cost-effective for log storage and archives — no need to pay for SSDs when low-speed storage suffices.
- Snapshot Costs & Best Practices:
- Snapshots are stored in Amazon S3, but they are billed separately.
- Regularly delete unused snapshots to avoid unnecessary storage costs.
- Use Amazon Data Lifecycle Manager (DLM) to automate retention policies and ensure you’re not keeping snapshots longer than required.
Networking & data transfer costs
EC2 pricing includes networking and data transfer charges based on where the data moves:
- Within the same Availability Zone (AZ): Free for EC2-to-EC2 communication.
- Between different AZs in the same region: $0.01/GB in each direction, costs add up fast if cross-AZ communication is frequent.
- Between different regions: Higher charges apply, so avoid unnecessary cross-region data transfers.
- Outbound to the internet: The first 100GB per month is free, then pricing follows a tiered model — after 150TB, a flat rate of $0.05/GB applies.
- Using CloudFront: No transfer cost between EC2 and CloudFront. Caching content at edge locations can reduce outbound data transfer expenses.
Load balancing costs
AWS Elastic Load Balancers (ELB) distribute traffic across multiple EC2 instances, but they also add costs:
- Load Balancer Usage: Charged per hour and per Load Capacity Unit (LCU). The more requests and traffic, the higher the cost.
- Cross-AZ Data Transfer: If your ELB distributes traffic across AZs, you pay for both ELB usage and the inter-AZ data transfer costs.
- Autoscaling Considerations: Remember that if your application is both Load Balanced and Autoscaled, Load Balancer costs will increase along with your ASG.
Region & Availability Zone selection
EC2 pricing varies significantly based on the AWS region due to local infrastructure costs, demand, and regulatory factors. Choosing the right region can help optimize costs.
For example:
- North Virginia (us-east-1) is one of the most affordable AWS regions due to its high infrastructure density.
- São Paulo (sa-east-1) is among the most expensive due to limited data center capacity and higher operational costs.
Additionally, deploying instances across multiple Availability Zones ensures high availability but will introduce inter-region data transfer costs, so do so only as necessary.
Best Practices and Tips for Reducing Your EC2 Instance Pricing
Did you know that if you use Amazon’s own processor brand, Graviton, instead of AMD or Intel, you can save up to 20% in EC2 instance costs? Choosing AMD still offers up to a 10% cost reduction over Intel processors.
There are plenty of other ways to reduce your EC2 costs. Here are a few examples:
Improve your AWS cloud visibility
One of the foundational steps to effectively manage and reduce EC2 instance costs is to gain comprehensive visibility into your AWS cloud environment. This includes understanding your instance usage patterns, monitoring resource allocation, and identifying underutilized or idle instances.
Improving cloud visibility with tools like AWS Cost Explorer is a proactive approach to managing EC2 Instance costs. This helps you optimize performance and ensure that you’re only paying for the resources you truly need.
Only use specialized EC2 instance types when necessary
AWS offers a variety of instance types, each tailored for specific workloads and use cases. While it might seem safer to pick a larger or more specialized instance “just in case,” this approach can lead to significant overspending.
The AWS rightsizing recommendations can help you identify and reduce costs associated with underutilized instances. By analyzing your usage patterns and comparing them to the capabilities of your chosen instance types, AWS suggests more cost-effective configurations to help you avoid overprovisioning resources and paying for unnecessary capacity.
You should also avoid the expense of running those instances continuously when they’re either unnecessary or when a less powerful option would work.
Stop non-production instances during inactive hours
Instance stop/start scheduling is a great cost-saving strategy, as it keeps resources from incurring unnecessary charges by sitting idle. However, AWS doesn’t offer a built-in way to do this, so DevOps and Engineering teams need to implement their own solutions.
For teams looking for a head start on building their own instance scheduling tool, they can leverage AWS’ Instance Scheduler template. By avoiding costs associated with idle resources, you can significantly lower expenses — especially for instances billed based on resource usage.
Implement a cost allocation tagging strategy
Cost allocation tags help you track costs. After you activate the tags, AWS uses the tags to organize your instances and other related resource costs, such as storage, for each billing period on your cost allocation report. This makes it easier to categorize, track, and manage resource expenses.
You can identify where spending is highest, as well as the workload, application, or product incurring the spend. Basically, with tags you get to know the what, why, where and by whom attributes of each resource. Then you can prioritize core tags and schedule periodic reviews to ensure resources align with workload needs and business objectives.
In short, a cost allocation tagging strategy provides a granular view of your spending that enables you to quickly identify underused or unused resources, thereby optimizing spending.
Upgrade to latest-generation instances
AWS continually innovates and releases newer EC2 instance types that are optimized for performance, cost, and specific use cases. These updates incorporate the latest hardware and technological advancements. This means faster CPU clock speeds, improved memory performance, and better networking capabilities.
As a result, a smaller, newer instance might now handle tasks that once required a larger, older instance — with equal or even better performance.
Over time, older instance types might see reduced support, fewer updates, or even deprecation. Transitioning to newer instances ensures you always have supported technology. This allows you to benefit from the latest security patches, updates, and features.
Leverage EC2 Auto Scaling and EC2 fleet
AWS designed Amazon EC2 Auto Scaling specifically for managing EC2 servers. It automatically adjusts the number of EC2 instances in response to varying load patterns. That means when there are spikes in traffic or CPU utilization, it seamlessly scales up the number of instances to accommodate demand. During low traffic, it reduces the number of instances.
This optimizes resource allocation by ensuring there’s no over- or under-provisioning, ultimately reducing costs and saving on operational costs.
In order to avoid dependency on a single instance type, a good strategy is to configure scalable solutions leveraging EC2 Fleet, which will launch differing instance types to meet the computing demand. Amazon’s EC2 Fleet and Spot Fleet can launch a fleet of tens, hundreds, or thousands of instances in a single operation. EC2 Fleet and Spot Fleet integrate seamlessly with EC2 Auto Scaling to give you the best of both worlds: optimized costs and responsive scaling.
Use an automated cost optimization tool
While FinOps teams can implement manual cost optimization strategies, it’s time-consuming and inefficient. Automated optimization tools use data analysis and machine learning to streamline cost optimization processes like data collection, real-time tracking and alerts, analysis, and reports.
ProsperOps is one such tool that can take the manual effort out of rate optimization, automating optimization efforts to maximize savings while eliminating friction and manual oversight.
Automatically Optimize Your EC2 Costs With ProsperOps
ProsperOps delivers cloud savings-as-a-service, automatically blending discount instruments to maximize your savings while lowering commitment lock-in risk. Using our autonomous discount management platform, we optimize the hyperscaler’s native discount instruments to reduce your cloud spend and place you in the 98th percentile of FinOps teams.
Using advanced strategies, ProsperOps can continuously analyze your company’s compute usage patterns to identify inefficiencies and autonomously manage a portfolio of commitments to ensure you pay the best rate for whatever compute resources you decide to run.
This hands-free approach to AWS cost optimization can save your team valuable time while ensuring automation continually optimizes your AWS discounts for maximum Effective Savings Rate (ESR).
Make the most of your AWS cloud spend with ProsperOps. Schedule your free demo today!
