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AWS Lambda
Developer Guide

What Is AWS Lambda?

AWS Lambda is a compute service where you can upload your code to AWS Lambda and the service can run the code on your behalf using AWS infrastructure. After you upload your code and create what we call a Lambda function, AWS Lambda takes care of provisioning and managing the servers that you use to run the code. You can use AWS Lambda as follows:

  • As an event-driven compute service where AWS Lambda runs your code in response to events, such as changes to data in an Amazon S3 bucket or an Amazon DynamoDB table.

  • As a compute service to run your code in response to HTTP requests using Amazon API Gateway or API calls made using AWS SDKs.

AWS 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, code monitoring and logging. All you need to do is supply your code in one of the languages that AWS Lambda supports (currently Node.js, Java, and Python). For more information about the AWS Lambda execution environment, see Lambda Execution Environment and Available Libraries. For information about how AWS Lambda determines compute resources required to execute your code, see Compute Resources for Your Lambda Function.

AWS Lambda executes your code only when needed and scales automatically, from a few requests per day to thousands per second. With these capabilities, you can use Lambda to easily build data processing triggers for AWS services like Amazon S3 and Amazon DynamoDB, process streaming data stored in Amazon Kinesis, or create your own back end that operates at AWS scale, performance, and security.

When Should I Use AWS Lambda?

AWS Lambda is an ideal compute platform for many application scenarios, provided that you can write your application code in languages supported by AWS Lambda (that is, Node.js, Java, and Python), and run within the AWS Lambda standard runtime environment and resources provided by Lambda.

When using AWS Lambda, you are responsible only for your code. AWS Lambda manages the compute fleet that offers a balance of memory, CPU, network, and other resources. This is in exchange for flexibility, which means you cannot log in to compute instances, or customize the operating system or language runtime. These constraints enable AWS Lambda to perform operational and administrative activities on your behalf, including provisioning capacity, monitoring fleet health, applying security patches, deploying your code, and monitoring and logging your Lambda functions.

If you need to manage your own compute resources, Amazon Web Services also offers other compute services to meet your needs.

  • Amazon Elastic Compute Cloud (Amazon EC2) service offers flexibility and a wide range of EC2 instance types to choose from. It gives you the option to customize operating systems, network and security settings, and the entire software stack, but you are responsible for provisioning capacity, monitoring fleet health and performance, and using Availability Zones for fault tolerance.

  • Elastic Beanstalk offers an easy-to-use service for deploying and scaling applications onto Amazon EC2 in which you retain ownership and full control over the underlying EC2 instances.

Are You a First-time User of AWS Lambda?

If you are a first-time user of AWS Lambda, we recommend that you read the following sections in order:

  1. Read the product overview and watch the introductory video. These resources are available on the AWS Lambda webpage.

  2. Read the "How It Works" section of this guide. This section introduces various AWS Lambda components you work with to create an end-to-end experience. For more information, see AWS Lambda: How It Works.

  3. Review the programming model. When creating a Lambda function there are core concepts you should be familiar with. This section explains these concepts and provides details of how they work in different languages that you can use to author your Lambda function code. For more information, see Programming Model.

  4. Try the console-based Getting Started exercise. The exercise provides instructions for you to create and test your first Lambda function using the console. You also learn about the console provided blueprints to quickly create your Lambda functions. For more information, see Getting Started.

Beyond the Getting Started exercise, you can explore the various use cases, each of which is provided with a tutorial that walks you through an example scenario. Depending on your application needs (for example, whether you want event driven Lambda function invocation or on-demand invocation), you can follow specific tutorials that meet your specific needs. For more information, see Examples of How to Use AWS Lambda.

The following topics provide additional information about AWS Lambda: