Getting Started with Google Cloud Platform: A Beginner’s Guide to Cloud Excellence

📘 Chapter 2: Core GCP Services and Use Cases

Google Cloud Platform (GCP) offers a vast range of services across compute, storage, networking, databases, analytics, AI/ML, DevOps, and security. However, for beginners and most real-world applications, a smaller set of core services serves as the foundation for building scalable cloud-based solutions.

In this chapter, we’ll dive into the most commonly used GCP services and explore their use cases with practical code examples and architecture scenarios.

🧠 Categories of Core GCP Services

☁️ 1. Compute Services

🔹 A. Compute Engine (VMs)

Create and manage virtual machines in Google’s data centers.

Key Features:

• Customizable VM types
• Preemptible (spot) instances
• Persistent disks and snapshots
• Supports Windows, Linux, container images

Use Case: Host a backend service or database server.

Example: Launch a VM via CLI

bash

gcloud compute instances create my-vm \

  --zone=us-central1-a \

  --machine-type=e2-micro \

  --image-family=debian-11 \

  --image-project=debian-cloud

🔹 B. App Engine (PaaS)

Fully managed serverless platform to build and deploy apps.

Key Features:

• Automatic scaling and load balancing
• Supports multiple languages (Python, Node.js, Java, Go, PHP)
• Zero server management

Use Case: Deploy a website or web API without managing infrastructure.

Example: Deploy App

bash

gcloud app deploy app.yaml

🔹 C. Cloud Run (Serverless Containers)

Run stateless containers that respond to HTTP requests.

Key Features:

• Fast deployment from Docker images
• Scales down to zero
• Bill only when requests are active

Use Case: Host REST APIs, cron jobs, or microservices.

Example: Deploy Container

bash

gcloud run deploy my-app \

  --image gcr.io/my-project/my-image \

  --platform managed \

  --region us-central1

🔹 D. Google Kubernetes Engine (GKE)

Managed Kubernetes service for containerized applications.

Use Case: Deploy and orchestrate microservices at scale with Kubernetes.

🗄️ 2. Storage Services

🔹 A. Cloud Storage (Object Storage)

Google’s unified object storage service for unstructured data.

Key Features:

• Multi-region, regional, and nearline storage
• Lifecycle management and object versioning
• Public file hosting support

Use Case: Store images, backups, website assets.

Example: Upload File

bash

gsutil cp image.png gs://my-bucket/

🔹 B. Filestore (NFS File Storage)

High-performance file storage for GKE and Compute Engine VMs.

🔹 C. Persistent Disks

Block storage for Compute Engine.

Types: Standard, SSD, Balanced

Use Case: Attach to VMs for performance-optimized read/write operations.

🧮 3. Database Services

🔹 A. Cloud SQL

Managed relational database service (MySQL, PostgreSQL, SQL Server).

Use Case: Web apps, WordPress sites, transactional applications.

Example: Create MySQL Instance

bash

gcloud sql instances create my-sql-db \

  --database-version=MYSQL_8_0 \

  --tier=db-f1-micro \

  --region=us-central

🔹 B. Firestore

NoSQL document database for serverless apps and mobile backends.

Use Case: Real-time apps like chat, live dashboards.

🔹 C. Bigtable

High-throughput NoSQL database for time-series or IoT data.

Use Case: Monitoring, finance, or analytics-heavy applications.

🔹 D. Cloud Spanner

Globally distributed SQL database with horizontal scalability.

Use Case: Enterprise-scale applications requiring both strong consistency and scalability.

🌐 4. Networking & Content Delivery

🔹 A. Virtual Private Cloud (VPC)

Define and isolate your network with subnets, firewalls, and routes.

Use Case: Secure deployment of internal or external-facing apps.

🔹 B. Cloud Load Balancing

Distribute traffic across multiple instances or regions.

Use Case: Improve performance, uptime, and reliability.

🔹 C. Cloud CDN

Global caching for static or dynamic content.

Use Case: Speed up website content delivery.

📡 5. Messaging & Integration

🔹 A. Pub/Sub

Real-time messaging middleware for decoupling services.

Use Case: Event-driven microservices, log ingestion.

Example: Publish a Message

bash

gcloud pubsub topics publish my-topic --message="Hello World"

📊 6. BigQuery (Analytics & Warehousing)

BigQuery is Google’s serverless enterprise data warehouse.

Key Features:

• ANSI SQL support
• Massive-scale analytics on petabytes of data
• Near real-time performance

Use Case: Marketing analytics, financial modeling, ad-tech analysis.

Example: Run SQL Query

sql

SELECT name, SUM(amount)

FROM `project.dataset.sales`

GROUP BY name

🧠 7. AI & ML with Vertex AI

Vertex AI is a fully managed AI platform for training, deploying, and managing ML models.

Use Case:

• Build chatbots, predictive models, and recommender systems.

🛠️ 8. Monitoring and Observability

🔹 Cloud Monitoring

Track the performance of services, set alerts.

🔹 Cloud Logging

Capture and query logs from GCP services and apps.

Use Case: Debugging and real-time operational visibility.

🔐 9. IAM and Security Tools

• IAM for role-based access control
• Cloud Identity and SSO integration
• Cloud Key Management Service (KMS)
• VPC Service Controls and Policy Constraints

🧩 Summary Table – Core GCP Services Overview

📘 Use Case Scenarios