Services used for developing application:

• Cloud CDN: Speeds up content delivery globally by caching it in data centers near users for faster access.

• Cloud Run: A fully managed service that runs containerized applications with auto-scaling based on demand.

• Cloud SQL: A managed relational database service for MySQL, PostgreSQL, and SQL Server.

• Identity Platform: Manages user authentication, offering login, registration, and user management features.

• Cloud Scheduler: A service to run cron jobs, and scheduling tasks like backups or notifications at specific times.

• Cloud Functions: Serverless functions that execute code in responding events or HTTP requests.

• Cloud Pub/Sub: A messaging service for real-time data processing and communication between applications.

• BigQuery: A fully managed data warehouse for fast SQL-based analysis of large datasets.

• Cloud Dataflow: Processes and transforms large data streams or batches using Apache Beam.

• Cloud Monitoring: Tracks the performance and health of your applications and services.

• Cloud Logging: Collects and analyzes log data from your applications and infrastructure.

• Cloud Armor: Protects your applications from DDoS attacks and other threats with security policies.

• VPC (Virtual Private Cloud): A customizable network to securely connect and isolate cloud resources.

• Cloud Build: Automates the building, testing, and deployment of code for your applications.

• Artifact Registry: Stores and manages container images and packages for deployment.

• Cloud Load Balancing: Distributes incoming traffic across multiple servers to improve availability and performance.

• Auto-scaling: Automatically adjusts the number of resources (like servers) based on traffic or demand to optimize performance and cost.

Flow Diagram and Use Case Explanation :

1. Frontend (Client Side)

• Users: Customers interact with your website through browsers or mobile apps.

• Static Content Delivery:

Cloud Storage: Set up Google Cloud Storage to host static assets like images, CSS, and JavaScript.

Cloud CDN: Integrate Cloud CDN with Cloud Storage to deliver these assets globally with low latency.

Steps:

1. Upload static files (HTML, JS, CSS) to Google Cloud Storage.

2. Configure Cloud CDN to cache and deliver content faster to users.

2. Backend (API Layer)

• Cloud Run: Deploy containerized backend services to handle API requests, business logic, and authentication.

• Use Docker to containerize services.
• Deploy services on Cloud Run for auto-scaling and efficient management.

Steps:

1. Develop backend services (e.g., Node.js, Python, etc.).
2. Containerize your services using Docker.
3. Deploy each service on Google Cloud Run.
4. Set up authentication and handle API requests.

3. Database (Storage)

• Cloud SQL: Use Google Cloud SQL (MySQL/PostgreSQL) to store user data, product catalogs, and orders.
• Fully managed relational database with automated backups and scaling.

Steps:

1. Create a Cloud SQL instance.
2. Configure database schemas for products, users, orders, etc.
3. Connect backend services (from Cloud Run) to the database.

4. Authentication

• Identity Platform: Manage user authentication using OAuth, Google, Facebook, or custom logins.

Steps:

1. Enable Identity Platform in your GCP project.
2. Configure authentication methods (Google, Facebook, etc.).
3. Integrate with the frontend and backend to handle login, registration, and session management.

5. Microservices Architecture

• Product Service: Handles product catalog operations.
• Order Service: Manages order processing and workflows.
• Payment Service: Integrates with payment gateways like Stripe.

Steps:

1. Develop each service (product, order, payment) as separate containers.
2. Deploy services on Cloud Run.
3. Set up API endpoints for each service.

6. Task Scheduling and Event-Driven Actions

• Cloud Scheduler: Automate periodic tasks like sending emails or data backups.
• Cloud Functions: Trigger serverless functions for events (e.g., task completion, order notifications).

Steps:

1. Use Cloud Scheduler to schedule jobs (e.g., sending reminder emails).
2. Write Cloud Functions to handle event-based tasks (e.g., new order notifications).

7. Storage and Media Management

• Cloud Storage: Use Google Cloud Storage to store product images and user-uploaded files.
• Cloud Pub/Sub: Implement event-driven messaging for actions like order notifications and status updates.

Steps:

1. Store and serve images and media files from Cloud Storage.
2. Use Cloud Pub/Sub for messaging between microservices.

8. Analytics

• BigQuery: Store and analyze large datasets (e.g., sales data, user interactions).
• Cloud Dataflow: Use Cloud Dataflow for real-time or batch processing of analytical data.

Steps:

1. Stream or batch important data (e.g., orders, user activity) into BigQuery.
2. Use Dataflow for large-scale data transformations or real-time analytics.

9. Monitoring and Logging

• Cloud Monitoring: Set up monitoring for uptime and performance of all services.
• Cloud Logging: Collect logs from Cloud Run, SQL, and other services for analysis.

Steps:

1. Enable Cloud Monitoring for key performance metrics.
2. Use Cloud Logging to collect logs for debugging and auditing.

10. Security

• Cloud Armor: Set up firewall rules to protect against DDoS attacks.
• VPC: Use Virtual Private Cloud for secure networking and isolation.

Steps:

1. Configure Cloud Armor with security policies.
2. Set up a VPC to isolate and secure backend resources.

11. Deployment and CI/CD

• Cloud Build: Automate build and deployment processes.
• Artifact Registry: Store Docker images and other build artifacts.

Steps:

1. Set up Cloud Build to automate deployments from your code repository.
2. Store Docker images in Artifact Registry for easy deployment to Cloud Run.

12. Scaling

• Cloud Load Balancing: Distribute traffic across multiple backend services.
• Auto-scaling: Use Cloud Run’s auto-scaling feature to dynamically adjust the number of instances based on traffic.

Steps:

1. Configure Cloud Load Balancing to route traffic to Cloud Run instances.
2. Set up auto-scaling policies to scale services during high traffic.