Hands-on Lab — PCDE Google Cloud Professional Cloud Database Engineer

Overview

Prerequisites

Steps

1. 1.Provider, project services, naming

   Enable Cloud Build, Cloud Deploy, Cloud Run, Artifact Registry, and Cloud Monitoring APIs.

   Copy

   terraform {
     required_version = ">= 1.5"
   
     required_providers {
       google = { source = "hashicorp/google", version = "~> 6.0" }
     }
   }
   
   provider "google" {
     project = "your-project-id" # REPLACE
     region  = "us-central1"
   }
   
   locals {
     labels = {
       project    = "certlabpro-pcde"
       managed_by = "terraform"
     }
   }
   
   resource "google_project_service" "cloudbuild" {
     service            = "cloudbuild.googleapis.com"
     disable_on_destroy = false
   }
   
   resource "google_project_service" "clouddeploy" {
     service            = "clouddeploy.googleapis.com"
     disable_on_destroy = false
   }
   
   resource "google_project_service" "run" {
     service            = "run.googleapis.com"
     disable_on_destroy = false
   }
   
   resource "google_project_service" "artifactregistry" {
     service            = "artifactregistry.googleapis.com"
     disable_on_destroy = false
   }
   
   resource "google_project_service" "monitoring" {
     service            = "monitoring.googleapis.com"
     disable_on_destroy = false
   }

2. 2.Create the Artifact Registry image destination

   Provisions:

   • Artifact Registry

   PCDE-canonical CI/CD shape: Cloud Build outputs images into Artifact Registry; Cloud Deploy promotes the same image SHA through environments. The repo is the single source-of-truth across all environments — immutable images, mutable tags.

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   resource "google_artifact_registry_repository" "images" {
     repository_id = "certlabpro-pcde-images"
     location      = "us-central1"
     format        = "DOCKER"
   
     labels = local.labels
   
     depends_on = [google_project_service.artifactregistry]
   }

3. 3.Define a Cloud Build trigger on a GitHub repo

   Provisions:

   • Cloud Build

   Cloud Build triggers are the PCDE commit-to-build primitive. We define a trigger on a GitHub repo's main branch — every push runs the cloudbuild.yaml at repo root, which would docker build + docker push into the Artifact Registry from Step 2.

   Replace github-owner and github-repo with your actual repo. The trigger will provision but won't fire until the GitHub Cloud Build app is installed on the repo (manual one-time console step).

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   resource "google_cloudbuild_trigger" "main_push" {
     name        = "certlabpro-pcde-main-push"
     description = "Build on push to main"
     filename    = "cloudbuild.yaml"
   
     github {
       owner = "github-owner" # REPLACE
       name  = "github-repo"  # REPLACE
   
       push {
         branch = "^main$"
       }
     }
   
     depends_on = [google_project_service.cloudbuild]
   }

4. 4.Wire a Cloud Deploy pipeline with staging → prod Cloud Run targets

   Provisions:

   • Cloud Deploy
   • Cloud Run

   Cloud Deploy is GCP's managed CD service — promotes a release through ordered stages (typically dev → staging → prod), each backed by a target (Cloud Run service, GKE cluster, or Anthos cluster). PCDE exam tests this release-once, promote-many shape extensively.

   We define two Cloud Run target services (one for staging, one for prod, both scale-to-zero) + one delivery pipeline chaining them. A real release would be triggered via gcloud deploy releases create after a successful Cloud Build run; the lab provisions the substrate without firing a release.

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   resource "google_cloud_run_v2_service" "staging" {
     name     = "certlabpro-pcde-staging"
     location = "us-central1"
   
     template {
       scaling { max_instance_count = 5 }
   
       containers {
         image = "us-docker.pkg.dev/cloudrun/container/hello"
       }
     }
   
     labels = local.labels
   
     depends_on = [google_project_service.run]
   }
   
   resource "google_cloud_run_v2_service" "prod" {
     name     = "certlabpro-pcde-prod"
     location = "us-central1"
   
     template {
       scaling { max_instance_count = 10 }
   
       containers {
         image = "us-docker.pkg.dev/cloudrun/container/hello"
       }
     }
   
     labels = local.labels
   
     depends_on = [google_project_service.run]
   }
   
   resource "google_clouddeploy_target" "staging" {
     name     = "staging"
     location = "us-central1"
   
     run {
       location = "projects/${data.google_project.current.project_id}/locations/us-central1"
     }
   
     depends_on = [google_project_service.clouddeploy]
   }
   
   resource "google_clouddeploy_target" "prod" {
     name     = "prod"
     location = "us-central1"
   
     run {
       location = "projects/${data.google_project.current.project_id}/locations/us-central1"
     }
   
     require_approval = true # promotion to prod needs manual approval
   
     depends_on = [google_project_service.clouddeploy]
   }
   
   data "google_project" "current" {}
   
   resource "google_clouddeploy_delivery_pipeline" "main" {
     name     = "certlabpro-pcde-pipeline"
     location = "us-central1"
   
     serial_pipeline {
       stages {
         target_id = google_clouddeploy_target.staging.name
       }
   
       stages {
         target_id = google_clouddeploy_target.prod.name
       }
     }
   
     depends_on = [google_project_service.clouddeploy]
   }

5. 5.Define an SLO + alert policy on the prod service

   Provisions:

   • Cloud Monitoring

   PCDE's SLO / SLI / error budget vocabulary is the load-bearing observability shape — every PCDE exam question tagged Site Reliability tests this. We define a service-level objective: "99% of HTTP requests to the prod service should return 2xx over a rolling 28-day window." Then a Cloud Monitoring alert fires when the burn rate indicates the budget is being consumed too fast.

   With the five blocks in place (Artifact Registry, Cloud Build trigger, two Cloud Run targets, Cloud Deploy pipeline, prod SLO + alert), the PCDE commit → build → deploy → observe loop is end-to-end provisioned.

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   resource "google_monitoring_service" "prod" {
     service_id   = "certlabpro-pcde-prod-svc"
     display_name = "PCDE prod Cloud Run service"
   
     basic_service {
       service_type = "CLOUD_RUN"
   
       service_labels = {
         service_name = google_cloud_run_v2_service.prod.name
         location     = google_cloud_run_v2_service.prod.location
       }
     }
   
     depends_on = [google_project_service.monitoring]
   }
   
   resource "google_monitoring_slo" "prod_availability" {
     service             = google_monitoring_service.prod.service_id
     slo_id              = "certlabpro-pcde-prod-availability"
     display_name        = "99% requests return 2xx (28-day rolling)"
     goal                = 0.99
     rolling_period_days = 28
   
     basic_sli {
       availability {
         enabled = true
       }
     }
   }
   
   resource "google_monitoring_alert_policy" "prod_budget_burn" {
     display_name = "PCDE prod — fast budget burn"
     combiner     = "OR"
   
     conditions {
       display_name = "1-hour burn rate > 14.4 (fast burn)"
   
       condition_threshold {
         filter          = "select_slo_burn_rate(\"${google_monitoring_slo.prod_availability.name}\", \"3600s\")"
         duration        = "0s"
         comparison      = "COMPARISON_GT"
         threshold_value = 14.4 # consumes 2% of monthly budget in 1 hour
       }
     }
   }

Cleanup