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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