Skip to content

Terraform and Google AI integration for debugging plan/apply issues

License

Notifications You must be signed in to change notification settings

gautambaghel/terraform-google-ai-debugger

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

29 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

terraform-google-ai-debugger

Overview

The AI debugger for Terraform is a solution designed to address runtime issues, enhancing the identification and resolution of challenges in deploying developer infrastructure. It leverages Google Cloud services and Terraform Cloud to optimize the remediation process.

diagram

Architecture

The diagram below shows the Terraform AI debugger components leveraging low cost serverless Google Cloud resources.

diagram

Resources created in Google Cloud are:

  • API Gateway
  • Cloud Functions - callback, process, request
  • Cloud Storage Bucket
  • Service Accounts
  • Secrets Manager
  • Workflow
  • Vertex AI - Gemini Pro Text

Pre-requisites

Pre-requisites for the AI debugger deployment only:

  • Google Cloud SDK
  • Google Cloud project with owner permissions
  • Google Cloud credentials setup
    • gcloud auth application-default login
    • gcloud auth login
  • Makefile
  • Terraform v1.4+
  • Terraform Cloud account and workspace created
  • Terraform sample deployment to connect to the above workspace

Additional pre-requisites for cloud function development:

  • Python 3.10+
  • Python IDE, e.g. PyCharm

Deploy

Google Cloud

Create a file in the terraform folder named terraform.tfvars.

project_id = "__GOOGLE_PROJECT__"
tfc_api_key = "__TERRAFORM_CLOUD_API_KEY__"
terraform_org_name = "__TERRAFORM_CLOUD_ORG_NAME__"
terraform_workspace_names = ["__TF_WS_1_NAME__", "__TF_WS_2_NAME__"]
  • project_id - Google project id for deploying services
  • tfc_api_key - The Terraform Cloud API key, this could be the team (recommended) or user token
  • terraform_org_name - The Terraform Cloud organization name
  • terraform_workspace_names - The list of Terraform Cloud workspace names to attach debugger

To format the Terraform config files use

terraform -chdir=terraform fmt

Execute the commands below to deploy the Google Cloud resources

terraform -chdir=terraform init
terraform -chdir=terraform plan
terraform -chdir=terraform apply

Destroy

A secrets manager secret is not destroyed by Terraform so delete it manually

gcloud secrets delete terraform-cloud-api-key-{random_str_here}

All the resources deployed to the Google Cloud project can be destroyed with the single command below

terraform -chdir=terraform destroy

Cloud Function Development

The cloud functions for the AI debugger are in the folders below:

Cloud Function pytests have been created in the folder cloud_functions/tests to aid local development and unit testing.

Terraform pytests have been created in the folder tests to deploy, test and destroy resources, run them as follows:

cd tests/
pipenv install
pipenv run tests

About

Terraform and Google AI integration for debugging plan/apply issues

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published