Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context.
Scanned 9/2/2026
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---
name: application-design-center-design-deploy
description: >-
Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC).
Use when:
- Designing GCP infrastructure with Terraform.
- Validating local HCL.
- Performing best-practice plan scans.
- Importing templates to Application Design Center (ADC).
- Deploying templates.
- Troubleshooting deployment failures.
Boundaries:
- Only use for GCP-specific cloud infrastructure.
- Only use for Terraform coding within the ADC context.
license: Apache-2.0
metadata:
version: v1
publisher: google
category: CloudInfrastructure
---
# 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.
--------------------------------------------------------------------------------
## Index
1. [Pre-requisites: Setup & Confirmation](#pre-requisites-setup-confirmation)
2. [Phase 1: Local Infrastructure Design & Validation](#phase-1-local-infrastructure-design-validation)
3. [Phase 2: Shifted-Left Best Practices Assessment & Iterative Remediation](#phase-2-shifted-left-best-practices-assessment-iterative-remediation)
4. [Phase 3: Import IaC to Application Design Center](#phase-3-import-iac-to-application-design-center)
5. [Phase 4: Application Deployment & Monitoring](#phase-4-application-deployment-monitoring)
6. [Phase 5: Troubleshoot Deployment Failures](#phase-5-troubleshoot-deployment-failures)
7. [Phase 6: Verification & E2E Testing](#phase-6-verification-e2e-testing)
--------------------------------------------------------------------------------
## 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:
```bash
gcloud config set project <project_id>
```
--------------------------------------------------------------------------------
## 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](references/design_guide.md))
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:
```bash
terraform plan -out=tfplan && terraform show -json tfplan > tfplan.json
```
Verify that the `tfplan.json` file is successfully written in your scratch
directory.
--------------------------------------------------------------------------------
## 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:
```bash
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:
```bash
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:
```bash
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:
```bash
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.
--------------------------------------------------------------------------------
## 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:
```bash
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:
```json
{
"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}`
--------------------------------------------------------------------------------
## 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.
--------------------------------------------------------------------------------
## 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:
```hcl
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](references/troubleshooting_guide.md)).
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:
```bash
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.
--------------------------------------------------------------------------------
## 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
Report bugs or improvements for this skill at [Google Skills Issues](https://github.com/google/skills/issues).
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