AWS Lambda

AWS Lambda Serverless Compute Guide

With AWS Lambda, easily launch code for nearly any type of application or backend service, without having to deal with any additional administration.

A quick overview of Amazon Lambda

Amazon Lambda is a serverless compute service that lets you execute code while downsizing the amount of maintenance needed.

What is Amazon Lambda?

Not having clear visibility into Lambda costs can lead to a number of potential consequences. One major issue is that managing your AWS bill can become overwhelming, similar to a runaway truck that is difficult to control. Without proper monitoring and measurement of your Lambda spend, it is easy for costs to spiral out of control.

Existing cost optimization tools face several challenges that hinder their effectiveness. One common issue is a heavy reliance on tagging, which can be burdensome and often leads to inaccuracies and inconsistencies. These tools are also notorious for being clunky and overly complex, making it difficult for non-technical team members to navigate and understand the insights they provide.

Moreover, the lack of actionable insights is another major drawback. Existing tools often fail to offer specific and meaningful information, such as mapping costs to unit costs or cost per customer. This makes it challenging for teams to grasp the direct impact of their work on overall costs and hampers their ability to make informed, data-driven decisions.

AWS Lambda is a serverless compute service that allows you to run code without having to provision or manage servers, write caseload cluster scaling logic, keep event integrations up to date, or manage runtimes.

Amazon Lambda allows for running application or backend code without administration costs.  More specifically, this reduces the need for managing servers, workload scaling logic, maintaining event scaling, and more.

Why Amazon Lambda?

Lambda offers a multitude of benefits, making it an ideal choice for your computing needs. By simply uploading your code as a ZIP file or container image, Lambda effortlessly locates the required computing power and executes it based on incoming traffic. This seamless process allows you to focus on your application’s functionality without worrying about infrastructure management.

One of the key advantages of Lambda is its ability to work harmoniously with other AWS services through a few simple calls from your application. This integration saves you time and effort, as Lambda is optimized to collaborate effortlessly with services such as S3, Cognito, and DynamoDB.

By default, Lambda is capable of working with a wide selection of programming languages including Node.js, Java, and Python. For testing functionality and building, Lambda files can be developed on both serverless and container applications such as AWS SAM.

No servers to manage

AWS Lambda does not require any base physical infrastructure to run on to carry out your tasks. Utilizing is simply a matter of uploading your code for it to automatically run. Once you upload your code, Lambda takes care of all the resource allocation, automatically adding and retracting resources in response to each event. This dynamic allocation ensures optimal performance and efficiency, regardless of the scale of your tasks.

Continuous scaling

Resources for calculations are automatically added and retracted in response to each event. The uploaded code continues to run in parallel and scales directly to the size of the current task. Task sizes can range from just a few per day to hundreds of thousands in mere seconds. Lambda also offers the convenience of adjusting the memory size to suit your program’s requirements. With a few simple steps, you can fine-tune your application’s performance, optimizing the memory allocation to achieve the desired results.

Proper cost-optimization

You will never have to overpay for what resources you use. With the aforementioned benefits comes a high level of flexibility. Running your code will charge you by the millisecond and the number of times your code is ran. In totality, you can save upwards of an additional 17%.

Consistent performance

Adjusting memory size to fit your program is incredibly easy. Running the program back-to-back can also be done within the double digit milliseconds by enabling Provisioned Concurrency. This feature allows you to run your program back-to-back in a matter of milliseconds. This feature ensures that your application remains responsive and delivers consistent performance, even during periods of high demand.

Amazon Lambda Features

Lambda is a powerful service that allows you to integrate other AWS services with custom logic and develop your back-end services with the scalability, security, and performance of AWS. It offers a wide range of features and capabilities that make it a versatile choice for developers. For a more in-depth overview of what AWS Lambda has to offer, everything can be found here.


Modify AWS with custom logic

Integrating new code changes how certain AWS services will process new data.  After uploading the code and establishing individual settings, the code will be tied to a service of your specification.  The service will then act as a trigger condition, subsequently running the code and enacting changes to the new data.

No new tools

One of the key advantages of Lambda is its flexibility in programming languages. You can write your code in the language of your choice, and both third-party and native libraries are supported. This allows you to leverage existing code and libraries, making development faster and more efficient.

Highly automated

The need to worry about OS updates or resizing as usage continues is removed.  Maintenance, security, self-deployment, administration, activity logging, and monitoring all come with the package.


In the same way all other AWS services are preserved, Lambda maintains capacity across availability zones, meaning it can still run should an availability zone facility suffer a system error.

Links with AWS RDS and LFS

Using Amazon RDS Proxy, Lambda can be set up using the in-house database services, making it incredibly easy to set up several serverless applications that require database interactions.

To simplify data storage and management, Lambda integrates seamlessly with Amazon Elastic File System (EFS). This feature enables you to read, write, and persist data at any scale, eliminating the need for temporary storage and reducing application complexity.

Manual control of performance

Provisioned Concurrency can either be used to keep applications at the ready for a surge of intake, or lowered or turned off completely during inactivity.

Integral security

Your applications are protected by AWS SDK and AWS Identity and Access Management (IAM) and Lambda runs concealed by a VPC by default.  Lambda also meets many current security standards, all of which are given in full detail here.

Connects to shared files

Amazon Elastic File System (EFS) lets users read, write, and persist high volumes at low frequencies at any scale.  This forgoes the need to download data for temporary storage, simplifying the application’s complexity.

Tight budget control

Pay only for what you use.  Since Lambda charges by the millisecond, there won’t be a single second you will be overpaying for.  Add to that the ability to control what resources you are using and it is very easy to budget your Lambda use. In terms of cost-effectiveness, Lambda’s pricing model is based on usage, with charges calculated by the millisecond. This means you only pay for the actual resources consumed by your functions, eliminating any overpayment. 

AWS Lambda Pricing

Lambda uses a pay-as-you-go model where users are charged based on what resources they use, how many requests they make, and for the code’s run time.

Run time is calculated by when the code either returns or terminates, rounded up to the nearest millisecond.  The pricing for resources typically depends on how much memory is allocated to the program and the CPU power that is applied.  Further details on function configuration can be found here.

Mapping Lambda costs to specific unit costs, such as cost per customer, is crucial for gaining clear visibility into the financial impact of your work and making informed data-driven decisions. Many cost optimization tools in the market have limitations, as they heavily rely on tagging, are cumbersome to use, and lack simplicity. Moreover, these tools often fail to provide actionable insights that can be easily understood by team members, hindering their ability to comprehend the implications of their actions on overall costs.


Free Tier

AWS Lambda does offer a free trial for new and unsure users.  This tier offers one million free requests and 400,000 GB-seconds of compute time per month.


The spreadsheets of prices and formulas for billing users can be found here in full detail.  There are additional deviations in rates based on the regions that users are operating in. To calculate the total monthly charges for multiple Lambda functions, you will need to follow these steps:

1. Determine the monthly charges for each function: Start by calculating the total cost for each individual function separately. This can be done by considering the pricing factors such as the number of requests, execution time, memory size, and any additional resources used by each function.

2. Calculate the total cost for each function: Once you have determined the monthly charges for each function, add up all the costs together for each individual function.

3. Add the costs of all functions together: After obtaining the total cost for each function, sum up these costs to arrive at the final sum you will pay for using commensurate AWS Lambda computing resources.

Just remember your total Lambda charges can increase if you use other AWS services alongside Lambda. While Lambda pricing primarily depends on the number of requests and the duration of their execution, it is important to note that using additional AWS services can contribute to the overall cost. For instance, if you transfer data between services or implement services that are charged separately, such as Amazon S3 for storage or Amazon RDS for databases, these costs will be added to the Lambda charges. Therefore, it is crucial to consider the potential impact of other AWS services on your total Lambda charges when evaluating the overall cost of your AWS infrastructure.

If you want to experiment with what your bill would look like with your desired resources, you can use the AWS Pricing Calculator found here. For general economics on AWS’ resources, more information can be found here.

Need help with AWS Lambda?

Getting Started With Amazon Lambda

AWS has ample documentation and tutorials for you to start learning how to fully utilize your Lambda function.  But before anything, it is advised that you look through this page for use cases and understand how Lambda can benefit your project and applications. 

Over the course of these tutorials, you will also learn to use serverless development tools like AWS Cloud9.  For everything from initially uploading a Lambda function to editing and testing, to managing the functions, working with specific coding languages, and troubleshooting, all the documentation is laid in full here.

1. Log in

Log in or sign up to the AWS Management Console and set up your root account. You will also want to install the AWS Command Line Interface (CLI) if you plan on configuring Lambda Functions from the command line.

2. Create a function

Functions can be uploaded as either a ZIP file or a container image. Here are a couple of tutorials for both methods.

3. Editing the code

Lambda does provide an environment on which you can modify your uploaded function. It functions like any other editor and can be adjusted to your personal preference. For more on the Lambda editor console, everything is right here.


The Command Line Interface is for managing functions and the resources at your Lambda function’s disposal. This is for creating execution roles, creating functions, and listing Lambda functions on your account. Tutorials can be found here.

5. Quotas

There are hard limits on the total resources that can be expended for all operations by a Lambda function. While a few resources like the number of concurrent functions being run in parallel and the storage for your functions can be renegotiated, most of these limits cannot be raised. All the numbers and caps are listed here.

Amazon Lambda Support

Need some extra help initiallizing your AWS Lambda functions? AllCode is an AWS Select Consulting Partner with 10+ years of experience developing cloud-based solutions for enterprise-scale applications.

Amazon trusts and recommends our services to businesses who need a hand or who are looking to cloudsource their technology stack. We are the experts to guide you down the path for successful use of cloud services.