What is AWS Lambda?

You can use AWS Lambda to run code without provisioning or managing servers.

Lambda runs your code on a high-availability compute infrastructure and performs all of the administration of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, and logging. With Lambda, all you need to do is supply your code in one of the language runtimes that Lambda supports.

You organize your code into Lambda functions. The Lambda service runs your function only when needed and scales automatically. You only pay for the compute time that you consume—there is no charge when your code is not running. For more information, see AWS Lambda Pricing.

Tip

To learn how to build serverless solutions, check out the Serverless Developer Guide.

When to use Lambda

Lambda is an ideal compute service for application scenarios that need to scale up rapidly, and scale down to zero when not in demand. For example, you can use Lambda for:

• File processing: Use Amazon Simple Storage Service (Amazon S3) to trigger Lambda data processing in real time after an upload.

• Stream processing: Use Lambda and Amazon Kinesis to process real-time streaming data for application activity tracking, transaction order processing, clickstream analysis, data cleansing, log filtering, indexing, social media analysis, Internet of Things (IoT) device data telemetry, and metering.

• Web applications: Combine Lambda with other AWS services to build powerful web applications that automatically scale up and down and run in a highly available configuration across multiple data centers.

• IoT backends: Build serverless backends using Lambda to handle web, mobile, IoT, and third-party API requests.

• Mobile backends: Build backends using Lambda and Amazon API Gateway to authenticate and process API requests. Use AWS Amplify to easily integrate with your iOS, Android, Web, and React Native frontends.

When using Lambda, you are responsible only for your code. Lambda manages the compute fleet that offers a balance of memory, CPU, network, and other resources to run your code. Because Lambda manages these resources, you cannot log in to compute instances or customize the operating system on provided runtimes. Lambda performs operational and administrative activities on your behalf, including managing capacity, monitoring, and logging your Lambda functions.

Key features

The following key features help you develop Lambda applications that are scalable, secure, and easily extensible:

Environment variables

Use environment variables to adjust your function's behavior without updating code.

Versions

Manage the deployment of your functions with versions, so that, for example, a new function can be used for beta testing without affecting users of the stable production version.

Container images

Create a container image for a Lambda function by using an AWS provided base image or an alternative base image so that you can reuse your existing container tooling or deploy larger workloads that rely on sizable dependencies, such as machine learning.

Layers

Package libraries and other dependencies to reduce the size of deployment archives and makes it faster to deploy your code.

Lambda extensions

Augment your Lambda functions with tools for monitoring, observability, security, and governance.

Function URLs

Add a dedicated HTTP(S) endpoint to your Lambda function.

Response streaming

Configure your Lambda function URLs to stream response payloads back to clients from Node.js functions, to improve time to first byte (TTFB) performance or to return larger payloads.

Concurrency and scaling controls

Apply fine-grained control over the scaling and responsiveness of your production applications.

Code signing

Verify that only approved developers publish unaltered, trusted code in your Lambda functions

Private networking

Create a private network for resources such as databases, cache instances, or internal services.

File system access

Configure a function to mount an Amazon Elastic File System (Amazon EFS) to a local directory, so that your function code can access and modify shared resources safely and at high concurrency.

Lambda SnapStart for Java

Improve startup performance for Java runtimes by up to 10x at no extra cost, typically with no changes to your function code.