aws2js - AWS (Amazon Web Services) APIs client implementation for node.js

•    Javascript

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WARNING: aws2js is deprecated. Use aws-sdk instead. Amazon Web Services node.js module. Originally a fork of aws-lib.

amazon aws rest api https query-api ec2 rds ses elb s3 iam auto-scaling cloudwatch elasticache sqs simpledb sdb security-token-service sts dynamodb sns emr elastic-mapreduce

Clouddiscovery - The tool to help you discover resources in the cloud environment

•    Python

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Cloudiscovery helps you to analyze resources in your cloud (AWS/GCP/Azure/Alibaba/IBM) account. Now this tool only can check resources in AWS, but they are working to expand to other providers. The tool consists of various commands to help you understand the cloud infrastructure. It provides a CLI to easily perform desired actions.

cloud-discovery cloud cloud-infrastructure cloud-management aws aws-cli vpc diagrams aws-iot devops-tools aws-monitoring iam-policy aws-services

awesome-aws - A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources

•    Python

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A curated list of awesome AWS libraries, open source repos, guides, blogs, and other resources.Inspired by the awesome list.

aws cloud aws-sdk aws-cli cloudformation cloudwatch dynamodb elasticsearch kinesis lambda serverless machine-learning redshift s3 ec2 iam rds route53 ecs cloud-management

grafana-aws-cloudwatch-dashboards - :cloud: 20+ Grafana dashboards for AWS CloudWatch metrics: EC2, Lambda, S3, ELB, EMR, EBS, SNS, SES, SQS, RDS, EFS, ElastiCache, Billing, API Gateway, VPN,

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Set of AWS Grafana dashboards published on grafana.com - 10k+ downloads.Feel free to create pull request for additional AWS resources/printscreens/...

aws aws-cloudwatch grafana dashboard monitoring devops

mu - A full-stack DevOps on AWS framework

•    Go

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Amazon ECS (EC2 Container Service) provides an excellent platform for deploying microservices as containers. The challenge however is that there is a significant learning curve for microservice developers to deploy their applications in an efficient manner. Specifically, they must learn to use CloudFormation to orchestrate the management of ECS, ECR, EC2, ELB, VPC, and IAM resources. Additionally, tools like CodeBuild and CodePipeline must be mastered to create a continuous delivery pipeline for their microservices. To address these challenges, this tool was created to simplify the declaration and administration of the AWS resources necessary to support microservices. Similar to how the Serverless Framework improved the developer experience of Lambda and API Gateway, this tool makes it easier for developers to use ECS as a microservices platform.

microservice pipeline continuous-delivery docker ecs cloudformation codepipeline

aws-serverless-workshops - Code and walkthrough labs to set up serverless applications for Wild Rydes workshops

•    Javascript

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This repository contains a collection of workshops and other hands on content that will guide you through building various serverless applications using AWS Lambda, Amazon API Gateway, Amazon DynamoDB, AWS Step Functions, Amazon Kinesis, and other services.Web Application - This workshop shows you how to build a dynamic, serverless web application. You'll learn how to host static web resources with Amazon S3, how to use Amazon Cognito to manage users and authentication, and how to build a RESTful API for backend processing using Amazon API Gateway, AWS Lambda and Amazon DynamoDB.

serverless tutorial aws lambda

aws-serverless-workshops - Code and walkthrough labs to set up serverless applications for Wild Rydes workshops

•    Javascript

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This repository contains a collection of workshops and other hands on content that will guide you through building various serverless applications using AWS Lambda, Amazon API Gateway, Amazon DynamoDB, AWS Step Functions, Amazon Kinesis, and other services. Web Application - This workshop shows you how to build a dynamic, serverless web application. You'll learn how to host static web resources with Amazon S3, how to use Amazon Cognito to manage users and authentication, and how to build a RESTful API for backend processing using Amazon API Gateway, AWS Lambda and Amazon DynamoDB.

serverless tutorial aws lambda

aws-missing-tools - tools for managing AWS resources including EC2, EBS, RDS, IAM, CloudFormation and Route53

•    Shell

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tools for managing AWS resources including EC2, EBS, RDS, IAM, CloudFormation and Route53.

aws-lambda-redshift-loader - Amazon Redshift Database Loader implemented in AWS Lambda

•    Javascript

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With this AWS Lambda function, it's never been easier to get file data into Amazon Redshift. You simply push files into a variety of locations on Amazon S3, and have them automatically loaded into your Amazon Redshift clusters.For automated delivery of streaming data to S3 and subsequently to Redshift, also consider using Amazon Kinesis Firehose.

amazon redshift lambda

lambda-refarch-imagerecognition - 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

•    Javascript

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The Image Recognition and Processing Backend demonstrates how to use [AWS Step Functions] (https://aws.amazon.com/step-functions/) to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition. This workflow processes photos uploaded to Amazon S3 and extracts metadata from the image such as geolocation, size/format, time, etc. It then uses image recognition to tag objects in the photo. In parallel, it also produces a thumbnail of the photo.This repository contains sample code for all the Lambda functions depicted in the diagram below as well as an AWS CloudFormation template for creating the functions and related resources. There is also a test web app that you can run locally to interact with the backend.

lambda-refarch-imagerecognition - 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

•    Javascript

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The Image Recognition and Processing Backend demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition. This workflow processes photos uploaded to Amazon S3 and extracts metadata from the image such as geolocation, size/format, time, etc. It then uses image recognition to tag objects in the photo. In parallel, it also produces a thumbnail of the photo. This repository contains sample code for all the Lambda functions depicted in the diagram below as well as an AWS CloudFormation template for creating the functions and related resources. There is also a test web app that you can run locally to interact with the backend.

spring-cloud-aws - Integration for Amazon Web Services APIs with Spring

•    Java

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Spring Cloud AWS

spring spring-boot spring-cloud aws aws-cloudformation aws-sqs aws-ses aws-java-sdk aws-rds aws-elasticache spring-cloud-core

aws-lambda-zombie-workshop - Code and walkthrough labs to set up a serverless chat application for the Zombie Apocalypse Workshop

•    Javascript

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The Zombie Microservices Workshop introduces the basics of building serverless applications using AWS Lambda, Amazon API Gateway, Amazon DynamoDB, Amazon Cognito, Amazon SNS, and other AWS services. In this workshop, as a new member of the AWS Lambda Signal Corps, you are tasked with completing the development of a serverless survivor communications system during the Zombie Apocalypse.Prior to beginning the labs, you will need to finalize the setup of User authentication for the application with Cognito User Pools. This is a necessary step to finalize the readiness of the application.

serverless aws-lambda amazon-web-services

aws-lambda-zombie-workshop - Code and walkthrough labs to set up a serverless chat application for the Zombie Apocalypse Workshop

•    Javascript

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The Zombie Microservices Workshop introduces the basics of building serverless applications using AWS Lambda, Amazon API Gateway, Amazon DynamoDB, Amazon Cognito, Amazon SNS, and other AWS services. In this workshop, as a new member of the AWS Lambda Signal Corps, you are tasked with completing the development of a serverless survivor communications system during the Zombie Apocalypse. Prior to beginning the labs, you will need to finalize the setup of User authentication for the application with Cognito User Pools. This is a necessary step to finalize the readiness of the application.

serverless aws-lambda amazon-web-services

autospotting - Automatically replace AWS EC2 instances in AutoScaling groups with identically configured but up to 90% cheaper spot instances

•    Go

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A simple and easy to use tool designed to significantly lower your Amazon AWS costs by automating the use of spot instances. When installed and enabled on an existing on-demand AutoScaling group, AutoSpotting clones one of your on-demand instances from the group with a spot instance that is cheaper, at least as large (automatically considering memory, CPU cores and disk volumes) and configured identically to it. Once the new spot instance is ready, it is attached to the group and an on-demand instance is detached and terminated to keep the group at constant capacity.

aws autoscaling-groups aws-lambda spot-instances cost ec2 amazon-web-services terraform-module infrastructure aws-autoscaling autoscaling cheaper-spot-instances cloudformation automation golang-application ec2-spot ec2-instance

punchcard - Type-safe AWS infrastructure.

•    TypeScript

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Punchcard is a TypeScript framework for building cloud applications with the AWS CDK. It unifies infrastructure code with runtime code, meaning you can both declare resources and implement logic within the context of one node.js application. AWS resources are thought of as generic, type-safe objects — DynamoDB Tables are like a Map<K, V>; SNS Topics, SQS Queues, and Kinesis Streams feel like an Array<T>; and a Lambda Function is akin to a Function<A, B> – like the standard library of a programming language. To contact other services in your Function, data structures such as SNS Topics, SQS Queues, DynamoDB Tables, etc. are declared as a Dependency.

nodejs aws typescript serverless infrastructure-as-code punchcard aws-cdk

AutoSpotting - Saves up to 90% of AWS EC2 costs by automating the use of spot instances on existing AutoScaling groups

•    Go

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AutoSpotting is the leading open source spot market automation tool, optimized towards quick/easy/frictionless adoption of the EC2 spot market at any scale. It is usually set up to monitor existing long-running AutoScaling groups with minimal configuration changes(often just tagging them, but even that can be avoided by using their existing tags), yielding the usual 70%-90% Spot cost savings but in a better integrated, more cost effective and easier to adopt way than the alternative tools and solutions.

infrastructure aws automation cloudformation aws-lambda ec2 autoscaling-groups spot-instances cost ec2-instance amazon-web-services autoscaling aws-autoscaling golang-application ec2-spot terraform-module cheaper-spot-instances

aws-serverless-auth-reference-app - Serverless reference app and backend API, showcasing authentication and authorization patterns using Amazon Cognito, Amazon API Gateway, AWS Lambda, and AWS IAM

•    TypeScript

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SpaceFinder is a reference mobile app that allows users to book conference rooms, work desks, and other shared resources. The app showcases serverless authentication and authorization using the AWS platform.The mobile front-end is built using the Ionic 3 framework and client libraries to call AWS services and mobile backend APIs. The backend APIs themselves are powered by AWS services. The backend APIs are built using a serverless architecture, which makes it easy to deploy updates, and it also means that there are no servers to operationally manage.

amazon-cognito aws-cognito serverless iam serverless-architectures aws-lambda cognito cognito-quickstart authentication authorization auth amazon-api-gateway aws aws-apigateway

lambda-refarch-mobilebackend - Serverless Reference Architecture for creating a Mobile Backend

•    Objective-C

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The Mobile Backend reference architecture (diagram) demonstrates how to use AWS Lambda along with other services to build a serverless backend for a mobile application. The specific example application provided in this repository enables users to upload photos and notes using Amazon Simple Storage Service (Amazon S3) and Amazon API Gateway respectively. The notes are stored in Amazon DynamoDB, and are processed asynchronously using DynamoDB streams and a Lambda function to add them to an Amazon CloudSearch domain. In addition to the source code for the Lambda functions, this repository also contains a prototype iOS application that provides examples for how to use the AWS Mobile SDK for iOS to interface with the backend resources defined in the architecture.To run the full example application, you must first deploy the backend resources, and then compile and run the example iOS application.

lambda-refarch-mobilebackend - Serverless Reference Architecture for creating a Mobile Backend

•    Objective-C

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The Mobile Backend reference architecture (diagram) demonstrates how to use AWS Lambda along with other services to build a serverless backend for a mobile application. The specific example application provided in this repository enables users to upload photos and notes using Amazon Simple Storage Service (Amazon S3) and Amazon API Gateway respectively. The notes are stored in Amazon DynamoDB, and are processed asynchronously using DynamoDB streams and a Lambda function to add them to an Amazon CloudSearch domain. In addition to the source code for the Lambda functions, this repository also contains a prototype iOS application that provides examples for how to use the AWS Mobile SDK for iOS to interface with the backend resources defined in the architecture. To run the full example application, you must first deploy the backend resources, and then compile and run the example iOS application.