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Google Cloud Resources: Global, Regional, and Zonal

Google Cloud resources are generally classified into three categories based on their scope:

  • Global Resources

  • Regional Resources

  • Zonal Resources

1. Global Resources

Global resources are not limited to a specific region or zone. They are accessible across all Google Cloud regions.

Examples of global resources include:

  • VPC Networks

  • IAM

  • Cloud DNS

  • Firewall Rules

  • Global Load Balancers

A VPC network is a global resource, meaning it can span multiple regions.

2. Regional Resources

A region is a geographic location where Google Cloud operates one or more data centers. This is where you deploy your cloud infrastructure.

Each region contains multiple zones, providing high availability and fault tolerance.

Examples of regional resources include:

  • Subnets

  • Cloud SQL

  • Cloud NAT

  • Cloud Routers

  • Regional Persistent Disks

A subnet is always regional, meaning it belongs to a single region. Multiple subnets can exist within the same global VPC, with one subnet created for each region as needed.

3. Zonal Resources

Each region is divided into multiple zones. A zone represents one or more physical data centers within that region.

Most compute resources are created in a specific zone.

Examples of zonal resources include:

  • Virtual Machine (VM) instances

  • Standard Persistent Disks

  • GPUs

  • TPUs

For example, if you create a VM in us-central1-a, both the VM and its attached standard persistent disk are zonal resources.

Google Cloud Global Network

Google Cloud has a high-speed global private network that connects all of its regions around the world.

When infrastructure is deployed across multiple regions, communication between those regions uses Google's global network, providing secure and reliable connectivity.

Summary

  • Global Resources: Available across all regions (e.g., VPC, IAM, Cloud DNS, Firewall Rules).

  • Regional Resources: Exist within a single region and support multiple zones (e.g., Subnets, Cloud SQL, Cloud NAT).

  • Zonal Resources: Deployed within a specific zone (e.g., VM instances, Standard Persistent Disks, GPUs).

Resource Hierarchy

Google Cloud
│
├── Global Resources
│     ├── VPC Network
│     ├── IAM
│     ├── Cloud DNS
│     └── Firewall Rules
│
├── Region
│     ├── Subnet
│     ├── Zone A
│     │      ├── VM
│     │      └── Persistent Disk
│     ├── Zone B
│     └── Zone C
│
└── Another Region
      ├── Subnet
      ├── Zone A
      ├── Zone B
      └── Zone C

This hierarchy helps organize Google Cloud resources and improves scalability, availability, and fault tolerance when designing cloud infrastructure.



Based on the whiteboard in your image, here's a clean and well-organized version of the notes.

Google Cloud Platform (GCP) Services Overview

Google Cloud Platform (GCP) provides a wide range of cloud services that are grouped into four major categories:

  • Compute

  • Storage

  • Big Data

  • Artificial Intelligence (AI)

1. Compute Services

Compute services provide the infrastructure and platforms required to run applications.

Compute Engine

  • Provides Virtual Machines (VMs).

  • Offers complete control over the operating system and infrastructure.

  • Best suited for traditional applications and custom workloads.

Kubernetes Engine (GKE)

  • Managed Kubernetes service for deploying and managing containerized applications.

  • Automates container orchestration, scaling, and management.

App Engine

  • A Platform as a Service (PaaS) offering.

  • Developers can deploy applications without managing servers.

  • Best suited for web and enterprise applications.

Cloud Functions

  • A serverless compute service.

  • Executes code in response to events.

  • Ideal for lightweight applications, automation, and event-driven workloads.

2. Storage Services

Storage services are used to store structured, semi-structured, and unstructured data.

Cloud Storage

  • Object storage for files, images, videos, backups, and static website content.

Bigtable

  • A NoSQL database designed for large-scale analytical and operational workloads.

  • Suitable for applications requiring low latency and high throughput.

Cloud SQL

  • Managed relational database service.

  • Supports MySQL, PostgreSQL, and SQL Server.

Cloud Spanner

  • Globally distributed relational database.

  • Combines SQL capabilities with horizontal scalability and high availability.

Cloud Datastore (Firestore in Datastore mode)

  • NoSQL document database.

  • Designed for applications that require flexible schemas and automatic scaling.

3. Big Data Services

Big Data services help organizations ingest, process, analyze, and manage large volumes of data.

BigQuery

  • Fully managed data warehouse.

  • Enables fast SQL analytics on massive datasets.

Pub/Sub

  • Messaging and event ingestion service.

  • Used for real-time data streaming and communication between applications.

Dataflow

  • Fully managed data processing service.

  • Supports both stream processing and batch processing using ETL pipelines.

Data Catalog

  • Metadata management service.

  • Helps organize, discover, and govern enterprise data assets.

4. Artificial Intelligence (AI) Services

Google Cloud provides pre-trained AI services that can be integrated into applications.

Natural Language API

  • Performs sentiment analysis.

  • Extracts entities and syntax from text.

  • Understands natural language.

Vision API

  • Analyzes images.

  • Detects objects, faces, logos, labels, and text.

Speech-to-Text API

  • Converts spoken audio into text.

  • Supports multiple languages.

Translation API

  • Translates text between different languages.

  • Useful for multilingual applications.

Summary Table

CategoryServicesPurpose
ComputeCompute Engine, GKE, App Engine, Cloud FunctionsRun applications and workloads
StorageCloud Storage, Bigtable, Cloud SQL, Cloud Spanner, Cloud DatastoreStore structured and unstructured data
Big DataBigQuery, Pub/Sub, Dataflow, Data CatalogData ingestion, processing, analytics, and governance
AINatural Language API, Vision API, Speech-to-Text API, Translation APIBuild intelligent applications using machine learning

These notes closely match the content shown on the whiteboard while presenting the information in a structured, interview-friendly format that is easy to study and revise.


3. Creating the new project .

go to console.google.com

https://console.cloud.google.com


creating the new project .



After creating the project it looks like this .


after that we can create the resources we want and if we want to exit the project we need to click .

settings --> shut down .



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