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AWS Lambda is a powerful tool that allows developers to run their code without having to manage servers. We will delve into the details of the free tier for Lambda in this article. We’ll also discuss the limits of the Lambda free tier and provide some examples to help you understand how it works.
Before we dive into the specifics of the free tier, let’s quickly recap what AWS Lambda is. AWS Lambda is a serverless computing service that runs your code in response to events, automatically managing the underlying compute resources for you. This means you can focus on your code and not worry about managing servers, which makes it a popular choice for developers.
For a more detailed explanation of AWS Lambda, check out our article on what is a Lambda function.
Yes, to an extent. AWS Lambda does offer a free tier including 1 million requests per month and 400,000 GB-seconds of compute time per month. This free tier does not automatically expire at the end of your 12 month AWS Free Tier term, but is available indefinitely.
This means that you can run your Lambda functions for free, up to a certain limit. If you exceed these limits, you will need to pay for the additional compute time and requests.
The Lambda Free Tier includes 400,000 GB-seconds of compute time every month. To put this into perspective, if you configure your Lambda functions with 1 GB of memory, you get over 110 hours of compute time per month.
However, if you configure your functions with more memory, you get less free compute time. For example, if you configure your functions with 10 GB of memory, you only get about 11 hours of free compute time per month.
The free tier also includes 1 million free requests per month. After you’ve used up these requests, you will need to pay for any additional requests.
AWS Lambda is charging its users by the number of requests for their functions and by the duration, which is the time the code needs to execute. When your code starts running in response to an event, AWS Lambda counts a request. It will charge the total number of requests across all of the functions used. Duration is calculated by when your code started executing until it returns or is terminated, rounded up to the closest 1 millisecond. The AWS Lambda pricing depends on the amount of memory the user used to allocate to the function.
Let’s look at some examples to better understand how the Lambda free tier works.
Remember, these examples ignore any additional costs from other AWS services or data transfers. If your Lambda function interacts with other AWS services, like Amazon S3 or API Gateway, you may incur additional charges.
Are there any additional charges in AWS Lambda pricing models? Yes, there are. Read this carefully, and there will be no unpleasant surprises.
The possibility of additional costs to incur is significantly higher if you have used any other AWS services or data transfers. You will be charged regardless of the chosen tier. In the example, if your function is reading and writing data to or from Amazon S3, you will be charged for the read/write requests and all of the data stored within Amazon S3.
We will list some of the cases that will be charged additionally, and that way, you can follow up with all the changes made. If your Lambda function starts the external data transfers, you will be billed at the EC2 data transfer rate.
Also worth mentioning is that Amazon DynamoDB charges for data storage, throughput capacity, and data transfer. On the other hand, Amazon S3 is charging for storage, requests, and data transfers.
To ensure you stay within the free tier limits, it’s important to monitor your AWS Lambda usage. You can use Dashbird’s AWS Lambda monitoring tool to keep track of your Lambda functions and avoid any unexpected charges.
If this information was helpful, but it still gives you a hard time calculating the price you’d need to pay, use our AWS Lambda cost calculator. It might help determine the costs you need to pay for AWS Lambda services based on personal usage. Follow this link and calculate your own AWS Lambda prices.
Further reading:
6 tried and tested Lambda cost optimization strategies that work
How to test JavaScript Lambda functions?
Debugging with Dashbird: Lambda task timed out after X seconds
Serverless observability and real-time debugging
In this guide, we’ll talk about common problems developers face with serverless applications on AWS and share some practical strategies to help you monitor and manage your applications more effectively.
Today we are announcing a new, updated pricing model and the end of free tier for Dashbird.
In this article, we’re covering 4 tips for AWS Lambda optimization for production. Covering error handling, memory provisioning, monitoring, performance, and more.
Dashbird was born out of our own need for an enhanced serverless debugging and monitoring tool, and we take pride in being developers.
Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly. We are instantly aware now if there’s a problem. We love the fact that we have enough information in the Slack notification itself to take appropriate action immediately and know exactly where the issue occurred.
Thanks to Dashbird the time to discover the occurrence of an issue reduced from 2-4 hours to a matter of seconds or minutes. It also means that hundreds of dollars are saved every month.
Great onboarding: it takes just a couple of minutes to connect an AWS account to an organization in Dashbird. The UI is clean and gives a good overview of what is happening with the Lambdas and API Gateways in the account.
I mean, it is just extremely time-saving. It’s so efficient! I don’t think it’s an exaggeration or dramatic to say that Dashbird has been a lifesaver for us.
Dashbird provides an easier interface to monitor and debug problems with our Lambdas. Relevant logs are simple to find and view. Dashbird’s support has been good, and they take product suggestions with grace.
Great UI. Easy to navigate through CloudWatch logs. Simple setup.
Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs. We have Dashbird alert us in seconds via email when any of our functions behaves abnormally. Their app immediately makes the cause and severity of errors obvious.