This repository contains sample projects that can be deployed on your local machine using LocalStack.
Each example in the repository is prefixed with the name of the AWS service being used. For example, the elb-load-balancing directory contains examples that demonstrate how to use the Elastic Load Balancing service with LocalStack. Please refer to the sub directories for more details and instructions on how to start the samples.
- Docker
awslocalCLI- Serverless
- Terraform
make&jq
All samples require a valid LocalStack for AWS license. Your license provides a LOCALSTACK_AUTH_TOKEN to activate LocalStack. Set it before running any sample:
export LOCALSTACK_AUTH_TOKEN=<your-auth-token>
Alternatively, use the LocalStack CLI to persist the token:
localstack auth set-token <your-auth-token>
You can find your Auth Token on the LocalStack Web Application.
| Sample Name | Description |
|---|---|
| Serverless Websockets | API Gateway V2 websocket APIs deployed via the Serverless framework |
| RDS Database Queries | Running queries locally against an RDS database |
| RDS Failover Test | Running a failover test against an RDS global cluster |
| Neptune Graph Database | Running queries locally against a Neptune Graph database |
| Lambda Event Filtering | Lambda event source filtering with DynamoDB and SQS |
| Glacier & S3 select queries | Using Glacier API and running S3 Select queries locally |
| Cloudwatch Metrics alarm | Triggering a Cloudwatch metrics alarm based on a failing Lambda |
| EC2 with Docker backend | Running EC2 instances with Docker backend |
| Cognito with JWT | Running Cognito authentication and user pools locally |
| Transfer API with S3 | Using the Transfer API to upload files to S3 |
| Codecommit with Git repository | Using the Codecommit API to create and push to a Git repository |
| Lambda Debugging SAM Java | Debugging Java Lambda functions using AWS SAM |
| Lambda Debugging SAM JavaScript | Debugging JavaScript Lambda functions using AWS SAM |
| Lambda Debugging SAM Python | Debugging Python Lambda functions using AWS SAM |
| Lambda Debugging SAM TypeScript | Debugging TypeScript Lambda functions using AWS SAM |
| IAM Policy Enforcement | Enforcement of IAM policies when working with local cloud APIs |
| Lambda Hot Reloading | Hot reloading Lambda functions locally |
| IoT Basics | Usage of IoT APIs locally |
| REST API using Chalice | Deploying a REST API using the Chalice framework |
| ECS ECR Container application | Pushing Docker images to ECR and running them locally on ECS |
| Athena queries over S3 | Running Athena queries over S3 files locally |
| Terraform resources | Deploying various AWS resources via Terraform |
| Lambda Function URLs (JavaScript) | Invoking Lambda functions via HTTP(S) URLs using JavaScript |
| Lambda Function URLs (Python) | Invoking Lambda functions via HTTP(S) URLs using Python |
| Sagemaker inference | Creating & invoking a Sagemaker endpoint locally with MNIST dataset |
| MSK with Glue Schema Registry | Use of MSK, Glue Schema Registry, Glue ETL, and RDS |
| AppSync GraphQL | Deploying a GraphQL API using AppSync |
| Lambda XRay tracing | Using Lambda XRay tracing locally |
| Serverless Lambda Layers | Using Lambda layers locally deployed via the Serverless framework |
| Java Notification App | Notification app using AWS Java SDK, SNS, SQS, SES, deployed via CloudFormation |
| Lambda Container images | Deploying Lambda functions as container images |
| Glue crawler with RedShift | Glue Crawler to populate the Glue metadata store with the table schema of RedShift database tables |
| API Gateway custom domain | Using API Gateway v2 endpoints using custom domain names, deployed via the Serverless framework |
| CDK resources | Deploying various AWS resources via CDK |
| Glue for ETL jobs | Using Glue API to run local ETL jobs |
| Message Queue broker | Using MQ API to run local message queue brokers |
| ELB Load Balancing | Using ELBv2 Application Load Balancers locally, deployed via the Serverless framework |
| Reproducible ML | Train, save and evaluate a scikit-learn machine learning model using AWS Lambda and S3 |
| Lambda PHP/Bref CDK App | Running PHP/Bref Lambda handler locally, deployed via AWS CDK |
| Step Functions with Lambda | Orchestrating Lambda functions using AWS Step Functions |
| Multi-Account S3 Access | Accessing S3 resources across different AWS accounts and regions |
| Route53 DNS Failover | Route53 DNS failover based on health checks |
| EMR Serverless Sample | Running EMR Serverless jobs locally |
| EMR Serverless Spark | Running Java Spark jobs on EMR Serverless |
| EMR Serverless Python Dependencies | Adding Python dependencies to EMR Serverless PySpark jobs |
| Testcontainers Java Sample | Using LocalStack Testcontainers with RDS in Java |
To check out a single sample, you can use the following commands:
mkdir localstack-samples && cd localstack-samples git init git remote add origin -f [email protected]:localstack/localstack-pro-samples.git git config core.sparseCheckout true echo <LOCALSTACK_SAMPLE_DIRECTORY_NAME> >> .git/info/sparse-checkout git pull origin master
The above commands use sparse-checkout to only pull the sample you are interested in. You can find the name of the sample directory in the table above.
All samples should have a Makefile to unify the execution of the otherwise heterogeneous samples. It needs to fulfill two criteria:
- The sample should be executable independently, since it can be checked out on its own (see Checking out a single sample).
- It should contain a
test-citarget to be executed automatically within the CI pipeline. This step needs to take care of all infrastructure tasks (starting/stopping/logs/etc) in addition to any sample commands executed.
A typical Makefile looks like this:
export AWS_ACCESS_KEY_ID ?= test export AWS_SECRET_ACCESS_KEY ?= test export AWS_DEFAULT_REGION=us-east-1 SHELL := /bin/bash usage: ## Show this help @fgrep -h "##" $(MAKEFILE_LIST) | fgrep -v fgrep | sed -e 's/\\$$//' | sed -e 's/##//' install: ## Install dependencies @which localstack || pip install localstack @which awslocal || pip install awscli-local ## install whatever else you need, like node modules, python packages, etc. @test -e node_modules || npm install @test -e .venv || (python3 -m venv .venv; source .venv/bin/activate; pip install -r requirements.txt) run: ## Run the actual sample steps/commands. This assumes LocalStack is up and running. ./run.sh start: ## Start LocalStack in detached mode @test -n "${LOCALSTACK_AUTH_TOKEN}" || (echo "LOCALSTACK_AUTH_TOKEN is not set. Get your auth token at https://localstack.cloud/pricing."; exit 1) localstack start -d stop: ## Stop the Running LocalStack container @echo localstack stop ready: ## Make sure the LocalStack container is up @echo Waiting on the LocalStack container... @localstack wait -t 30 && echo LocalStack is ready to use! || (echo Gave up waiting on LocalStack, exiting. && exit 1) logs: ## Save the logs in a separate file, since the LS container will only contain the logs of the last sample run. @localstack logs > logs.txt test-ci: ## Execute the necessary targets in the correct order for an automatic execution. make start install ready run; return_code=`echo $$?`;\ make logs; make stop; exit $$return_code; .PHONY: usage install run start stop ready logs test-ci