Getting Started with Google Cloud Platform (GCP) for Developers

GCP is a strong choice for teams focused on data pipelines, machine learning, and developer-friendly managed services. This guide covers practical first steps for developers: creating projects, configuring IAM, using the Cloud SDK, and deploying small apps with Cloud Run or Cloud Functions.

1. Projects, billing, and organization

• Create a separate GCP project per environment (dev/stage/prod) to simplify IAM and billing controls.
• Link projects to a billing account and set budgets and alerts.

Reference: https://cloud.google.com/resource-manager/docs/creating-managing-projects

2. IAM basics for GCP

• Use prebuilt roles where appropriate and only grant the permissions an identity needs.
• Prefer service accounts for non-interactive systems.

Practical command:

gcloud projects create my-project --name="My Project"
gcloud config set project my-project

3. Install the Cloud SDK and authenticate

• Install gcloud and gsutil for CLI workflows.
• Use gcloud auth application-default login for local development that mimics service account behavior.

4. Core services to learn first

• Compute Engine — virtual machines.
• Cloud Run — serverless containers.
• Cloud Functions — event-driven functions.
• Cloud Storage — object storage.
• BigQuery — analytics and data warehousing.

Hands-on tip: deploy a simple container to Cloud Run to practice building images and IAM.

5. Local development and emulators

• Use the Cloud SDK emulators for Pub/Sub and Datastore when you need local testing.
• Use containerized environments and named gcloud configurations to avoid accidental operations in production.

6. Deployment patterns

• Container-based apps: build image → push to Artifact Registry → deploy to Cloud Run or GKE.
• Serverless functions: package and deploy with gcloud functions deploy or use Cloud Build for CI.

CI/CD: use Cloud Build or GitHub Actions with gcloud steps to build artifacts and deploy.

7. Observability and costs

• Use Cloud Monitoring and Logging for metrics and traces. Enable billing export to BigQuery for detailed cost analysis.
• Use sustained-use discounts and committed-use contracts for predictable workloads.

8. Security best practices

• Use VPC Service Controls for data exfiltration protection when handling sensitive data.
• Use KMS for key management and avoid long-lived service account keys when possible.

9. Example: Deploying a Go HTTP service to Cloud Run

1. Build a container with a minimal multistage Dockerfile.
2. Push to Artifact Registry.
3. Deploy to Cloud Run with gcloud run deploy --image IMAGE_URL --platform managed.

Internal links

• Pillar: Practical Cloud Computing for Developers
• Related: Cloud cost optimization
• Related: Introduction to Serverless Computing
• Related: Docker Basics for Developers

External references

• GCP Quickstarts: https://cloud.google.com/docs/quickstarts
• Cloud Run: https://cloud.google.com/run
• Google Cloud SDK: https://cloud.google.com/sdk