The Full integration level provides all the features that CloudReactor has to offer. Compared to the Simple integration level, it has these additional features:
- Task scheduling
- ECS service setup, including load balancer configuration
- Tasks show up in the CloudReactor dashboard before they execute
To gain these features, you need to register your Task beforehand with the CloudReactor API. Below, we’ll use the aws-ecs-cloudreactor-deploy Docker image to deploy to ECS as well do the CloudReactor registration. It’s also possible to make API calls to create Tasks directly if you know the ECS task definition.
The steps to grant CloudReactor Task management access are a pre-requisite for full integration.
The easiest way to gain full integration capabilities is to use the aws-ecs-cloudreactor-deploy Docker image to build and deploy your project. It deploys multiple tasks per project to both ECS and CloudReactor, so it alleviates the need to do the setup yourself.
aws-ecs-cloudreactor-deploy needs to be configured with AWS credentials that allow it to deploy Docker images to AWS ECR and create tasks in ECS on your behalf.
You can either:
- Use access keys or a role associated with an admin user or a power user with broad permissions; or
- Create a user and role with specific permissions for deployment.
If you’re using an admin or power user, feel free to skip to the next step.
If you want to use a new user and role, we’ve prepared a “CloudReactor AWS deployer” CloudFormation template. Feel free to inspect the template. Note than admin user has to upload this tempate, as it creates an additional user. When ready, log into the AWS management console, select the CloudFormation service, and upload this template. It will create a user with all the necessary permissions. When the CloudFormation template has completed deployment, it will output user credentials, save these for use later!).
For more details, see AWS permissions required to deploy
If you followed the instructions to grant CloudReactor Task management access, you’ve already created an API key with the
Developer access level. Otherwise, do that now.
Next, create another API key that your Task will use to communicate with CloudReactor while it’s running. Give the API key a name and associate it with the Run Environment you created. Ensure the Group is correct, the Enabled checkbox is checked, and the Access Level is
Task. Then select the Save button. You should then see your new API key listed. Copy the value of the key. This is the
Task API key.
If you code is written in python, you can fork the cloudreactor-python-ecs-quickstart project which also includes a lot of goodies for python development, like:
- Runs, tests, and deploys everything with Docker, no local python installation required
- Uses pip-tools to manage only top-level python library dependencies
- Uses pytest (testing), pylint (static code analysis), mypy (static type checking), and safety (security vulnerability checking) for quality control
- Uses GitHub Actions for Continuous Integration (CI)
You can now skip to setting Task properties.
If you have an existing project you want to deploy, follow the steps below.
First, if you haven’t already, Dockerize your project. The steps are very language dependent, so do a web search for “dockerize [your language]”.
If you haven’t already, ensure that you Docker image contains the files necessary to run proc_wrapper. This could either be a standalone executable, or having python 3.6+ installed and installing the cloudreactor-procwrapper package. Your Dockerfile should call proc_wrapper as its entrypoint. If using a standalone Linux executable:
ENTRYPOINT ./proc_wrapper $TASK_COMMAND
If using the python package:
ENTRYPOINT python -m proc_wrapper $TASK_COMMAND
Now let’s work on the build and deployment process. If you need to add custom build steps, such as compilation, see Build Customization.
Following that, copy and optionally modify
docker-compose-deploy.yml if you are working on a Windows machine) from the aws-ecs-cloudreactor-deploy repository into your project root directory.
You will need to remap your files your project into the Docker build context like this:
-v $PWD/Dockerfile:/work/docker_context/Dockerfile -v $PWD/src:/work/docker_context/src
Then your Dockerfile will see the contents of your
src directory in
Afterwards, copy the
deploy_config directory from the aws-ecs-cloudreactor-deploy repository into your project’s root directory; we’ll modify the contained files with the Task properties next.
Whether you are starting with an example quickstart project or modifying an existing project, the next step is to set properties for each Task in each deployment environment. Each deployment environment is associated with a Run Environment, and in most cases the mapping is one-to-one.
Common properties for all Tasks and deployment environments can be entered in
deploy_config/vars/common.yml. For every deployment environment (“staging”, “production”) that you have, create a file
deploy_config/vars/<environment>.yml that is based on
deploy_config/vars/example.yml and add your settings there.
example.yml have many properties you can uncomment and set, such as the subnets that you want your Task running in. In most cases, you can leave properties unset, defaulting to the properties in the Run Environment associated with the deployment environment. Task Configuration for aws-ecs-cloudreactor-deploy contains more details on how to set properties.
deploy.env and and fill in your AWS access key, access key secret, and default region. The access key and secret would be for the AWS user you plan on using to deploy with, possibly created in the section “Select or create user and/or role for deployment”. You may also populate this file with a script you write yourself, for example with something that uses the AWS CLI to assume a role and gets temporary credentials. If you are running this on an EC2 instance with an instance profile that has deployment permissions, you can leave this file blank.
Finally, deploy. In a bash shell, run:
./deploy.sh <environment> [TASK_NAMES]
or in Windows:
.\deploy.cmd <environment> [TASK_NAMES]
TASK_NAMES is an optional, comma-separated list of Tasks to deploy. If omitted, all tasks defined in
./deploy/vars/common.yml will be deployed.