Tropoform

Tropoform is a tool that provides a terraform like interface for deploying standalone AWS Cloud Formation stacks or stacks created by troposphere. Tropoform provides plan, apply, list, output & destroy operations on cloudformation stacks.

Requirements

• Python3.6+

Installation

To install the latest version of tropoform

pip install tropoform --user --upgrade

For development projects, it is advised to install in a python virtual environment

Or you can install from source https://github.com/cloudshiftstrategies/tropoform

Usage

use tropoform -h for help

$ tropform -h
usage: tropoform [-h] [-v]
                    {apply,plan,destroy,list,output,parameters,reason} ...

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         get DEBUG logging

operation:
  {apply,plan,destroy,list,output,parameters,reason}
    apply               create or update stack
    plan                view change plan
    destroy             remove stack
    list                list stacks
    output              view stack outputs
    parameters          list parameters used in a stack
    reason              list reasons for failed stack

see detailed usage help for an operation tropoform apply -h

usage: tropoform.py apply [-h] (-m MODULE_NAME | -t TEMPLATE_FILE)
                          [-p PARAMETER_FILES] [-c CAPABILITIES] [-r REGION]
                          [--auto_approve]
                          stack_name

positional arguments:
  stack_name            The name of the cloud formation stack on which to
                        perform operation. If a module exists in the current
                        working directory that matches the stack_name and has
                        a get_template() method, module_name is not required

optional arguments:
  -h, --help            show this help message and exit
  -m MODULE_NAME, --module_name MODULE_NAME
                        The name of the python troposphere module that will
                        create the template. Module must have a get_template()
                        method that returns a valid troposphere.Template
                        object
  -t TEMPLATE_FILE, --template_file TEMPLATE_FILE
                        The path to a cloud formation template file.
  -p PARAMETER_FILES, --parameter_files PARAMETER_FILES
                        Comma separated yaml parameter files that will be
                        passed to cloud formation as parameters
  -c CAPABILITIES, --capabilities CAPABILITIES
                        Comma separated list of AWS capabilities. default:
                        CAPABILITY_NAMED_IAM
  -r REGION, --region REGION
                        The name of the AWS region to perform operations.
                        default is the env variable: AWS_DEFAULT_REGION
  --auto_approve        If set, user will not be prompted to approve changes.
                        default=False

Usage Example

1. Create a cloud formation template using yaml or json formation

   OR

   Create a python module (script) using troposphere that has at least one method called get_template() which returns the un-rendered troposphere. Template() object.

   In the example.py script below, we create an IAM user inside the function get_template() and return the completed template object

   example.py

   from troposphere import Template
   from troposphere import iam
   
   def get_template():
       template = Template()
       template.add_resource(
           iam.User(
               "testIamUser",
               UserName="tropoform_test_user"
           )
       )
       return template
   

2. Configure your AWS credentials https://docs.aws.amazon.com/sdk-for-java/v1/developer-guide/setup-credentials.html so that you can make API / CLI calls.

   • Test your credentials with an awscli command like aws s3 ls
   • or you can test the boto3 python api python3 -c "import boto3; client = boto3.client('s3'); print(client.list_buckets())"

3. Run a tropoform plan on the stack and see that one IAM User resource will be created

   Using a cloud formation template

   $ tropoform plan myStack -t example_cfn_template.yaml
   STACK: myStack is not yet deployed
   STACK: myStack creates 1
   # ) action   logical_id                resource_type
    1) Create   testIamUser               AWS::IAM::User
   

   Or using a troposphere module

   $ tropoform plan myStack -m example.py
   STACK: myStack is not yet deployed
   STACK: myStack creates 1
   # ) action   logical_id                resource_type
    1) Create   testIamUser               AWS::IAM::User
   

4. Use tropofrom apply (create) the stack

   Using a cloud formation template

   $ tropoform apply myStack -t example_template.json
   STACK: myStack, Current Status: None
   CREATING Stack: myStack with 1 resources
   Are you sure? [yes|no] yes
   STACK: myStack, Status: CREATE_IN_PROGRESS - 16:36:10
   STACK: myStack, Status: CREATE_IN_PROGRESS - 16:36:25
   STACK: myStack, Status: CREATE_COMPLETE - 16:36:41
   STACK: myStack deployed 1 resources in 00:00:48
   STACK OUTPUTS:
   

   Or using a troposphere module

   $ tropoform apply myStack -m example.py
   STACK: myStack, Current Status: None
   CREATING Stack: myStack with 1 resources
   Are you sure? [yes|no] yes
   STACK: myStack, Status: CREATE_IN_PROGRESS - 16:36:10
   STACK: myStack, Status: CREATE_IN_PROGRESS - 16:36:25
   STACK: myStack, Status: CREATE_COMPLETE - 16:36:41
   STACK: myStack deployed 1 resources in 00:00:48
   STACK OUTPUTS:
   

5. Use tropoform list to see stacks that are applied. Notice it is in status CREATE_COMPLETE

   $ tropoform list
   stack_name           stack_status         drift_status         stack_description
   myStack              CREATE_COMPLETE      NOT_CHECKED  
   

6. Update the example.template and add another resource

   example.py

   from troposphere import Template
   from troposphere import iam
   
   def get_template():
       template = Template()
       template.add_resource(
           iam.User(
               "testIamUser",
               UserName="tropoform_test_user"
           )
       )
       template.add_resource(
           iam.User(
               "testIamUser2",
               UserName="tropoform_test_user2"
           )
       )
       return template
   

   and run a new tropoform plan. Notice that it will add one new resource.

   $ tropoform plan myStack -m example.py
   STACK: myStack has 1 detected changes
   # ) action   logical_id           resource_id               resource_type                  scope      Replace?
    1) Add      testIamUser2                                   AWS::IAM::User                 [] 
   

7. tropoform apply the changes and then use a tropoform list to verify

   $ tropoform apply myStack -m example.py
   STACK: myStack, Current Status: CREATE_COMPLETE
   UPDATING Stack: myStack
   Are you sure? [yes|no] yes
   STACK: myStack, Status: UPDATE_IN_PROGRESS - 16:42:38
   STACK: myStack, Status: UPDATE_IN_PROGRESS - 16:42:54
   STACK: myStack, Status: UPDATE_COMPLETE - 16:43:09
   STACK: myStack updated 2 resources in 00:00:48
   STACK OUTPUTS:
   
   $ tropoform list
   stack_name           stack_status         drift_status         stack_description
   myStack              UPDATE_COMPLETE      NOT_CHECKED   
   

8. destroy the stack when you are done with it

   $ tropoform destroy myStack
   DELETING STACK: myStack with 2 resources
   Are you sure? [yes|no] yes
   STACK: myStack, Status: UPDATE_COMPLETE - 16:44:37
   STACK: myStack deleted in 00:00:15
   
   

Additional features

1. Parameter files

   Often cloudformation templates will require parameters so that they can be easily reusable. You can create yaml based files with key: value pairs and add them as arguments to the tropoform plan and tropoform apply operations

   example_parms1.yaml

   Parm1: Parameter 1
   Parm2: "2"
   

   example_parms2.yaml

   Parm3: Parameter 3
   Parm4: "4"
   

   Using the parameter files in an apply

   $ tropoform apply myStack -m example.py -p example_parms1.yaml,example_parms2.yaml
   
   

2. Capabilities

   Cloud formation stacks may require acknowledgement that it will create resources of certain types. The most common is CAPABILITIES_NAMED_IAM which authorizes cloud formation to create IAM resources. This is included by default in tropoform. But if your stack requires additional capabilities, you can include them with the -c argument. See more information about capabilities in this documentation: https://docs.aws.amazon.com/AWSCloudFormation/latest/APIReference/API_CreateStack.html

   Using additional capabilities in an apply

   $ tropoform apply myStack -m example.py -c CAPABILITY_NAMED_IAM,CAPABILITY_AUTO_EXPAND
   
   

3. Regions

   By default, troposphere will read the environment variable AWS_DEFAULT_REGION to determine where to manage stacks. But if you want to specify a different region for an operation pass the '-r' or '--region' argument

   Specifying a region in a list command

   $ tropoform list -r us-east-2
   
   

4. Stack Names and Module Name

   If the name you want to specify for your cloudformation stack is in the current working directory and has the same name as the troposphere script, then you can omit the module_name parameter

   Example of creating a cloud formation stack called "example" when "example.py" troposphere script exists in the current working directory

   $ tropoform apply example
   
   

   Example of creating a cloud formation stack called "myStack" when "example.py" troposphere script exists in some filesystem location

   $ tropoform apply myStack -m ../scripts/example.py
   
   

5. Auto Approve

   Sometimes when running tropoform in automated scripts, you dont want to be prompted to say yes to confirm the apply or destroy operation

   Example --auto_approve

   $ tropoform apply example --auto_approve
   

6. Reason for failures

   If your cloudformation stack fails to apply for some reason, the cloudformation event(s) that caused the will be printed.

   In the example below, we tried to attach a ManagedIamPolicy that is intentionally misspelled

   $ tropoform apply myStack -m example.py
   STACK: myStack, Current Status: None
   CREATING Stack: myStack with 1 resources
   Are you sure? [yes|no] yes
   STACK: myStack, Status: CREATE_IN_PROGRESS - 17:32:22
   STACK: myStack, Status: CREATE_IN_PROGRESS - 17:32:38
   STACK: myStack, Status: ROLLBACK_COMPLETE - 17:32:54
   STACK: myStack not deployed and is in status ROLLBACK_COMPLETE
   STACK myStack create/update FAILED due to the following stack events:
   UTC time   ResourceStatus  ResourceType                        LogicalResourceId              ResourceStatusReason
   22:32:47   CREATE_FAILED   AWS::IAM::User                      testIamUser                    Policy arn:aws:iam::aws:policy/AdministratorAcces does not exist or is not attachable. 
   

   You can use the tropoform reason operation to look up the status of a failed stack

   $ tropoform reason myStack
   STACK myStack create/update FAILED due to the following stack events:
   UTC time   ResourceStatus  ResourceType                        LogicalResourceId              ResourceStatusReason
   22:32:47   CREATE_FAILED   AWS::IAM::User                      testIamUser                    Policy arn:aws:iam::aws:policy/AdministratorAcces does not exist or is not attachable.
   

7. Parameters

   If your stack was deployed with parameters, you can check those paramaters with the tropoform parameters operation

   $ tropoform parameters myStack
   STACK: myStack Parameters: 
   Parm1                = value1 
   

8. Outputs

   If your stack specifies Output parameters, when the stack is done deploying, the outputs will be printed.

   $ tropoform apply myStack -m example.py --auto_approve
   STACK: myStack, Current Status: None
   CREATING Stack: myStack with 1 resources
   STACK: myStack, Status: CREATE_IN_PROGRESS - 17:40:44
   STACK: myStack, Status: CREATE_IN_PROGRESS - 17:40:59
   STACK: myStack, Status: CREATE_COMPLETE - 17:41:15
   STACK: myStack deployed 1 resources in 00:00:48
   STACK OUTPUTS:
   userArn              = arn:aws:iam::357849880876:user/tropoform_test_user
   

   If you want to access those outputs later, you can run tropoform output

   $ tropoform output myStack
   STACK OUTPUTS:
   userArn              = arn:aws:iam::357849880876:user/tropoform_test_user
   

Contributions welcome!

Open issues and send pull requests via the github repo https://github.com/cloudshiftstrategies/tropoform