Google Cloud Platform (GCP) Cheat Sheet

One of the most famous and leading players in the cloud computing and service market is Google Cloud Platform (GCP). Google’s expertise in running data centers cannot be denied. Given the fact that it runs the world’s top and the most advanced search engine. After Amazon Web Services (AWS) was launched in 2006, Google started to implement its data center expertise for the launch of its very own cloud service.

Moving forward, as of today, besides AWS and Microsoft Azure, GCP has become one of the three big players in public cloud vendor services. The high-level standard of service provided by Google has allowed it to become the leader of the market space, and it will continue to grow soon.

Keeping in view the success and popularity of GCP, the demand for professionals with GCP is increasing continuously. In this article, we will get through a Google Cloud cheat sheet to obtain a basic understanding of Google Cloud Platform.

What is the Google Cloud Platform (GCP)?

In simpler terms, Google Cloud Platform (GCP) can be best defined as a group of cloud computing products and services offered by Google. These cloud services provided by GCP helps the clients and users to store and compute data. Moreover, it also allows web developers to build, test, and deploy applications.

The Architecture of the Google Cloud Platform

Google Cloud Platform architecture is a variant of computing architecture that includes the formation of one or more logical software cases besides executing them above the primary software. The multitenancy of architecture enables numerous users to execute in a software environment simultaneously with different user services, interfaces, and resources.

Critical Advantages of Google Cloud Platform

Following are the benefits of GCP, which can helpful for you to form a factual basis of reasons to implement the Google Cloud Platform:

High Productivity – Quick Access to Innovation: Google’s systems are proficient in delivering updates proficiently every week. It leads to higher productivity and efficiency.

Easier Adoption of New Functionality for Users: Through a continuous stream, it delivers manageable improvements that involve lesser batches of change.

Employees Can Work Remotely: GCP hands over massive advantages to its employees. Remote working is one of them. Through web-based apps powered by Google Cloud, it enables full access to information across devices regardless of the location.

Quick Collaboration: Cloud computing makes it easier for Google users to access various projects simultaneously while data is being saved in the cloud instead of personal machines.

Enhanced Security: Google believes in the top-notch security of data. Therefore, leading security experts are employed by Google to provide customers the improved security benefits.

Lesser Data Vulnerability: GCP enables users to store data on personal computers at a minimal level. In the absence of web-based apps on the cloud platform, data on personal computers are more vulnerable to a security breach.

Control and Flexibility: GCP also allows users to have complete control over technology and ownership of their data stored in Google apps. Moreover, if the user decides against a service, the data can be pulled out of Google cloud.

GCP Products and Services

Now that you have gone through what Google Cloud Platform is and what are the notable advantages of deploying it let’s move forward and look into the products and services offered by Google. Following is a list of available products and services provided by Google:

Computing and Hosting: Computing and hosting services by GCP offer different options that include; working in a server-less environment or the utility of a managed application platform. It also provides additional flexibility and maximum control.

Machine learning: Google’s offered AI Platform offers several machine learning services. Users have the option to select APIs with pre-trained models for specific applications. Moreover, it also empowers users to build and practice their personal large-scale, comprehensive models with the help of a managed TensorFlow framework.

Storage: While talking about GCP storage services, the leading name that comes to mind is Google Cloud Storage. Consistency, scalability, and the large capacity for data storage are some features offered by it. Filestore is another outstanding storage service that provides fully managed NFS file servers.

Big Data: The services offered by Big Data include BigQuery for data analysis services, Dataflow for batching and streaming data processing, and Pub/Sub for asynchronous messaging.

Networking: Networking is one of the frequently used services with App Engine handling. The GKE implements Kubernetes Model with networking resources by Compute Engine. The networking services can help in developing DNS records, the connection between the existing network to Google’s system, and traffic load-balancing across resources.

Databases: The backbone of GCP’s popularity is undoubtedly the assortment of SQL and NoSQL database. MySQL or PostgreSQL databases are two options of Cloud SQL on GCP. Two distinctive substitutes to NoSQL data storage are The Cloud Firestore and Cloud Bigtable. Users also have the option of Cloud Spanner that offers an entirely managed, relational database service with transactional constancy. Schemas, SQL querying, and automatic synchronous replication are some other handy features of Cloud Spanner.

GCP: Terms, Definition, and Vocabulary

Before we start the GCP Cheat Sheet, it’s essential to understand the terms and definitions that relate to the Google Cloud Platform, and cloud computing holds great importance. Let’s go through and understand some common terms, definitions, and glossary.

Cloud Computing: The network and internet-based delivery of IT resources and services rather than through on-premise resources.

Cloud Migration: The process involved in shifting data, applications, and services from on-premise systems to the cloud.

Cloud Service Provider (CSP): Any entity which offers cloud computing services, either PaaS, IaaS, or SaaS.

Container: A virtual instance with the facility of multiple remote user-space cases permitted by the kernel of an operating system.

DevOps: An approach derived from the blend of development and operations teams that encourages communication, collaboration, and integration.

Google Cloud Platform: GCP is the cloud service offered by Google that provides both Infrastructures as a Service (IaaS) and Platform as a Service (PaaS) products.

Host Machine: The physical machine, usually a server which stores multiple containers or virtual machines in it.

Hybrid Cloud: A cloud computing system created with an amalgamation of both public and private clouds together with on-premises solutions.

Instance: A single server or virtual machine which supports a specific workload.

Multitenancy: Model of A software operation model that enables multiple instances of one or more applications running in a shared environment.

All Products & Services

Compute

Cloud Run: A server-less service for containerized applications

Cloud Functions: Event-specific, server-less functions

Compute Engine: VMs, TPUs, GPUs, Disks

Kubernetes Engine (GKE): Managed Kubernetes/containers solution

App Engine: A managed application platform

Bare Metal Solution: Hardware designed for specialized workloads

Preemptible VMs: Short-lived computing instances

Shielded VMs: Hardened VMs

Sole-tenant nodes: Dedicated physical servers

Storage

Cloud File Store: Managed Network File System server

Cloud Storage: Multi-class and multi-region object storage

Persistent Disk: Blocked storage for VMs

Local SSD: VM locally attached to SSDs

Database

Cloud Bigtable: Petabyte-scale, non-relational, and low-latency

Cloud Filestore: Server-less, NoSQL document Database

Cloud Memory Store: Redis and Memcached which is managed

Cloud Spanner: Horizontally scalable relational Database

Cloud SQL: Managed SQL Server, MySQL, PostgreSQL

Data and Analytics

BigQuery: Data warehouse and analytics

BigQuery BI Engine: In-memory analytical engine

BigQuery ML: BigQuery model training and serving

Cloud Composer: A managed service of workflow orchestration

Cloud Data Fusion: Data pipelines that are graphically managed

Cloud Dataflow: Stream or batch processing of data

Cloud Dataprep: Visual data wrangling

Cloud Dataproc: Managed services of Hadoop and Spark

Cloud Pub/Sub: Global and real-time messaging

Data Catalog: A use of metadata management

Data Studio: Collective data exploration/dash boarding

Looker: Enterprise-level BI and Analytics

Hybrid and Multi-cloud

Authors: Enterprise-level hybrid and multi-cloud platform

Anthos GKE: Kubernetes Engine that is hybrid, on-prem

Anthos Configuration Management: Automation of policy and security

Anthos Service Mesh: Istio - Managed service mesh

Cloud Run for Anthos: A server-less development for Anthos

Google Cloud Marketplace for Anthos: Pre-configured containerized apps

Migrate for Anthos: Migration of VMs to Kubernetes Engine

Operations: Logging, monitoring, troubleshooting

Cloud Build: Continuous incorporation/delivery platform

Traffic Director: Service mesh traffic management

Apigee API Management: API development, management, security

AI/ML

AI Hub: Hosted AI component sharing

AI Platform Data Labeling: Humans controlled data labeling

AI Platform Deep Learning VMs: Pre-configured VMs intended for deep learning

AI Platform Deep Learning Containers: Pre-configured containers intended for deep learning

AI Platform Notebooks: Managed JupyterLab notebook cases

AI Platform Pipelines: Hosted ML work-flows

AI Platform Predictions: Auto-scaled model serving

AI Platform Training: Dispersed AI training

AI Platform: A managed platform for ML

AutoML Natural Language: Custom models of text

AutoML Tables: Specific structured data models

AutoML Translation: Customized domain-specific translation

AutoML Video Intelligence: Customized video annotation models

AutoML Vision: Custom image models

Cloud Natural Language API: Parsing and analysis of text

Cloud Speech-to-Text API: Audio conversion to text

Cloud Talent Solutions API: Job searching with ML

Cloud Text-To-Speech API: Text conversion to audio

Cloud TPU: Hardware acceleration for ML

Cloud Translation API: Detection of language and its translation

Cloud Video Intelligence API: Scene-level video annotation

Cloud Vision API: Recognition and grouping of image

Contact Center AI: AI-based in the contact center

Dialogflow: Create colloquial interfaces

Document AI: Classify, analyze, and search documents

Explainable AI: Understand ML model expectations

Recommendations AI: Make custom recommendations

Vision Product Search: Visual search related to products

Networking

Carrier Peering: Peering through a carrier

Direct Peering: Peering via GCP

Dedicated Interconnect: Dedicated private network connection

Partner Interconnect: Connect VPC with on-prem network

Cloud Armor: DDoS security and WAF

Cloud CDN: Network for content delivery

Cloud DNS: Programmable DNS serving

Cloud Load Balancing: Multi-region load distribution/balancing

Cloud NAT: Service related to network address translation

Cloud Router: VPC/on-prem network route exchange (BGP)

Cloud VPN (HA): Virtual private network connection (VPN)

Network Service Tiers: Price vs. performance ranking

Network Telemetry: Service related to network telemetry

Traffic Director: Service mesh traffic management

Google Cloud Service Mesh: Service aware network management

Virtual Private Cloud: Networking defined by software

VPC Service Controls: Security limits for API-based services

Network Intelligence Center: Network surveillance and topology

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Internet of Things (IoT)

Cloud IoT Core: Devices management and data ingestion

Gaming

Google Cloud Game Servers: Orchestrated Agones clusters

Identity and Security

Access Transparency: Access to the audit cloud provider

Binary Authorization: Deploy-time security of Kubernetes

Cloud Audit Logs: Audit tracks for GCP

Cloud Data Loss Prevention API: Categorize and redact critical data

Cloud HSM: Hardware related security module service

Cloud EKM: External keys controlled by the user

Cloud IAM: Resource access control 

Cloud Identity: Manage users, devices, and applications

Cloud Identity-Aware Proxy: Identity-based application access

Cloud KMS: Hosted key management service

Cloud Resource Manager: Management of cloud project metadata

Cloud Security Command Center: Security management and data risk platform

Cloud Security Scanner: Scanner of app engine security

Context-aware Access: End-user access control based on attribute

Event Threat Detection: Scans for doubtful activity

Managed Service for Microsoft Active Directory: Managed Microsoft Active Directory

Secret Manager: Accumulate and manage secrets 

Security Key Enforcement: Two-step key verification

Shielded VMs: Hardened VMs

Titan Security Key: A device for two-factor authentication (2FA)

VPC Service Controls: VPC data restrictions

Management Tools

Cloud APIs: APIs for services related to cloud

Cloud Billing API: GCP billing managed by the program

Cloud Billing: Tools of billing and cost management

Cloud Console: Web-based management console

Cloud Deployment Manager: Infrastructure deployment based on templates

Cloud Mobile App: iOS/Android GCP management app

Private Catalog: Internal Solutions Catalogue

Cloud Debugger: Live production debugging

Error Reporting: Application error reporting

Cloud Logging: Centralized logging

Cloud Monitoring: Infrastructure and application monitoring 

Cloud Profiler: CPU and heap profiling

Cloud Trace: Application performance understandings

Transparent SLIs: Monitoring of GCP services

Developer Tools

Cloud Build: Constant integration and delivery platform

Cloud Code for IntelliJ: IntelliJ GCP tools

Cloud Code for VS Code: VS Code GCP tools

Cloud Code: Cloud-native IDE extensions

Cloud Scheduler: Cron job service

Cloud SDK: CLI for GCP

Cloud Shell: Terminal/CLI based on browser

Cloud Source Repositories: Hosted private Git repos

Cloud Tasks: Asynchronous task implementation

Cloud Tools for Eclipse: Eclipse GCP tools

Cloud Tools for Visual Studio: GCP tools for Visual Studio

Container Analysis: Programmed security scanning

Container Registry: Private container registry/storage

Artifact Registry: Universal package manager

Gradle App Engine Plugin: Plugin for Gradle App Engine

Maven App Engine Plugin: Plugin for Maven App Engine

Migration to GCP

BigQuery Data Transfer Service: Big amount of import analytics data

Cloud Data Transfer: Data relocation tools/CLI

Google Transfer Appliance: Rentable data transport box

Migrate for Anthos: Transfer VMs to GKE containers

Migrate for Compute Engine: Compute Engine migration tools

Migrate from Amazon Redshift: Migration from Redshift to BigQuery

Migrate from Teradata: Migration from Teradata to BigQuery

Storage Transfer Service: Online/on-premises transfer of data

VM Migration: VM transfer tools

Cloud Foundation Toolkit: Infrastructure as Code outlines

API Platform and Ecosystems

API Analytics: API metrics

API Monetization: Financial aspect of APIs

Apigee API Platform: Develop, monitor, and secure APIs

Apigee Hybrid: Management of hybrid/multi-cloud API environments

Apigee Sense: Protection of API from attacks

Cloud Endpoints: Cloud API gateway

Cloud Healthcare API: GCP interoperability of healthcare systems

Developer Portal: Management portal of API

GCP Marketplace: Partner & open source market

Google Maps Platform

Directions API: Acquire directions between locations

Distance Matrix API: Multi-origin/destination travel times

Geocoding API: Conversion of address to/from coordinates

Geolocation API: Originate location without using GPS

Maps Embed API: Demonstrate iframe embedded maps

Maps JavaScript API: Dynamic web maps

Maps SDK for Android: Maps made for Android applications

Maps SDK for iOS: Maps made for iOS applications

Maps Static API: Display stationary map images

Maps SDK for Unity: Unity SDK used for games

Maps URLs: URL system for maps

Places API: Rest-based Places features

Places Library, Maps JS API: Places features intended for web

Places SDK for Android: Places features made for Android

Places SDK for iOS: Places feature for iOS

Roads API: Change coordinates into roads

Street View Static API: Stationary Street view images

Street View Service: The street view for JavaScript

Time Zone API: Convert coordinates to time-zone

G Suite Platform

Admin SDK: Management of G Suite resources

AMP for Email: Dynamic and interactive email

Apps Script: Spread and automate almost everything

Calendar API: Calendars creation and management

Classroom API: Establish and manage classrooms

Cloud Search: Combined search for enterprise

Docs API: Documents creation and edition

Drive Activity API: Recover Google Drive activity

Drive API: Read and write files

Drive Picker: File selection widget of drive

Email Markup: Interactive email using schema.org

G Suite Add-ons: Spread G Suite apps

G Suite Marketplace: Storefront for incorporated applications

Gmail API: Improve Gmail

Hangouts ChatBots: Colloquial bots in chat

People API: User’s contacts management

Sheets API: Create, read, and write spreadsheets

Slides API: Create, read, and edit presentations

Task API: Search, read, and update Tasks

Vault API: Management of your organization’s eDiscovery

Mobile (Firebase)

Cloud Firestore: Document storage and synchronization

Cloud Functions for Firebase: Event-driven, server-less applications

Cloud Storage for Firebase: Storage and serving of Object

Crashlytics: Crash recording and analytics

Firebase A/B Testing: Creation of A/B test experiments

Firebase App Distribution: Reliable tester quick access

Firebase Authentication: Drop-in authentication

Firebase Cloud Messaging: Send device notifications

Firebase Dynamic Links: Link to application content

Firebase Extensions: Pre-installed development solutions

Firebase Hosting: Web hosting with CDN/SSL

Firebase In-App Messaging: Send in-app relative messages

Firebase Performance Monitoring: Monitoring of app/web performance

Firebase Predictions: Forecast user targeting

Firebase Realtime Database: Real-time synchronization of data

Firebase Remote Config: Remote configuration of installed apps

Firebase Test Lab: Mobile testing device farm

Google Analytics for Firebase: Mobile application analytics

ML Kit for Firebase: ML APIs for mobile

GCP Foundational Open Source Projects

Apache Beam: Data processing service of batch/streaming

gRPC: Remote Procedure Call (RPC) framework

gVisor: Protected container runtime

Istio: Connecting and safeguarding services

Knative: Server-less framework for Kubernetes

Kubeflow: Machine learning toolkit for Kubernetes

Kubernetes: Management service of containerized application

OpenCensus: Framework made for cloud-native observability

TensorFlow: Machine learning framework

How to Work on the Google Cloud Platform?

Let’s briefly look into the details of the basic steps for working on GCP. The most effective way to learn is by taking small steps. These small steps can be practiced with the help of some quick-start guides related to the Google Cloud Platform. The said guides are real-time activities that contain basic tasks. 

• The first task is to learn about the creation of a Linux VM, connecting with it, and ultimately deleting it. This simple and easy task can be beneficial in learning about the Google Compute Engine.
• The next activity to learn about working on GCP is knowing how to store a file and share it. This activity contains some easy to understand tasks of bucket creation, file uploading, file sharing, and then it is organizing into a folder. Google Cloud Storage can be learned through this activity.
• You can gain an essential impression of Kubernetes Engine and Cloud SDK with a simple task of deploying a Docker Container Image. The activity involves using Cloud Shell for configuration of cloud and running a container image. 

Other necessary activities that you can practice are as under:

• For understanding Machine Learning API, training a TensorFlow model locally in the Cloud with a solitary worker and a dispersed environment.
• Through the Cloud Vision API service, running label detection on an image can also be practiced.
• Deployment of a small App Engine application through the creation of a Python application for a basic understanding of Google App Engine

Additional Resources

Below are some additional resources related to GCP:

• Google Cloud Home Page
• Google Cloud Blog
• Google Cloud Open Source
• GCP Medium Publication
• Apigee Blog
• Firebase Blog
• G Suite Developers Blog
• G Suite GitHub
• G Suite Twitter
• Google Cloud Certifications
• Google Cloud System Status
• Google Cloud Training
• Google Developers Blog
• Google Maps Platform Blog
• Google Open Source Blog
• Google Security Blog
• Kaggle Home Page
• Kubernetes Blog
• Regions and Network Map

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