AWS Lambda Power Tuning is an open-source tool that can help you visualize and fine-tune the memory/power configuration of Lambda functions. It runs in your own AWS account - powered by AWS Step Functions - and it supports three optimization strategies: cost, speed, and balanced.

This is intended to be a repo containing all of the official AWS Serverless architecture patterns built with CDK for developers to use. All patterns come in Typescript and Python with the exported CloudFormation also included.

A serverless architecture for orchestrating ETL jobs in arbitrarily-complex workflows using AWS Step Functions and AWS Lambda.

Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS

AWS Step Functions is an orchestration service for reliably executing multi-step processes using visual workflows. This repository includes detailed examples that will help you unlock the power of serverless workflow.

Powertools (logger, HTTP client, AWS clients, middlewares, patterns) for Lambda functions.

This is the repo for Serverlesspresso workshop. Questions? Contact @jbesw or @benjamin_l_s on GitHub or Twitter.

Serverlesspresso - The serverless coffee ordering application! As seen at AWS re:Invent 2021. Presented by AWS Serverless DA team. Questions? Contact @jbesw.

The Image Recognition and Processing Backend reference architecture demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition.

Configuration with AWS step functions and lambdas which initiates processing from activity state

Simple demo application deployed using LocalStack

This web app shows how to build a complex backend workflows as stand-alone AWS Step Functions applications. See the Compute Blog articles to learn more. @jbesw

AWS Lambda Power Tuner UI is an open source project creating a deployable easy to use website built on a layered technology stack allowing you to optimize your Lambda functions for cost and/or performance in a data-driven way via an easy to use UI.

Build and deploy a serverless data pipeline on AWS with no effort.

Execute AWS Step Functions locally

Build Train and Deploy your own custom container using AWS StepFunctions Data Science SDK

Customers using R can run simulation and machine learning securely and at scale with Amazon SageMaker while also reducing the cost of development by using the fully elastic resources in the cloud. In this demo, learn how to build, train, and deploy statistical and ML models in R at scale using Amazon SageMaker from your IDE.

This project contains source code and supporting files for a serverless application which can be used for Computer Vision inferencing using Amazon Rekognition.

An AWS CodeBuild project optimized for multiple source repos & any combination of buildspec based scripts from config values

A Step Functions microservice for remediating GuardDuty findings.