A quick overview of Amazon Lambda
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?
By simply uploading code as a ZIP file or container image, Lambda automatically locates the needed computing power and executes based on incoming traffic. Lambda is also optimized to work with other AWS services with just a few calls from an application.
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.
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 a few per day to hundreds of thousands in mere seconds.
You will never have to overpay for what resources you use. 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%.
Adjusting memory size to fit your program is incredibly easy. Running the program back-to-back can also be done within the double didgit milliseconds by enabling Provisioned Concurrency.
Amazon Lambda Features
Lambda is used to either integrate other AWS services with custom logic or work on your personal back-end services with AWS scale, security, and performance. For a more in-depth overview of what AWS Lambda has to offer, everything can be found in totality 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
Lambda lets you use coding languages of your choice. Third-party and native libraries work.
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
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.
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.
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.
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 is called to when it 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.
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. 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 resources can be found here.
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 in 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.
4. AWS CLI
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.
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.
Need help with AWS Lambda?
Amazon Lambda Support
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