Serverless on AWS

Build and run applications without thinking about servers

Serverless is a way to describe the services, practices, and strategies that enable you to build more agile applications so you can innovate and respond to change faster. With serverless computing, infrastructure management tasks like capacity provisioning and patching are handled by AWS, so you can focus on only writing code that serves your customers. Serverless services like AWS Lambda come with automatic scaling, built-in high availability, and a pay-for-value billing model. Lambda is an event-driven compute service that enables you to run code in response to events from over 150 natively-integrated AWS and SaaS sources - all without managing any servers.

Move from idea to market, faster

Lower your costs

By eliminating operational overhead, your teams can release quickly, get feedback, and iterate to get to market faster.

With a pay-for-value billing model, you never pay for over-provisioning and your resource utilization is optimized on your behalf.

Adapt at scale

Build better applications, easier

With technologies that automatically scale from zero to peak demands, you can adapt to customer needs faster than ever.

Serverless applications have built-in service integrations, so you can focus on building your application instead of configuring it.

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Read the Serverless Quarterly Recap Blog Post »

Serverless Services on AWS

Modern applications are built serverless-first, a strategy that prioritizes the adoption of serverless services, so you can increase agility throughout your application stack. We’ve developed serverless services for all three layers of your stack: compute, integration, and data stores. Consider getting started with these services:

Use cases

Web Applications
Data Processing
Batch processing
Event Ingestion

Web Applications
Web Applications

To-Do List App

The Web Application reference architecture is a general-purpose, event-driven, web application back-end that uses AWS Lambda, Amazon API Gateway for its business logic. It also uses Amazon DynamoDB as its database and Amazon Cognito for user management. All static content is hosted using AWS Amplify Console.

This application implements a simple To Do app, in which a registered user can create, update, view the existing items, and eventually, delete them.

Sample Code »
Data Processing
Data Processing

Real-time File Processing

The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses AWS Lambda. This architecture is ideal for workloads that need more than one data derivative of an object.

In this example application, we deliver notes from an interview in Markdown format to S3. S3 Events are used to trigger multiple processing flows - one to convert and persist Markdown files to HTML and another to detect and persist sentiment.

Sample Code »
Batch processing
Batch processing

Extract Transfer Load

This reference architecture demonstrates the use of AWS Step Functions to orchestrate an Extract Transfer Load (ETL) workflow with AWS Lambda.

This solution processes the global air quality data, OpenAQ available in the AWS registry for open data. It generates the minimum, maximum and average ratings for air quality measurements on a daily basis. The ETL workflow will have to be triggered manually but this can be easily scheduled on a recurring basis using Amazon EventBridge rule. Once the transformation completes, you will be notified over email of the S3 location to the summarized data.

Sample Code »
Event Ingestion
Event Ingestion

Serverless Document Repository

This application uses Amazon ML services like Comprehend and Rekognition to index documents and images, and then sends the results to Elasticsearch for fast indexing.
This architecture is designed for large numbers of documents by using queuing.

Sample Code »