AWS Knowledge
AWS Fargate Pricing: Tips for Cost Management
Piyush Kalra
Oct 14, 2024
The cloud environment may sound scary for so many people, but if one looks closely, the Fargate pricing is a blessing for many developers, devops engineers, cloud architects and new startups, but only if you are able to manage it correctly. Amazon Web Services Fargate allows one to run containerized applications without having to manage the servers, but only when cost management is optimally done. So in order to help you in achieving your best optimal run with fargate, we have compiled a few insights and AWS cost management strategies along with some real world use cases as well.
AWS Fargate and Its Role in Cloud Computing
(Image Source: AWS Fargate)
AWS Fargate is tightly integrated with Amazon Elastic Container Service and Amazon Elastic Kubernetes Service and allows users to focus entirely on running their workload. The beauty of this serverless computing engine is that it takes away the responsibility of having to manage server infrastructure resources. Understanding its pricing framework is paramount to making sure the operation runs smoothly.
How AWS Fargate Works
An application that has been containerized is deployed via a created task definition that specifies the images of the containers and the needed CPU, memory, networking, among others. Fargate now uses the task definition to perform the three core functions of managing containers which include deployment, scaling and operation of the said containers. It uses ECS as the basis for container orchestration, and takes care of scheduling, scaling, and load balancing. Each Fargate task runs in a separate environment complete with its own network services stack thus improving accountability among tasks.
Core Functionalities
Among the key features of Fargate include automated scaling capabilities, resource limitation, and security features. This means that the developers do not have to give a lot of attention to the infrastructure, instead they can focus on the application and this improves the efficiency.
Integration with Amazon ECS and EKS
The use of Amazon ECS and EKS would allow for easier orchestration and task management when using Fargate. This would ensure that tasks run in separate environments or silos, preventing unauthorized access to information between the tasks while not compromising security in any way.
How Does AWS Fargate Pricing Work?
AWS Fargate operates a pay-as-you-go pricing scheme, which means that customers are charged only for the resources used. This model highlights two primary compute factors: the vCPU and the GB of RAM. In addition, the pricing of a Task or Pod involved deployment also considers the operating system, CPU architecture in use, and any additional storage resources. When working with containers on Fargate, you are required to define the amount of vCPU and GB of RAM required via a Task Definition that AWS will use to deploy services on the Fargate. Cost configuration is simple: the Cost is equal to the number of Tasks multiplied by the vCPU and GB used by each Task.
For instance, if you deploy a service via Fargate in the us-east-1 region, the costs incurred are for every second with a one-time min billable duration of at least a minute. (The rates can vary based on OS and architecture). The breakdown of costs to run Linux/x86 Systems is $0.04048 per vCPU per hour, $0.004445 per GB per hour; For running Linux/ARM it is $0.03238 per vCPU per hour and $0.00356 per GB per hour; For Windows/x86 it costs $0.09148 per vCPU per hour in addition to a charge of $0.046 per vCPU per hour for an OS license and $0.01005 per GB per hour.
Use the AWS Pricing Calculator for fargate to determine the amount of cost applicable to your specific setup and region
Pricing Components of AWS Fargate
Compute Resources
The charge for running your task on AWS Fargate is vCPU and memory resources. You pay by the second with a minimum of one minute so that you are charged as accurately as possible.
For example:
You run a task, configured to use 2 vCPUs and 4 GB of memory, for 10 hours on the Linux/ARM architecture, in the US East (Ohio) region.
vCPU Cost:
vCPU: 2 vCPUs
Duration: 10 hours
vCPU rate in US East (Ohio): $0.04048 per vCPU hour
vCPU Cost = vCPU * Duration * vCPU rate = 2 vCPUs * 10 hours * $0.04048/vCPU/hour = $0.8096
Memory Cost:
Memory: 4 GB
Duration: 10 hours
Memory rate in US East (Ohio): $0.004445 per GB hour
Memory Cost = Memory * Duration * Memory rate = 4 GB * 10 hours * $0.004445/GB/hour = $0.1778
Total Compute Cost:
Total Compute Cost = vCPU Cost + Memory Cost = $0.8096 + $0.1778 = $0.9874
Storage Costs
Each Fargate storage task has 20 GB of ephemeral storage by default, and charges apply to any additional storage. For example, in the US East (Ohio) region, it costs $0.000111 per GB per hour.
For example:
You used an extra 10 GB of storage above the default 20 GB in the US East (Ohio) region. The cost per GB per hour is still $0.000111.
Additional Storage Cost Calculation
10 GB * $0.000111/GB/hour = $0.00111/hour
For a full day (24 hours), the extra storage cost will be:
$0.00111/hour * 24 hours = $0.02664
Thus, the additional storage charge for one full day is $0.02664.
Data Transfer Fees
AWS Fargate adopts the same data transfer pricing structure for all regions. Incoming data transfer is free, while any data transfer out is charged according to your usage tiers. You can check the data transfer pricing here.
For example:
You have transferred 100 GB of data out in a month, and the costs for everything up to 10 TB are charged at $0.09 per GB:
First 1 GB: Free
Remaining 99 GB: 99 GB * $0.09/GB = $8.91
Total Data Transfer Cost: $8.91
Additional Charges
There could be additional charges as well based on the usage of different services offered by AWS - such as Amazon CloudWatch to monitor and log events. All these costs have to be considered while planning for AWS Fargate.
For example:
Assume that you use 20 GB of logs, 15 metrics, and 10 alarms with the costs $0.50 per GB for ingested logs, $0.03 per GB for archived logs, $0.30 per metric per month, and $0.10 per alarm per month:
Logging Costs:
Ingested Logs: 20 GB * $0.50/GB = $10.00
Archived Logs: 20 GB * $0.03/GB = $0.60
Total Logging Cost: $10.00 + $0.60 = $10.60
Monitoring Costs:
Metrics: 15 metrics * $0.30/metric = $4.50
Alarms: 10 alarms * $0.10/alarm = $1.00
Total Monitoring Cost: $4.50 + $1.00 = $5.50
These additions can significantly affect a budget for big applications, since the logging and monitoring will be carried out on a mass scale.
Cost Management Strategies
Right-Sizing Resources
As a conceptual mechanism, rightsizing resources simply means to level up the computing power based on your actual usage. This approach ensures that customers do not end up spending unnecessarily. Stick to the minimum, and only scale when required. Use AWS Cloudwatch and AWS Compute Optimizer to manage load and compute resources respectively.
Implementing Auto-Scaling
Auto-scaling tasks on AWS fargate allows you to remove unnecessary tasks from the workload when demand is low. This in return allows you to save workloads which can later be utilized when the demand is high.
Tips for Auto Scaling:
Use Application Auto-Scaling for your Fargate services.
To put in place scaling policies that will inform you on the use of the CPU or any other set metric
Include step scaling to have more accurate control over how the tasks are moving up or down.
Leverage AWS Savings Plans
If you use AWS Fargate on a consistent basis then you should consider utilizing Compute Saving Plans. The advantage of these plans is that they offer discounted futures rates in case you agree to a minimum consumption amount for 1 or 3 years.
Tips for Savings Plans:
Use AWS Cost Explorer to examine the Fargate usage patterns.
Start off with a lower level of commitment and gradually increase it as you understand your usage better.
To maintain flexibility, combine the use of On Demand with Savings Plans.
To understand more about Saving Plans and how you can use them to cut costs, check out our blogs.
Real-World Use Cases
The AWS Fargate pricing model can be best demonstrated by applying AWS Fargate to some practical cases. Let’s begin examining these other ways of pricing and applying the pricing models.
E-Commerce Platform with Variable Traffic
E commerce platforms which have variable traffic amounts are the ones that would benefit with the dynamic scaling features that AWS Fargate offers greatly. This helps the companies to effectively handle the rush hours while not having to pay when it is not busy.
Workloads that employ batch processing that are of regular usage enjoy the economic pricing offered by AWS Fargate. When businesses push their working tasks late into the night, they get the best use of resources available.
Best Practices for Cost Optimization
Monitoring and Reporting
Consistent observation and reporting are key contributors to successful cost control. Utilizing AWS Cost Explorer, you can see an analysis of your spending which can help to highlight certain areas where spending has grown as well as identify ways to lower that figure. Set spending triggers in AWS Budgets so that you stick to your budget and don’t incur unnecessary expenditures. This forward approach is vital to maintaining budgeting control. Refer to this article to understand how to use AWS cost explorer.
Data Transfer Optimization
It is beneficial to reduce the cost of data transfer within a business. Pairing Amazon CloudFront and caching techniques, for instance, can help mitigate the cost of data egress. To be economical, confer data transfers that do not leave the AWS cloud, targeting even the same Availability Zone (AZ). Make efficient use of Amazon CloudFront to deliver content and also reduce other costs associated with transfer. Transfer data only when it is necessary and secondly compress the data before the transfer takes place to prevent the same data being transferred over and over.
Conclusion
AWS Fargate is a great tool for running containerized applications with cloud infrastructure control but understanding its pricing plan offers aid in cutting the costs. Following the recommendations laid out in this article such as resource right sizing, leveraging on the use of savings plans and managing data transfer, AWS Fargate can work at lower costs. Out of these provisions you get to enjoy the full advantage of AWS Fargate at a fair price which benefits a firm looking to thrive in the cloud industry.
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