Rainbow - AWS Cloudformation on steroids

Working with Cloudformation inhouse, we discovered the following needs:

• Break a big stack into several smaller ones
• Reference resources between stacks and regions
• Add dynamic template preprocessing logic
• Compose a stack from reusable 'building blocks'
• Improve readability by coding templates and parameters in YAML (and have comments!)

Installation

pip install rainbow-cfn

Usage

• Configure boto
• Run rainbow

Datasources

What is a datasource

Datasource is a key-value mapping which Rainbow uses to fill Cloudformation templates parameters
Datasources can be YAML files, other Cloudformation stacks (resources, outputs and even parameters), files, etc.
The system is fully extensible for you to add any other datasources you might want.

Every parameter the template requires is being looked up on the list of datasources given to the rainbow CLI tool. A parameter can exist on multiple datasources, having the first match returned.
For example, say you run rainbow with --data-source yaml:a.yaml --data-source yaml:b.yaml --data-source:c.yaml, the files are:

# a.yaml
InstanceType: m1.small
KeyName: omrib-laptop
AvailabilityZones:
  - us-east-1a

# b.yaml
AutoScalingGroupMinSize: 0
AutoScalingGroupMaxSize: 1
Image: PreciseAmd64PvInstanceStore

# c.yaml
InstanceType: m1.large

Lets say your template requires the following parameters:

Parameters:
  AvailabilityZones: {Type: CommaDelimitedList}
  KeyName: {Type: String}
  AutoScalingGroupMinSize: {Type: String}
  AutoScalingGroupMaxSize: {Type: String}
  Image: {Type: String}
  InstanceType: {Type: String}

The lookup order is a.yaml, b.yaml and c.yaml. Rainbow will fill all the parameters as follows:

AvailabilityZones: us-east-1a (from a.yaml)
KeyName: omrib-laptop (from a.yaml)
AutoScalingGroupMinSize: 0 (from b.yaml)
AutoScalingGroupMaxSize: 1 (from b.yaml)
Image: PreciseAmd64PvInstanceStore (from b.yaml)
InstanceType: m1.small (from a.yaml. Even though the value exists in c.yaml as well, because the yaml:a.yaml datasource appears before yaml:c.yaml, the value will be m1.small and not m1.large)

Another cool feature of the YAML datasource is pointers. You can make the lookup begin all over again when a key has a value that begins with $. For example, when running rainbow with --data-source yaml:a.yaml --data-source yaml:b.yaml:

# a.yaml
AdminKeyName: omrib-laptop

# b.yaml
KeyName: $AdminKeyName
AdminKeyName: oren-laptop

The value of KeyName (b.yaml) points to AdminKeyName, which exists both on a.yaml and b.yaml, but the a.yaml value will be used, meaning KeyName equals omrib-laptop.
Pointers can be used to reference a key from a different type of datasource.

Available datasources

YAML

yaml[:rootkey]:path/to/file - stores all keys (starting from rootkey, if given) with their values

cfn_resources

cfn_resources[:region]:stackname - stores a logical resource to physical resource mapping. Read more about Cloudformation resources

cfn_outputs

cfn_outputs[:region]:stackname - stores a output to value mapping. Read more about Cloudformation outputs

cfn_parameters

cfn_parameters[:region]:stackname - input parameters to value mapping. You can use this as the only datasource when you only want to modify the template without touching the parameters.

file

file:name:path/to/file - stores a single key name with the value of the file content

file64

file64:name:path/to/file - same as file, but returns a BASE64 string instead of plaintext

Rainbow functions

Rb::InstanceChooser

From a given list of possible instance types, choose the first one that exists on that region.
Suppose you have a CFN stack that should be using a c3.large instance, but in a particular region that instance family is not yet supported. In that case, you want it to fallback to c1.medium.
A code of {'Rb::InstanceChooser': ['c3.large', 'c1.medium']} will evaluate to c3.large on regions that supports it and c1.medium on regions that don't.