Powerful CLI tool to simplify Amazon ECS deployments, rollbacks & scaling
ecs-deploy simplifies deployments on Amazon ECS by providing a convinience CLI tool for complex actions, which are executed pretty often.
- support for complex task definitions (e.g. multiple containers & task role)
- easily redeploy the current task definition (including docker pull of eventually updated images)
- deploy new versions/tags or all containers or just a single container in your task definition
- scale up or down by adjusting the desired count of running tasks
- add or adjust containers environment variables
- run one-off tasks from the CLI
- automatically monitor deployments in New Relic
Deploy a new version of your service:
$ ecs deploy my-cluster my-service --tag 1.2.3
Redeploy the current version of a service:
$ ecs deploy my-cluster my-service
Scale up or down a service:
$ ecs scale my-cluster my-service 4
Updating a cron job:
$ ecs cron my-cluster my-task my-rule
Update a task definition (without running or deploying):
$ ecs update my-cluster my-task
The project is availably on PyPI. Simply run:
$ pip install ecs-deploy
Run via Docker
Instead of installing ecs-deploy locally, which requires a Python environment, you can run ecs-deploy via Docker. All versions starting from 1.7.1 are available on Docker Hub: https://cloud.docker.com/repository/docker/fabfuel/ecs-deploy
Running ecs-deploy via Docker is easy as:
docker run fabfuel/ecs-deploy:1.7.1
In this example, the stable version 1.7.1 is executed. Alternatively you can use Docker tags master or latest for the latest stable version or Docker tag develop for the newest development version of ecs-deploy.
Please be aware, that when running ecs-deploy via Docker, the configuration - as described below - does not apply. You have to provide credentials and the AWS region via the command as attributes or environment variables:
docker run fabfuel/ecs-deploy:1.7.1 ecs deploy my-cluster my-service --region eu-central-1 --access-key-id ABC --secret-access-key ABC
As ecs-deploy is based on boto3 (the official AWS Python library), there are several ways to configure and store the authentication credentials. Please read the boto3 documentation for more details (http://boto3.readthedocs.org/en/latest/guide/configuration.html#configuration). The simplest way is by running:
$ aws configure
Alternatively you can pass the AWS credentials (via –access-key-id and –secret-access-key) or the AWS configuration profile (via –profile) as options when you run ecs.
Currently the following actions are supported:
Redeploy a service either without any modifications or with a new image, environment variable and/or command definition.
Scale a service up or down and change the number of running tasks.
Run a one-off task based on an existing task-definition and optionally override command and/or environment variables.
Update a task definition by creating a new revision to set a new image, environment variable and/or command definition, etc.
cron (scheduled task)
Update a task definition and update a events rule (scheduled task) to use the new task definition.
For detailed information about the available actions, arguments and options, run:
$ ecs deploy --help $ ecs scale --help $ ecs run --help
All examples assume, that authentication has already been configured.
To redeploy a service without any modifications, but pulling the most recent image versions, run the follwing command. This will duplicate the current task definition and cause the service to redeploy all running tasks.:
$ ecs deploy my-cluster my-service
Deploy a new tag
To change the tag for all images in all containers in the task definition, run the following command:
$ ecs deploy my-cluster my-service -t 1.2.3
Deploy a new image
To change the image of a specific container, run the following command:
$ ecs deploy my-cluster my-service --image webserver nginx:1.11.8
This will modify the webserver container only and change its image to “nginx:1.11.8”.
Deploy several new images
The -i or –image option can also be passed several times:
$ ecs deploy my-cluster my-service -i webserver nginx:1.9 -i application my-app:1.2.3
This will change the webserver’s container image to “nginx:1.9” and the application’s image to “my-app:1.2.3”.
Deploy a custom task definition
To deploy any task definition (independent of which is currently used in the service), you can use the --task parameter. The value can be:
A fully qualified task ARN:
$ ecs deploy my-cluster my-service --task arn:aws:ecs:eu-central-1:123456789012:task-definition/my-task:20
A task family name with revision:
$ ecs deploy my-cluster my-service --task my-task:20
Or just a task family name. It this case, the most recent revision is used:
$ ecs deploy my-cluster my-service --task my-task
ecs will still create a new task definition, which then is used in the service. This is done, to retain consistent behaviour and to ensure the ECS agent e.g. pulls all images. But the newly created task definition will be based on the given task, not the currently used task.
Set an environment variable
To add a new or adjust an existing environment variable of a specific container, run the following command:
$ ecs deploy my-cluster my-service -e webserver SOME_VARIABLE SOME_VALUE
This will modify the webserver container definition and add or overwrite the environment variable SOME_VARIABLE with the value “SOME_VALUE”. This way you can add new or adjust already existing environment variables.
Adjust multiple environment variables
You can add or change multiple environment variables at once, by adding the -e (or –env) options several times:
$ ecs deploy my-cluster my-service -e webserver SOME_VARIABLE SOME_VALUE -e webserver OTHER_VARIABLE OTHER_VALUE -e app APP_VARIABLE APP_VALUE
This will modify the definition of two containers. The webserver’s environment variable SOME_VARIABLE will be set to “SOME_VALUE” and the variable OTHER_VARIABLE to “OTHER_VALUE”. The app’s environment variable APP_VARIABLE will be set to “APP_VALUE”.
Set environment variables exclusively, remove all other pre-existing environment variables
To reset all existing environment variables of a task definition, use the flag --exclusive-env
$ ecs deploy my-cluster my-service -e webserver SOME_VARIABLE SOME_VALUE --exclusive-env
This will remove all other existing environment variables of all containers of the task definition, except for the variable SOME_VARIABLE with the value “SOME_VALUE” in the webserver container.
Set a secret environment variable from the AWS Parameter Store
This option was introduced by AWS in ECS Agent v1.22.0. Make sure your ECS agent version is >= 1.22.0 or else your task will not deploy.
To add a new or adjust an existing secret of a specific container, run the following command:
$ ecs deploy my-cluster my-service -s webserver SOME_SECRET KEY_OF_SECRET_IN_PARAMETER_STORE
You can also specify the full arn of the parameter:
$ ecs deploy my-cluster my-service -s webserver SOME_SECRET arn:aws:ssm:<aws region>:<aws account id>:parameter/KEY_OF_SECRET_IN_PARAMETER_STORE
This will modify the webserver container definition and add or overwrite the environment variable SOME_SECRET with the value of the KEY_OF_SECRET_IN_PARAMETER_STORE in the AWS Parameter Store of the AWS Systems Manager.
Set secrets exclusively, remove all other pre-existing secret environment variables
To reset all existing secrets (secret environment variables) of a task definition, use the flag --exclusive-secrets
$ ecs deploy my-cluster my-service -s webserver NEW_SECRET KEY_OF_SECRET_IN_PARAMETER_STORE --exclusive-secret
This will remove all other existing secret environment variables of all containers of the task definition, except for the new secret variable NEW_SECRET with the value coming from the AWS Parameter Store with the name “KEY_OF_SECRET_IN_PARAMETER_STORE” in the webserver container.
Modify a command
To change the command of a specific container, run the following command:
$ ecs deploy my-cluster my-service --command webserver "nginx"
This will modify the webserver container and change its command to “nginx”. If you have a command that requries arugments as well, then you can simply specify it like this as you would normally do:
$ ecs deploy my-cluster my-service –command webserver “ngnix -c /etc/ngnix/ngnix.conf”
This works fine as long as any of the arguments do not contain any spaces. In case arguments to the command itself contain spaces, then you can use the JSON format:
$ ecs deploy my-cluster my-service –command webserver ‘[“sh”, “-c”, “while true; do echo Time files like an arrow $(date); sleep 1; done;”]’
More about this can be looked up in documentation. https://docs.aws.amazon.com/AmazonECS/latest/developerguide/task_definition_parameters.html#container_definitions
Set a task role
To change or set the role, the service’s task should run as, use the following command:
$ ecs deploy my-cluster my-service -r arn:aws:iam::123456789012:role/MySpecialEcsTaskRole
This will set the task role to “MySpecialEcsTaskRole”.
Ignore capacity issues
If your cluster is undersized or the service’s deployment options are not optimally set, the cluster might be incapable to run blue-green-deployments. In this case, you might see errors like these:
ERROR: (service my-service) was unable to place a task because no container instance met all of its requirements. The closest matching (container-instance 123456-1234-1234-1234-1234567890) is already using a port required by your task. For more information, see the Troubleshooting section of the Amazon ECS Developer Guide.
There might also be warnings about insufficient memory or CPU.
To ignore these warnings, you can run the deployment with the flag --ignore-warnings:
$ ecs deploy my-cluster my-service --ignore-warnings
In that case, the warning is printed, but the script continues and waits for a successful deployment until it times out.
The deploy and scale actions allow defining a timeout (in seconds) via the --timeout parameter. This instructs ecs-deploy to wait for ECS to finish the deployment for the given number of seconds.
To run a deployment without waiting for the successful or failed result at all, set --timeout to the value of -1.
Scale a service
To change the number of running tasks and scale a service up and down, run this command:
$ ecs scale my-cluster my-service 4
Running a Task
Run a one-off task
To run a one-off task, based on an existing task-definition, run this command:
$ ecs run my-cluster my-task
You can define just the task family (e.g. my-task) or you can run a specific revision of the task-definition (e.g. my-task:123). And optionally you can add or adjust environment variables like this:
$ ecs run my-cluster my-task:123 -e my-container MY_VARIABLE "my value"
Run a task with a custom command
You can override the command definition via option -c or --command followed by the container name and the command in a natural syntax, e.g. no conversion to comma-separation required:
$ ecs run my-cluster my-task -c my-container "python some-script.py param1 param2"
The JSON syntax explained above regarding modifying a command is also applicable here.
Run a task in a Fargate Cluster
If you want to run a one-off task in a Fargate cluster, additional configuration is required, to instruct AWS e.g. which subnets or security groups to use. The required parameters for this are:
$ ecs run my-fargate-cluster my-task --launchtype=FARGATE --securitygroup sg-01234567890123456 --subnet subnet-01234567890123456 --public-ip
You can pass multiple subnet as well as multiple securitygroup values. the public-ip flag determines, if the task receives a public IP address or not. Please see ecs run --help for more details.
With ECS deploy you can track your deployments automatically. Currently only New Relic is supported:
To record a deployment in New Relic, you can provide the the API Key (Attention: this is a specific REST API Key, not the license key) and the application id in two ways:
Via cli options:
$ ecs deploy my-cluster my-service --newrelic-apikey ABCDEFGHIJKLMN --newrelic-appid 1234567890
Or implicitly via environment variables NEW_RELIC_API_KEY and NEW_RELIC_APP_ID
$ export NEW_RELIC_API_KEY=ABCDEFGHIJKLMN $ export NEW_RELIC_APP_ID=1234567890 $ ecs deploy my-cluster my-service
Optionally you can provide an additional comment to the deployment via --comment "New feature X" and the name of the user who deployed with --user john.doe
If the service configuration in ECS is not optimally set, you might be seeing timeout or other errors during the deployment.
The timeout error means, that AWS ECS takes longer for the full deployment cycle then ecs-deploy is told to wait. The deployment itself still might finish successfully, if there are no other problems with the deployed containers.
You can increase the time (in seconds) to wait for finishing the deployment via the --timeout parameter. This time includes the full cycle of stopping all old containers and (re)starting all new containers. Different stacks require different timeout values, the default is 300 seconds.
The overall deployment time depends on different things:
- the type of the application. For example node.js containers tend to take a long time to get stopped. But nginx containers tend to stop immediately, etc.
- are old and new containers able to run in parallel (e.g. using dynamic ports)?
- the deployment options and strategy (Maximum percent > 100)?
- the desired count of running tasks, compared to
- the number of ECS instances in the cluster
There are some other libraries/tools available on GitHub, which also handle the deployment of containers in AWS ECS. If you prefer another language over Python, have a look at these projects:
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