- Pre-requisites
- Install AWS Copilot
- Deploy Sample Application with ONE command only
- BUILD-Deploy Microservices Application
- RELEASE-Deploy Release Pipeline for the Microservices Application
- OPERATE-Monitor Logs and Status
- Clean up
- References and More
AWS Copilot is an open source command line interface that makes it easy for developers to BUILD,RELEASE, and OPERATE production ready containerized applications on AWS App Runner, Amazon ECS, and AWS Fargate. You can start simple with just a Dockerfile and then grow with addons. You can work across multiple AWS accounts, and regions. Add more automation and have more visibility in your application’s health.
Using AWS CloudFormation, it will automate all this so you can only work on building efficient containers and copilot will take care of How you build, release and operate on your code. It's an interactive way to deploy some standard application environments for you to quickly setup your microservices application.
For example, a 'Load Balanced Web Service' would look something like this :
You will need to have the latest version of the AWS CLI installed and configured before running the deployment script.
After installing the AWS CLI, simply run the 'aws configure' command once. This setups the default profile in your environment.
If you need help installing and configuring, please follow the links below:
The easiest way is to create an AWS Cloud9 environment that comes pre-built with pre-requisites. Just run 'aws configure' once and you are good to go.
Installing AWS Copilot is easy. Checkout the manual instructions based on your Operating System in the Copilot Docs.
For Linux x86 (64-bit), use following command :
curl -Lo copilot https://github.com/aws/copilot-cli/releases/latest/download/copilot-linux && \
chmod +x copilot && \
sudo mv copilot /usr/local/bin/copilot && \
copilot --help && \
copilot --versionAt the time of writing this Readme, copilot was at version: v1.8.0
To deploy a sample Load Balanced Web Service application with just one command, run the following command :
git clone https://github.com/aws-samples/amazon-ecs-cli-sample-app.git demo-app && \
cd demo-app && \
copilot init --app demo \
--name api \
--type 'Load Balanced Web Service' \
--dockerfile './Dockerfile' \
--port 80 \
--deployThis will clone the AWS sample app, and initiate the deployment of the application. It will take few minutes for it to automatically create basic networking infrastructure, build your docker image, create a repository in Amazon ECR, push the docker image, create the Amazon ECS Clusters, ALB, and finally create tasks. In the end, it will provide you with a URL that points to your deployed sample application.
In real world, you would have a microservices application to be deployed. Following will walk you through individual commands of Copilot that can deployed individual components of your microservices application, build a release pipeline and showcase how can view logs & health status of your application.
About the Sample Microservices Application This is a reference architecture that shows a containerized Node.js microservices application to using AWS Copilot.
The microservices app was developed from the AWS Sample here
The sample has 3 services - users,threads,posts - defined behind an Amazon Application Load Balancer (ALB), and we create rules on the ALB that direct requests that match a specific path to a specific service. So each service will only serve one particular class of REST object, and nothing else. This will give us some significant advantages in our ability to independently monitor and independently scale each service.
Microservices Application Architecture
The typical flow of the commands will be based on above architecture.
- Create the app
git clone https://github.com/gaonkarr/aws-copilot-demo.git && \
cd aws-copilot-demo && \
copilot app init social-media-app- Create the TEST environment in Region of your choice. Following creates it in ap-southeast-2.
copilot env init --name test --region ap-southeast-2 --default-config- Create the PROD environment in Region of your choice. Following creates it in ap-northeast-1. Notice the --prod flag. This is helpful to identify production environments. It is also automatically considered production when the pipeline is create in step .
copilot env init --name prod --region ap-northeast-1 --default-config --prod- Create a Service for "Users"
copilot svc init --name users \
--svc-type "Load Balanced Web Service" \
--dockerfile ./services/users/Dockerfile- Step 4 creates a manifest file for the service under folder 'copilot/users/manifest.yaml'. In the manifest file, can make any changes to the default configurations for the service. Open this file and add following code to the end. This will tell configure the test environment with 1 task while the prod environment will have 2 tasks. Saved the file before proceeding.
environments:
test:
count: 1 # Number of tasks to run for the "test" environment.
prod:
count: 2 # Number of tasks to run for the "prod" environment.- Deploy the "Users" service in TEST environment
copilot svc deploy --name users --env test- Deploy the "Users" service in PRODUCTION environment
copilot svc deploy --name users --env prodOptionally, You can repeat steps 4-6 for every new service you wish to deploy. Example, repeat following for the "Threads" and "Posts" services:
copilot svc init --name threads --svc-type "Load Balanced Web Service" --dockerfile ./services/threads/Dockerfile
copilot svc deploy --name threads --env test
copilot svc deploy --name threads --env prod
copilot svc show
copilot svc init --name posts --svc-type "Load Balanced Web Service" --dockerfile ./services/posts/Dockerfile
copilot svc deploy --name posts --env test
copilot svc deploy --name posts --env prod
copilot svc showYou can open each service in each environment using the URL provided in the output. Make sure to add '/api/service-name' to view each service individually.
- Use the show command to check status of your environment deployments
copilot svc show
copilot env show --name test
copilot env show --name prod
copilot app show
- Initialize the CodePipeline creation. This will create manifest files - pipeline.yml and buildspec.yml in the copilot folder.
copilot pipeline init- Add these to your git repository, commit and push your code.
git add copilot/pipeline.yml copilot/buildspec.yml copilot/.workspace && \
git commit -m "Adding pipeline artifacts" && \
git push- Deploy the copilot pipeline using update command and check the status.
copilot pipeline update
copilot pipeline status
copilot svc logs
copilot svc status
Remember to delete all the resources once you are done testing.
copilot app delete
Explore advanced features – addons, storage, sidecars, etc
AWS Copilot CLI repository - https://github.com/aws/copilot-cli/
AWS Copilot CLI documentation - https://aws.github.io/copilot-cli/
Guides and resources - https://aws.github.io/copilot-cli/community/guides/
Containers from the Couch videos - https://www.youtube.com/c/ContainersfromtheCouch/search?query=copilot