Amazon Web Services Deployment

Deployment is driven by Packer, Troposphere, the AWS Command Line Interface and Boto, the AWS SDK for Python. It requires some setup in your Amazon account, editing a configuration file, creating AMIs, and launching a stack.

Dependencies

To install the Python deployment dependencies, use pip:

$ cd deployment
$ pip install -r requirements.txt

Next, install Packer using the steps detailed on Packer's website.

Create Identity and Access Management (IAM) roles

See Create an IAM Instance Profile for Your Amazon EC2 Instances.

Configure an AWS Profile using the AWS CLI

Using the AWS CLI, create an AWS profile:

$ aws configure --profile mmw-stg

You will be prompted to enter your AWS credentials, along with a default region. These credentials will be used to authenticate calls to the AWS API when using Boto, Packer, and the AWS CLI.

Edit the configuration file

A configuration file is required to launch the stack. An example file (default.yml.example) is available in the current directory.

Launch and manage stacks

Stack launching is managed with mmw_stack.py. This command provides an interface for automatically generating AMIs and launching Model My Watershed stacks.

Generating AMIs

Before launching the Model My Watershed stack, AMIs for each service need to be generated:

$ ./mmw_stack.py create-ami --aws-profile mmw-stg --mmw-profile staging \
                            --machine-type mmw-{app,monitoring,tiler,worker}

Pruning AMIs

After creating several AMIs, older ones become stale and are no longer needed. To prune them use:

$ ./mmw_stack.py prune-ami --aws-profile mmw-stg --mmw-profile staging \
                           --keep 5 --machine-type mmw-{app,monitoring,tiler,worker}

Launching Stacks

After successfully creating AMIs, you can launch a Model My Watershed stack with the launch-stacks subcommand. To view all options for the launch-stacks subcommand, you can use the --help option.

Using the parameters set in default.yml, you can launch a full stack with the following command:

$ ./mmw_stack.py launch-stacks --aws-profile mmw-stg --mmw-profile staging \
                               --mmw-config-path default.yml