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
| Category | Services | Purpose |
|---|---|---|
| Compute | Compute Engine, GKE, App Engine, Cloud Functions | Run applications and workloads |
| Storage | Cloud Storage, Bigtable, Cloud SQL, Cloud Spanner, Cloud Datastore | Store structured and unstructured data |
| Big Data | BigQuery, Pub/Sub, Dataflow, Data Catalog | Data ingestion, processing, analytics, and governance |
| AI | Natural Language API, Vision API, Speech-to-Text API, Translation API | Build 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.
Comments
Post a Comment