FabulAWS uses Fabric for deployment, with which some familiarity is strongly recommended. This page assumes that you’ve completed the necessary setup described in the Server Architecture. You will also need a local development environment setup as described in New Project Setup.


When deploying to an environment, your local copy of the code should be up to date and must also have a checkout of the correct branch. Environments can be mapped to branches in the fabulaws-config.yml file.

Testing environment

The testing environment is usually a temporary environment that can be used for load testing, deployment testing, or other activities that would otherwise negatively impact the primary environment for testing new features (see Staging environment below).

To create a new instance of the testing environment, you can use the create_environment command to Fabric, like so:

fab create_environment:myproject,testing

Prior to running this command, be certain that all prior instances of testing servers have been terminated via the AWS console. This command will create all the required servers in parallel. To avoid difficulty with determining which server failed to be created when a problem is encountered, the logs for server creation are saved to separate files. Always check these files to ensure that the servers were created successfully.

Staging environment

The staging environment is typically used for testing and quality assurance of new features. It also serves as a testing ground for doing the deployment itself. New features (even small bug fixes) should be deployed to and tested on the staging environment prior to being deployed to the production environment.

The staging environment is usually a copy of the production environment running on smaller (cheaper) virtual machines at EC2. It also typically contains a recent snapshot of the production database, so any issues specific to the production environment can be tested on staging without affecting usability of the production site.

Production environment

The production environment is typically hosts the live servers in use by the the application’s end-users.

Deployment methods

Since FabulAWS uses Amazon Autoscaling, special care must be taken to update the autoscaling image at the same time as new code is deployed.

Autoscaling: Updating the image

Because AMI creation can be a time-intensive part of the process, it can be done separately ahead of time to prepare for a deployment.

To create an autoscaling AMI and launch configuration based on the current version of the code (from the appropriate branch - see above), run the following command:

fab create_launch_config_for_deployment:myproject,<environment>

This command will print out the name of the created launch configuration, which can be passed into the associated autoscaling deployment methods below. If needed, the launch configuration names and associated images can also be found via the AWS console.

Autoscaling: Full deployment

A “full” deployment should be used any time there are backwards-incompatible updates to the application, i.e., when having two versions of the code running simultaneously on different servers might have damaging results or raise errors for users of the site. Note that this type of deployment requires downtime, which may need to be scheduled ahead of time depending on which environment is impacted.

With autoscaling, a full deployment works as follows:

  1. First, the autoscaling group’s ability to add new instances to the load balancer is suspended, a new launch configuration for the new version of the code is installed, and the desired number of instances for the group is doubled. This has the effect of spinning up all the new required instances without adding them to the load balancer.
  2. Once those instances have been created, the “upgrade in progress” message is displayed on all the servers, deploy_worker is run to update the database schema and any static media, and the autoscaling group’s ability to add instances to the load balancer is resumed. The process then waits for all instances to be healthy in the load balancer.
  3. Finally, the old instances in the group are terminated, and the “upgrade in progress” message is removed from the new servers.

The syntax for completing a full deployment is as follows:

fab deploy_full:myproject,<environment>[,<launch config name>]

The launch configuration name is optional, and one will be created automatically if not specified.


This command does not update secrets from your local file to the servers. If you want to do that, explicitly run fab <environment> update_server_passwords before running this command.

Autoscaling: Serial deployment

A “serial” deployment can be used any time the changes being deployed are minimal enough that having both versions of the code running simultaneously will not cause problems. This is usually the case any time there are minor, code-only (non-schema) updates. Each server points to a separate copy of the static media specific to the version of the code that it’s running, so backwards incompatible CSS and JavaScript changes can safely be deployed serially.

Serial deployments with autoscaling work by gradually marking instances in the autoscaling group as unhealthy, and then waiting for the group to create a new, healthy instance before proceeding. A serial deployment can be started as follows:

fab deploy_serial:cmyproject,<environment>[,<launch config name>]

Again, the launch config is optional and one will be created automatically if not specified.


This command does not update secrets from your local file to the servers. If you want to do that, explicitly run fab <environment> update_server_passwords before running this command.


You may see errors that look like this while running a serial deployment:

400 Bad Request
<ErrorResponse xmlns="">
    <Message>Could not find EC2 instance i-1bb70c35.</Message>

These errors are expected and simply mean that the elastic load balancer is not yet aware of the newly created instance.

Suspending and restarting autoscaling processes

If for any reason autoscaling needs to be suspended, this can be accomplished through Fabric. To suspend all autoscaling processes, simply run:

fab suspend_autoscaling_processes:myproject,<environment>

To resume autoscaling once any issues have been resolved, run:

fab resume_autoscaling_processes:myproject,<environment>

A note about usernames

If you get a prompt that looks something like this when you attempt to deploy, it’s quite possible that you’re giving the remote server the wrong username (or you don’t have access to the servers to begin with):

[] Passphrase for private key:

When deploying to any environment, if your local username is different from the username you use to login to the remote server, you need to give Fabric a username on the command line, like so:

fab -u <remoteusername> <environment> <commands>