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Professional Cloud Developer (PCD) Certification Lab Map

The Professional Cloud Developer certification validates your ability to design, build, test, deploy, and integrate scalable applications on Google Cloud — with a strong emphasis on Cloud Run, GKE, Cloud Build, Artifact Registry, Cloud Deploy, runtime secrets, service authentication, and observability. The RAD platform's four foundation modules (Services_GCP, App_CloudRun, App_GKE, App_Common) give you a live lab for exactly these skills: Services_GCP provisions the shared platform (VPC, Cloud SQL, Redis, GKE Autopilot, Artifact Registry, Binary Authorization, Workload Identity Federation), App_CloudRun and App_GKE are full-featured deployment engines for Cloud Run v2 services and Kubernetes workloads, and App_Common supplies the shared submodules they both use (secrets and rotation, Cloud Build container builds, Cloud Deploy pipelines, IAM, storage, monitoring). Application wrapper modules (Django, Wordpress, etc.) exist on the platform but everything in these guides uses the foundation modules directly.

How to use this guide

  • Deploy one of the profiles below through your deployment portal, then work through the matching section exploration guide.
  • Every section guide pairs portal variables with the GCP console views and gcloud/kubectl commands the exam expects you to know.
  • Use the coverage legend to plan study time: 🟡 and 📘 topics include a "Beyond the modules" block telling you what to practice outside the platform.
  • PCD is a developer exam: when working through the labs, always ask "what would my application code see?" — the env vars, the secret refs, the socket paths, the tokens.

Coverage legend

SymbolMeaning
Fully demonstrated — deploy it, see it, modify it in the RAD platform
🟡Partially demonstrated — the modules touch the concept; supplement with docs
📘Concept-only — not implemented by the modules; study pointers provided

Deployment profiles

Profile: Serverless baseline

Purpose: a default Cloud Run v2 service with database, probes, and runtime secrets — the workhorse for Sections 1, 3.1, and 4. Modules: Services_GCP (defaults), then App_CloudRun.

VariableValue
create_postgres (Services_GCP)true (default)
deploy_applicationtrue (default)
min_instance_count0 (default — scale to zero)
max_instance_count3 (raise from default 1 to observe scale-out)
database_type"POSTGRES" (default)
startup_probe_config / health_check_configdefaults (HTTP /healthz)

Estimated incremental cost: low — Cloud Run scales to zero; the dominant costs are the db-custom-1-3840 Cloud SQL instance and the e2-small NFS VM that Services_GCP creates by default.

Profile: Delivery pipeline

Purpose: GitHub-triggered Cloud Build (Kaniko) → Artifact Registry → Cloud Deploy progressive delivery with Binary Authorization attestation. Sections 2 and 3.1. Modules: Services_GCP + App_CloudRun.

VariableValue
enable_cicd_triggertrue
github_repository_urlyour repo URL
enable_cloud_deploytrue
cicd_enable_cloud_deploytrue
cloud_deploy_stagesdefault (dev, staging, prod with require_approval = true on prod)
enable_binary_authorization (both modules)true
binauthz_evaluation_mode"REQUIRE_ATTESTATION"
enable_vulnerability_scanning (Services_GCP)true
enable_workload_identity_federation (Services_GCP)true

Estimated incremental cost: low/moderate — three per-stage Cloud Run services (all can scale to zero) plus Cloud Build minutes per push.

Profile: Kubernetes lab

Purpose: GKE Autopilot deployment with Workload Identity, HPA, namespace governance, and the Secret Manager CSI add-on. Sections 1.1, 3.2, and 4.2. Modules: Services_GCP with GKE enabled, then App_GKE.

VariableValue
create_google_kubernetes_engine (Services_GCP)true
gke_cluster_mode (Services_GCP)"AUTOPILOT" (default)
min_instance_count / max_instance_count (App_GKE)1 / 3 (defaults)
enable_resource_quota (App_GKE)true
enable_network_segmentation (App_GKE)true
enable_pod_disruption_budget (App_GKE)true (default)

Estimated incremental cost: moderate — Autopilot bills per pod resource request plus the cluster management fee; the default 1000m/512Mi pod is the dominant driver.

Profile: Hardened edge

Purpose: IAP authentication, Cloud Armor WAF + global HTTPS load balancer, automatic secret rotation, and Memorystore caching. Sections 1.1, 1.2, and 4.1. Modules: Services_GCP with Redis, then App_CloudRun.

VariableValue
create_redis (Services_GCP)true
redis_tier (Services_GCP)"BASIC" (default)
enable_iaptrue (plus iap_authorized_users)
enable_cloud_armortrue (requires application_domains — see Section 1 guide)
application_domainsa domain you control
enable_auto_password_rotationtrue
secret_rotation_period"2592000s" (default, 30 days)

Estimated incremental cost: moderate — the global external Application Load Balancer forwarding rule and the 1 GB Memorystore instance bill continuously even when the Cloud Run service is idle. IAP alone (without Cloud Armor) adds no LB cost.

Section 1: Designing highly scalable, available, and reliable cloud-native applications (~36% of the exam)

The largest section. The modules demonstrate platform selection (Cloud Run vs GKE), scaling behavior, revision-based traffic splitting, runtime secrets, IAP, Binary Authorization, and storage selection. API management products and application messaging are study-only.

Exam topicCoverageWhere in RADGuide
1.1 Platform choice, scaling, cold startsmin_instance_count, max_instance_count, cpu_always_allocated, execution_environmentSection 1 guide
1.1 Traffic splitting, canary, rollbacktraffic_split, max_revisions_to_retain (App_CloudRun)Section 1 guide
1.1 Caching, CDN, session affinity🟡create_redis, enable_redis, enable_cdn; session affinity hardcoded onSection 1 guide
1.1 REST/gRPC APIs, API management, async messaging🟡container_protocol = "h2c" enables end-to-end HTTP/2 (gRPC-ready) on Cloud Run and appProtocol kubernetes.io/h2c on the GKE Service; API management and messaging are study-onlySection 1 guide
1.2 Secrets at runtime + rotationsecret_environment_variables, enable_auto_password_rotation, secret_rotation_periodSection 1 guide
1.2 End-user auth (IAP), supply-chain securityenable_iap, enable_binary_authorization, enable_vulnerability_scanningSection 1 guide
1.2 CMEK, audit logs, network segmentation🟡enable_cmek, enable_audit_logging, enable_network_segmentationSection 1 guide
1.3 Relational/object/cache storage selectioncreate_postgres, create_mysql, storage_buckets, create_redis, enable_alloydbSection 1 guide
1.3 Firestore, Spanner, Bigtable, BigQuery, signed URLs📘create_firestore provisions the DB only — SDK usage is study-onlySection 1 guide

Section 2: Building and testing applications (~23% of the exam)

The build pipeline is the strongest coverage in the repo: every deployment runs real Cloud Build jobs (Kaniko or Docker), pushes to Artifact Registry with cleanup policies, and can sign images for Binary Authorization. Local tooling and emulators are study-only.

Exam topicCoverageWhere in RADGuide
2.1 Local dev environment, emulators, Cloud Code/Shell/Workstations📘nearest: per-tenant isolated deployments via tenant_deployment_idSection 2 guide
2.2 Cloud Build container buildscontainer_image_source = "custom", container_build_configSection 2 guide
2.2 Artifact Registry, image lifecycle, mirroringmax_images_to_retain, image_retention_days, delete_untagged_images, Crane digest-aware mirroringSection 2 guide
2.2 CI triggers, Kaniko, attestationenable_cicd_trigger, cicd_trigger_config, Kaniko v1.23.2, pipeline image signingSection 2 guide
2.3 Unit/integration testing in CI🟡generated build pipeline is extensible; no test step ships by defaultSection 2 guide

Section 3: Deploying applications (~20% of the exam)

Both deployment targets are fully implemented. App_CloudRun covers revisions, scaling, probes, volumes, jobs, and Cloud Deploy promotion; App_GKE covers Deployments/StatefulSets, HPA/VPA, probes, quotas, PDBs, and the Gateway API.

Exam topicCoverageWhere in RADGuide
3.1 Cloud Run service configuration (scaling, CPU, gen2, timeout)min/max_instance_count, cpu_always_allocated, execution_environment, timeout_secondsSection 3 guide
3.1 Revisions, traffic management, rollbacktraffic_split, max_revisions_to_retainSection 3 guide
3.1 Cloud Deploy progressive deliveryenable_cloud_deploy, cloud_deploy_stages, cicd_enable_cloud_deploySection 3 guide
3.1 Cloud Run jobs (migrations, init)initialization_jobs, cron_jobsSection 3 guide
3.2 GKE workloads, resources, probesworkload_type, container_resources, startup_probe_config, health_check_configSection 3 guide
3.2 HPA/VPA, quotas, PDBs, exposuremin/max_instance_count, enable_vertical_pod_autoscaling, enable_resource_quota, enable_custom_domainSection 3 guide

Section 4: Integrating applications with Google Cloud services (~21% of the exam)

Database connectivity (Cloud SQL Auth Proxy on both platforms), runtime configuration injection, Workload Identity, and alerting are demonstrated live. Client-library coding, tracing, and profiling are study-only.

Exam topicCoverageWhere in RADGuide
4.1 Cloud SQL connectivity (sockets, sidecar proxy)enable_cloudsql_volume, cloudsql_volume_mount_path, GKE proxy sidecarSection 4 guide
4.1 Storage integration (GCS Fuse, NFS, Redis)gcs_volumes, enable_nfs, enable_redisSection 4 guide
4.1 Pub/Sub & Firestore application code📘only rotation/SCC topics exist — no app messagingSection 4 guide
4.2 Service accounts, ADC, Workload Identityper-app SAs, KSA annotation iam.gke.io/gcp-service-account, additional_cloudrun_sa_rolesSection 4 guide
4.2 Workload Identity Federation (keyless CI)enable_workload_identity_federation, wif_provider_typeSection 4 guide
4.2 Service-to-service auth (ID tokens)🟡roles/run.invoker bindings (IAP agent, allUsers); calling code is study-onlySection 4 guide
4.3 Logging, metrics, alerting, dashboardssupport_users, alert_policies (the platform's monitoring and dashboard layers)Section 4 guide
4.3 Uptime checksuptime_check_config creates a <service>-uptime-check + alert policy on publicly reachable endpointsSection 4 guide
4.3 Trace, Profiler, Error Reporting📘not implemented — study-onlySection 4 guide