Designing and Deploying GCP Infrastructure with Application Design Center

Overview

This skill provides a prescriptive, production-grade workflow for the entire infrastructure lifecycle on Google Cloud Platform (GCP). It replaces the automated, opaque-box GAD design_infra tool with an agent-controlled design and validation loop utilizing modular Terraform and local CLI validation, followed by a shifted-left best practices plan scan prior to synchronization with the Application Design Center (ADC) registry for deployment and lifecycle management.

Always maintain the persona of a Principal Cloud Architect. Keep the local Terraform configuration as the source of truth, and ensure the design is fully compliant with best practices before importing it into the cloud registry.

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Index

1. Pre-requisites: Setup & Confirmation
2. Phase 1: Local Infrastructure Design & Validation
3. Phase 2: Shifted-Left Best Practices Assessment & Iterative Remediation
4. Phase 3: Import IaC to Application Design Center
5. Phase 4: Application Deployment & Monitoring
6. Phase 5: Troubleshoot Deployment Failures
7. Phase 6: Verification & E2E Testing

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Pre-requisites: Setup & Confirmation

Before executing Phase 1, you must perform the following setup steps:

1. Confirm Target Project & Location:

   • Explicitly ask the user to confirm the target GCP project ID and location (region).

   • If the user does not specify a location, use us-central1 as the default.

   • Verify that your local environment has the active project set:

     gcloud config set project <project_id>
     

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Phase 1: Local Infrastructure Design & Validation

Goal: Transform user requirements and codebase characteristics into a 100% validated, secure, and compile-ready Terraform configuration locally.

1. Invoke the design Skill: Call and execute the design skill (defined in design) for the user's prompt.

   • The design skill will autonomously perform the Codebase Analysis, query the catalog registry, planning, HCL generation, and local CLI validation loop (terraform init, validate, plan) in a dedicated scratch directory.

2. Locate Validated HCL: Identify the scratch directory where the design skill saved the validated, compile-ready Terraform files (e.g., scratch/tf_validate_<session_id>/).

3. Verify Handover (MANDATORY): Ensure that the local validation loop in the design skill completed successfully with a clean plan before proceeding. Meticulously inspect the HCL to verify:

   • Secret-Safe Policy: Confirm that no plaintext credentials, passwords, or hardcoded secrets are written in terraform.tfvars or HCL resource blocks. All sensitive inputs must be wired through GCP Secret Manager.
   • State Isolation Policy: Confirm that there is no remote backend block (e.g., backend "gcs" {}) in the HCL files. State must remain local in the scratch folder during validation, allowing ADC to handle the remote state registry upon import.
   • Remediation: If any violations are found, correct them in the HCL, re-run local validation, and verify again. Do not proceed with unvalidated or insecure code.

4. Export Terraform Plan to JSON (MANDATORY): In the scratch directory, run the following commands to generate a binary plan and convert it into a clean JSON representation:

   terraform plan -out=tfplan && terraform show -json tfplan > tfplan.json
   

   Verify that the tfplan.json file is successfully written in your scratch directory.

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Phase 2: Shifted-Left Best Practices Assessment & Iterative Remediation

Goal: Validate the local plan's alignment with security, cost, and reliability benchmarks BEFORE importing it into the cloud registry, using the native ADC plan assessment API.

1. Discover Space ID (MANDATORY): Before running the assessment or creating templates, you must dynamically discover the active ADC Space ID in your target location:

   • List Spaces: Run the command:

     gcloud design-center spaces list --project=<project_id> --location=<location>
     

   • Select Space: Parse the output to identify the active space (e.g., test-deploy or googlespace). If multiple spaces exist, ask the user to confirm. If no space exists, ask the user or create one:

     gcloud design-center spaces create <space_id> --project=<project_id> --location=<location>
     

2. Execute Plan Assessment via gcloud: Run the plan-based assessment using the discovered Space ID and your exported tfplan.json file. Execute the command directly in your terminal:

   gcloud design-center spaces generate-terraform-assessment-report <space_id> \
       --location=<location> \
       --project=<project_id> \
       --terraform-plan="<scratch_directory_path>/tfplan.json" \
       --format=json
   

3. Analyze Findings: Present all findings to the user in a clean tabular format, detailing specific violations, resource scopes, and associated severity levels.

4. Local Remediation Loop:

   • Do not attempt to import or commit insecure code.

   • Edit your local HCL files in the scratch directory to fix the reported violations (e.g., adding encryption keys, enabling OS Login, or restricting IAM scopes).

   • Re-run Phase 1 local validation and plan export:

     terraform validate && terraform plan -out=tfplan && terraform show -json tfplan > tfplan.json
     

   • Re-run the plan assessment command shown in step 2.

5. Exit Criteria:

   • All high/critical findings resolved, or acceptable trade-offs documented.
   • Maximum of three (3) iterative attempts reached. Once clean or acceptable, proceed to Phase 3.

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Phase 3: Import IaC to Application Design Center

Goal: Synchronize the fully validated and best-practice-compliant local HCL configuration with the ADC cloud registry to establish the deployable template resource.

1. Verify or Create the Application Template (MANDATORY): Before importing the HCL, you must ensure the parent Application Template resource exists in the discovered ADC space.

   • Check Existence: Run gcloud design-center spaces application-templates describe <template_id> --space=<space_id> --project=<project_id> --location=<location> to check if the template exists.

   • Create if Missing: If the describe command returns a NOT_FOUND error, create the template resource first by running:

     gcloud design-center spaces application-templates create <template_id> --space=<space_id> --project=<project_id> --location=<location> --display-name="<Name>" --description="<Description>"
     

2. Strict HCL Parser Constraints (CRITICAL): Before calling the import operation, ensure your local HCL complies with the ADC registry's strict ingestion rules:

   • Pure Module Policy (No Resource Blocks): The ADC parser strictly prohibits any resource blocks inside the imported HCL. Only module, variable, output, and provider blocks are allowed. If a resource is required (e.g. Private Service Access peering) but no standalone module is registered for it in the catalog, you MUST check if it is supported as a built-in configuration option inside an existing registered module (e.g. setting private_service_access_config inside module "vpc").
   • Strict String Typing: The ADC parser does not perform implicit type coercion from boolean to string. For example, subnet private access must be declared as a literal string: subnet_private_access = "true", NOT as a boolean true.
   • No Terraform Block: The parser strictly prohibits the terraform {} version constraint block. Omit it entirely from providers.tf or main.tf.

3. Import to ADC Template: Once the template resource is confirmed to exist and the HCL is validated against the above constraints, invoke the hosted application_design_center:manage_application_template MCP tool with the APPLICATION_TEMPLATE_OPERATION_IMPORT_IAC operation:

   • Arguments:

     • project: The target project ID.

     • location: The GCP deployment region (e.g., us-central1).

     • spaceId: The discovered ADC space ID.

     • applicationTemplateId: A unique name for your application template.

     • operation: APPLICATION_TEMPLATE_OPERATION_IMPORT_IAC

     • iacModule: A structured object containing the files list:

       {
         "files": [
           { "name": "main.tf", "content": "<content of main.tf>" },
           { "name": "variables.tf", "content": "<content of variables.tf>" },
           { "name": "terraform.tfvars", "content": "<content of terraform.tfvars>" }
         ]
       }
       

   • Resilience & Retries (MANDATORY):

     • If the IMPORT_IAC call fails due to a transient error (e.g., 502 Bad Gateway, 504 Gateway Timeout, or 429 Rate Limit), do not immediately retry.
     • Use exponential backoff with jitter (e.g., waiting 2s, 4s, 8s plus a random fraction of a second).
     • Verify Revision before Retry: If a timeout occurred, first call gcloud alpha design-center spaces application-templates describe to check if the import actually succeeded in the background. Only retry if the template was not updated.

4. Capture Template URI: Upon success, this establishes the template resource in your space. Construct the applicationTemplateUri using the pattern: projects/{project}/locations/{location}/spaces/{spaceId}/applicationTemplates/{applicationTemplateId}

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Phase 4: Application Deployment & Monitoring

Goal: Deploy the validated, best-practice-compliant application template to the GCP environment.

1. Deploy Application: Invoke the hosted application_design_center:manage_application MCP tool with the APPLICATION_OPERATION_DEPLOY operation:
   • Arguments:
     • project: Target project ID.
     • location: Target deployment location.
     • spaceId: Target space ID.
     • applicationId: A unique ID for the deployed application instance.
     • applicationTemplateUri: The URI established in Phase 3.
     • serviceAccount: The deployment service account.
   • Resilience & Retries (MANDATORY):
     • If the DEPLOY operation fails with transient network or gateway errors (e.g., 502, 504), apply exponential backoff with jitter before retrying.
     • If the deployment LRO times out or fails with a state conflict, verify the application status using gcloud design-center spaces applications describe to confirm its status before retrying the deploy call, avoiding concurrent conflicting deployments.
2. Active LRO Monitoring:
   • The tool returns a Long-Running Operation (LRO). Inform the user that the deployment has started.
   • Do not sleep during deployment status polling. Poll the LRO actively every 30–60 seconds until done: true using the command gcloud design-center operations describe <operation_name>.
3. Handle Results:
   • Success: If done is true and there is no error field, proceed to Phase 6.
   • Failure: If an error field is present, analyze the error type and proceed to Phase 5.

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Phase 5: Troubleshoot Deployment Failures

Goal: Diagnose and remediate deployment failures iteratively using the specialized troubleshooting skill and established cloud resolution patterns.

1. Iterative Cloud Resolution Patterns (CRITICAL): If the deployment fails with a REVISION_FAILED or TERRAFORM error, check for these common resource conflicts:

   • Service Account 409 Conflict (alreadyExists): If the deployment fails because a service account generated by the module (e.g. frontend-service-us-central-sa) already exists in the project, remediate the local HCL by disabling service account creation and referencing the existing one:

     create_service_account = false
     service_account        = "<existing_service_account_email>"
     

   • Container Image 404 NotFound: If the deployment fails because a container image is not found, confirm that the image exists in your registry. For testing or hello-world deployments, leverage the official public Google hello-world image: us-docker.pkg.dev/cloudrun/container/hello

2. Delegate to the Troubleshooting Skill: If a deployment failure occurs and does not match the above patterns, invoke and execute the specialized infra-deployment-debugging guide (located in infra-deployment-debugging).

3. Select the Troubleshooting Context:

   • For Local Validation Errors (Phase 1/2): Follow Case B: Raw Terraform Deployment instructions in the troubleshooting skill to isolate syntax, compilation, and plan-time validation errors.
   • For Cloud Deployment Failures (Phase 4): Follow Case A: ADC Application Deployment instructions in the troubleshooting skill to analyze LRO errors, retrieve service logs, and diagnose cloud environment issues.

4. Apply Local-First Remediation:

   • Follow the troubleshooting skill's remediation guides to formulate a fix.

   • MANDATORY: Apply the fix directly to your local HCL files in the scratch directory, re-run local validation, re-import the HCL, and trigger a new deployment.

   • Re-run Phase 1 local validation and plan export:

     terraform validate && terraform plan -out=tfplan && terraform show -json tfplan > tfplan.json
     

   • Re-run the plan assessment (Phase 2) to ensure no new violations are introduced.

   • Re-import the corrected HCL to ADC using APPLICATION_TEMPLATE_OPERATION_IMPORT_IAC.

   • Trigger a new deployment using APPLICATION_OPERATION_DEPLOY.

5. Iteration Threshold: Repeat the troubleshooting, validation, import, and redeployment cycle up to five (5) times. If it still fails, report the full history and diagnostics to the user.

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Phase 6: Verification & E2E Testing

Goal: Confirm that the deployed services are healthy and fully functional.

1. Retrieve Deployed Resources: Invoke the hosted application_design_center:manage_application MCP tool with the APPLICATION_OPERATION_GET operation to retrieve the resource details, public endpoints, and output parameters.
2. Health Check: Verify that all services are using the correct container image URLs and that their runtime status is healthy.
3. E2E Validation: Conduct a simple demo test (e.g., checking public HTTP endpoints or triggering a dry-run transaction) to ensure E2E functionality. Present the results and public URLs to the user to conclude the task.

Reporting Issues

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