Terraform
Build AWS infrastructure with CDK for Terraform
The Cloud Development Kit for Terraform (CDKTF) allows you to define your infrastructure in a familiar programming language such as TypeScript, Python, Go, C#, or Java. CDKTF generates Terraform configuration in JSON, then automatically applies that configuration via Terraform to provision your infrastructure.
In this tutorial, you will provision an EC2 instance on AWS using your preferred programming language.
If you do not have CDKTF installed on your system, follow the steps in the install CDKTF tutorial to install it before you continue with this tutorial.
Prerequisites
To follow this tutorial, you need the following installed locally:
- Terraform v1.2+
- An HCP Terraform account, with CLI authentication configured
- CDK for Terraform v0.15+
- an AWS account
- AWS Credentials configured for use with Terraform
Terraform and CDKTF will use credentials set in your environment or through other means as described in the Terraform documentation.
You will also need to install a recent version of the programming language you will use for this tutorial. We have verified this tutorial works with the following language versions.
Python v3.7 and pipenv v2021.5.29
Initialize a new CDK for Terraform application
Start by creating a directory named learn-cdktf
for your project.
$ mkdir learn-cdktf
Then navigate into it.
$ cd learn-cdktf
Inside the directory, run cdktf init
, specifying the template for your
preferred language and Terraform's AWS provider. Select your HCP Terraform
Organization when prompted, and use the default name learn-cdktf
for your
HCP Terraform Workspace. CDKTF will also prompt you for other information
about your project, such as the name and description. Accept the defaults for
these options.
Tip
If you would prefer to keep your state locally, use the --local
flag with cdktf init
.
$ cdktf init --template="python" --providers="aws@~>4.0"
? Project Name learn-cdktf
? Project Description A simple getting started project for cdktf.
Detected Terraform Cloud token.
We will now set up Terraform Cloud for your project.
? Terraform Cloud Organization Name <YOUR_ORG>
We are going to create a new Terraform Cloud Workspace for your project.
? Terraform Cloud Workspace Name learn-cdktf
? Do you want to send crash reports to the CDKTF team? See
https://www.terraform.io/cdktf/create-and-deploy/configuration-file#enable-crash
-reporting-for-the-cli for more information Yes
Generating Terraform Cloud configuration for '<YOUR_ORG>' organization and 'learn-cdktf' workspace.....
Creating a virtualenv for this project...
##...
========================================================================================================
Your cdktf Python project is ready!
cat help Prints this message
Compile:
pipenv run ./main.py Compile and run the python code.
Synthesize:
cdktf synth [stack] Synthesize Terraform resources to cdktf.out/
Diff:
cdktf diff [stack] Perform a diff (terraform plan) for the given stack
Deploy:
cdktf deploy [stack] Deploy the given stack
Destroy:
cdktf destroy [stack] Destroy the given stack
Learn more about using modules and providers https://cdk.tf/modules-and-providers
Use Providers:
You can add prebuilt providers (if available) or locally generated ones using the add command:
cdktf provider add "aws@~>3.0" null kreuzwerker/docker
You can find all prebuilt providers on PyPI: https://pypi.org/user/cdktf-team/
You can also install these providers directly through pipenv:
pipenv install cdktf-cdktf-provider-aws
pipenv install cdktf-cdktf-provider-google
pipenv install cdktf-cdktf-provider-azurerm
pipenv install cdktf-cdktf-provider-docker
pipenv install cdktf-cdktf-provider-github
pipenv install cdktf-cdktf-provider-null
You can also build any module or provider locally. Learn more: https://cdk.tf/modules-and-providers
========================================================================================================
Checking whether pre-built provider exists for the following constraints:
provider: aws
version : ~>4.0
language: python
cdktf : 0.15.0
Found pre-built provider.
Package installed.
CDKTF provides packages with prebuilt classes for each supported programming
language for many common Terraform providers that you can use in your CDKTF
projects. The cdktf init
command you just ran will find a pre-built AWS
provider that you will use for this project. For other Terraform providers and
modules, CDKTF automatically generates the appropriate classes for your chosen
language.
Define your CDK for Terraform Application
Open the main.py
file to view your application code. The template creates a scaffold with no functionality.
Replace the contents of main.py
with the following code for a new Python
application, which uses the CDK to provision an AWS EC2 instance in us-west-1
,
and stores its state in HCP Terraform.
main.py
#!/usr/bin/env python
from constructs import Construct
from cdktf import App, NamedRemoteWorkspace, TerraformStack, TerraformOutput, RemoteBackend
from cdktf_cdktf_provider_aws.provider import AwsProvider
from cdktf_cdktf_provider_aws.instance import Instance
class MyStack(TerraformStack):
def __init__(self, scope: Construct, ns: str):
super().__init__(scope, ns)
AwsProvider(self, "AWS", region="us-west-1")
instance = Instance(self, "compute",
ami="ami-01456a894f71116f2",
instance_type="t2.micro",
)
TerraformOutput(self, "public_ip",
value=instance.public_ip,
)
app = App()
stack = MyStack(app, "aws_instance")
RemoteBackend(stack,
hostname='app.terraform.io',
organization='<YOUR_ORG>',
workspaces=NamedRemoteWorkspace('learn-cdktf')
)
app.synth()
Replace <YOUR_ORG>
with the HCP Terraform organization name you chose when
you ran terraform init
earier. If you chose a different workspace name,
replace learn-cdktf
with that name.
Tip
If you would prefer to store your project's state locally, remove or
comment out RemoteBackend(stack, [...] )
and remove RemoteBackend
from the from cdktf import [...]
line near the top of the file..
Examine the code
Most of the code is similar to concepts found in a traditional Terraform configuration written in HCL, but there are a few notable differences. Review the code for the programming language you have selected.
You must explicitly import any classes your Python code uses. For example, you
will use TerraformOutput
to create a Terraform output value for your EC2
instance's public IP address.
#!/usr/bin/env python
from constructs import Construct
from cdktf import App, NamedRemoteWorkspace, TerraformStack, TerraformOutput, RemoteBackend
The example code also imports the AWS provider and other resources from the
package you installed earlier. In this case you need the AwsProvider
and
Instance
classes for your compute resource.
from cdktf_cdktf_provider_aws.provider import AwsProvider
from cdktf_cdktf_provider_aws.instance import Instance
The MyStack
class defines a new stack, which contains code to define your
provider and all of your resources.
class MyStack(TerraformStack):
def __init__(self, scope: Construct, ns: str):
super().__init__(scope, ns)
The code configures the AWS provider to use the us-west-1
region.
AwsProvider(self, "AWS", region="us-west-1")
The code configures the AwsProvider
by passing in named arguments that map to
Terraform arguments as listed in the AWS provider
documentation.
The Instance
class creates a t2.micro
EC2 instance with an AWS ami.
instance = Instance(self, "compute",
ami="ami-01456a894f71116f2",
instance_type="t2.micro",
)
The Instance
class also accepts named arguments, using camel case for
properties that correspond to the AWS provider
documentation.
The code stores the instance as a variable so that the TerraformOutput
below
can reference the instance's public_ip
attribute.
TerraformOutput(self, "public_ip",
value=instance.public_ip,
)
When you write CDKTF code with an IDE, use it view the properties and functions
of the classes, variables, and packages in your code. This example uses the
public_ip
attribute from the instance
variable.
Finally, your application uses the stack you have defined, configures a remote
backend to store your project's state in HCP Terraform, and calls app.synth()
to generate Terraform configuration.
app = App()
stack = MyStack(app, "aws_instance")
RemoteBackend(stack,
hostname='app.terraform.io',
organization='<YOUR_ORG>',
workspaces=NamedRemoteWorkspace('learn-cdktf')
)
app.synth()
Provision infrastructure
Now that you have initialized the project with the AWS provider and written code
to provision an instance, it's time to deploy it by running cdktf deploy
.
When CDKTF asks you to confirm the deploy, respond with a yes
.
$ cdktf deploy
Deploying Stack: aws_instance
Resources
✔ AWS_INSTANCE compute aws_instance.compute
Summary: 1 created, 0 updated, 0 destroyed.
Output: public_ip = 50.18.17.102
The cdktf deploy
command runs terraform apply
in the background.
After the instance is created, visit the AWS EC2 Dashboard.
Notice that the CDK deploy command printed out the public_ip
output value,
which matches the instance's public IPv4 address.
Change infrastructure by adding the Name tag
Add a tag to the EC2 instance.
Update the Instance
in main.py
to add a Name
tag.
main.py
instance = Instance(self, "compute",
ami="ami-01456a894f71116f2",
instance_type="t2.micro",
tags={"Name": "CDKTF-Demo"},
)
Deploy your updated application. Confirm your deploy by choosing Approve
.
$ cdktf deploy
aws_instance Initializing the backend...
aws_instance
Successfully configured the backend "remote"! Terraform will automatically
use this backend unless the backend configuration changes.
aws_instance Initializing provider plugins...
aws_instance - Finding hashicorp/aws versions matching "4.23.0"...
aws_instance - Using hashicorp/aws v4.23.0 from the shared cache directory
##...
Plan: 1 to add, 0 to change, 0 to destroy.
Changes to Outputs:
+ public_ip = (known after apply)
aws_instance
─────────────────────────────────────────────────────────────────────────────
Saved the plan to: plan
To perform exactly these actions, run the following command to apply:
terraform apply "plan"
Please review the diff output above for aws_instance
❯ Approve Applies the changes outlined in the plan.
Dismiss
Stop
##...
Apply complete! Resources: 1 added, 0 changed, 0 destroyed.
Outputs:
aws_instance public_ip = "54.219.167.18"
aws_instance
public_ip = 54.219.167.18
Clean up your infrastructure
Destroy the application by running cdktf destroy
. Confirm your destroy by
choosing Approve
.
$ cdktf destroy
aws_instance Initializing the backend...
aws_instance Initializing provider plugins...
- Reusing previous version of hashicorp/aws from the dependency lock file
aws_instance - Using previously-installed hashicorp/aws v4.23.0
##...
Plan: 0 to add, 0 to change, 1 to destroy.
Changes to Outputs:
- public_ip = "54.219.167.18" -> null
aws_instance
─────────────────────────────────────────────────────────────────────────────
Saved the plan to: plan
To perform exactly these actions, run the following command to apply:
terraform apply "plan"
Please review the diff output above for aws_instance
❯ Approve Applies the changes outlined in the plan.
Dismiss
Stop
##...
Plan: 0 to add, 0 to change, 1 to destroy.
Changes to Outputs:
- public_ip = "54.219.167.18" -> null
aws_instance aws_instance.compute (compute): Destroying... [id=i-0fc8d2e3931b28db3]
aws_instance aws_instance.compute (compute): Still destroying... [id=i-0fc8d2e3931b28db3, 10s elapsed]
aws_instance aws_instance.compute (compute): Still destroying... [id=i-0fc8d2e3931b28db3, 20s elapsed]
aws_instance aws_instance.compute (compute): Still destroying... [id=i-0fc8d2e3931b28db3, 30s elapsed]
aws_instance aws_instance.compute (compute): Destruction complete after 30s
aws_instance
Destroy complete! Resources: 1 destroyed.
Destroying your CDKTF application will not remove the HCP Terraform workspace that stores your project's state. Log into the HCP Terraform application and delete the workspace.
Next steps
Now you have deployed, modified, and deleted an AWS EC2 instance using CDKTF!
CDKTF is capable of much more. For example, you can:
- Use the
cdktf synth
command to generate JSON which can be used by the Terraform executable to provision infrastructure usingterraform apply
and other Terraform commands. - Use Terraform providers and modules.
- Use programming language features (like class inheritance) or data from other sources to augment your Terraform configuration.
- Use CDKTF with HCP Terraform for persistent storage of your state file and for team collaboration.
For other examples, refer to the CDKTF documentation repository. In particular, check out the:
- CDKTF Architecture documentation for an overview of CDKTF's architecture.
- Community documentation to learn how to engage with the CDKTF developer community.
- Review example code in several programming languages.