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Deploy with Terraform

Use Terraform in a Codefresh pipeline with Docker

Terraform is a platform for Infrastructure as Code. It allows you to describe you cloud infrastructure in a declarative manner.

You can use Terraform to deploy to Kubernetes or any other supported cloud platform. Because Terraform itself is already offered in a Docker container, it is very easy to run Terraform in a Codefresh pipeline.

Running Terraform inside Codefresh

Running Terraform inside Codefresh

The example Terraform project

You can see the example project at https://github.com/codefresh-contrib/terraform-sample-app. The repository contains a simple Terraform definition that creates a VM on Google cloud.

You can play with it locally after installing the terraform executable.

Prerequisites

You need to create a Codefresh account and a Google account first. Then you need to create a Service account Key which will allow terraform to communicate with Google cloud.

Add your service account json as a pipeline variable called ACCOUNT_JSON_CONTENT. The content of this variable will be used in order to authenticate to Google cloud.

Create a CI/CD pipeline for Terraform

Here is the whole pipeline:

codefresh.yml

version: '1.0'
stages:
  - checkout
  - prepare   
  - deploy
steps:
  main_clone:
    title: Cloning main repository...
    stage: checkout
    type: git-clone
    repo: 'codefresh-contrib/terraform-sample-app'
    revision: master
    git: github      
  SetupAuth:
    image: alpine:3.9
    title: Setting up Google cloud auth
    stage: prepare
    commands:
      - echo $ACCOUNT_JSON_CONTENT > /codefresh/volume/account.json
      - cf_export GOOGLE_CLOUD_KEYFILE_JSON=/codefresh/volume/account.json
  DeployWithTerraform:
    image: hashicorp/terraform:0.12.0
    title: Deploying Terraform plan
    stage: deploy
    commands:
      - terraform init
      - terraform apply -auto-approve

This pipeline does the following:

  1. Clones the source code with a Git clone step
  2. Runs cf_export to create a pipeline variable with the path of the google service account
  3. Runs terraform init/apply to create the VM on Google cloud.

For simplicity, we auto-approve the terraform plan in the example pipeline. In a production pipeline you would instead use an approval step to inspect the plan, before actually applying it.

The pipeline needs a single environment variable that holds the content of the service account.

Passing the Google account in the pipeline parameters

Passing the Google account in the pipeline parameters

Run the pipeline and see your deployment succeed.

Note that in a production pipeline you should also handle the Terraform state in a proper manner. The example provided is using a file for state storage which is not appropriate when using Terraform in a team environment. Instead you should use one of the storage backends that support High Availability and Locking.

Handling Pull requests

You can easily use the same pipeline or a different one for pull requests. In this case replace the terraform apply command with terraform plan. Even better, you can add an approval step to allow humans to inspect the pipeline first.