Google Cloud Platform (GCP) Cheat Sheet: Architecture, Services, and Core Concepts

What is Google Cloud Platform (GCP)?

GCP is Google’s suite of cloud computing services that enables organizations to store, compute, and analyze data at scale. Leveraging the same infrastructure that powers Google Search, GCP delivers high‑performance, secure, and globally distributed resources to developers and enterprises alike.

The GCP Architecture

At its core, GCP follows a multitenant model that allows multiple users to run workloads on shared physical infrastructure while keeping workloads isolated and secure. This architecture delivers rapid provisioning, elastic scaling, and cost efficiency.

Key Advantages of GCP

• Continuous Innovation – Google releases updates weekly, boosting productivity and keeping services at the cutting edge.
• Seamless Feature Rollout – Incremental improvements reduce the risk of large‑scale migrations.
• Remote Work Enablement – Cloud‑based tools give employees secure, device‑agnostic access to data and applications.
• Real‑Time Collaboration – Centralized storage and project sharing eliminate local bottlenecks.
• Enterprise‑Grade Security – Dedicated security teams, hardware‑backed encryption, and advanced threat detection protect data.
• Data Sovereignty & Flexibility – Users control where data resides and can move it out of GCP at any time.

Core GCP Services

Compute

• Compute Engine – VMs, GPUs, TPUs, persistent disks
• Cloud Run – Serverless containers
• Cloud Functions – Event‑driven serverless functions
• Kubernetes Engine (GKE) – Managed Kubernetes
• App Engine – Managed application platform
• Bare Metal Solution – Dedicated hardware for latency‑critical workloads
• Preemptible & Shielded VMs – Cost‑effective and hardened instances
• Sole‑tenant nodes – Dedicated physical servers for isolation

Storage

• Cloud Storage – Object storage with multi‑region tiers
• Cloud Filestore – Managed NFS file server
• Persistent Disk – Block storage for VMs
• Local SSD – High‑performance, attached SSDs

Databases

• Cloud SQL – Managed MySQL, PostgreSQL, SQL Server
• Cloud Spanner – Horizontally scalable relational DB
• Cloud Bigtable – Petabyte‑scale NoSQL
• Cloud Firestore – Serverless document database
• Cloud Memory Store – Managed Redis and Memcached

Data & Analytics

• BigQuery – Serverless data warehouse
• BigQuery BI Engine – In‑memory analytics
• BigQuery ML – Build ML models directly in BigQuery
• Dataflow – Unified batch and streaming pipelines
• Dataproc – Managed Hadoop/Spark clusters
• Dataprep – Visual data wrangling
• Data Fusion – Drag‑and‑drop data integration
• Data Catalog – Centralized metadata management
• Looker – Enterprise BI platform
• Cloud Composer – Workflow orchestration

Hybrid & Multi‑Cloud

• Anthos – Unified management across on‑prem and cloud
• Anthos GKE – Kubernetes on premises
• Anthos Service Mesh – Istio‑based service mesh
• Migrate for Anthos – VM to Kubernetes migration
• Cloud Build – CI/CD pipelines
• Operations Suite – Logging, monitoring, and error reporting
• Apigee API Platform – Design, secure, and monetize APIs

AI & Machine Learning

• AI Platform – End‑to‑end ML workflow
• AutoML (Vision, Language, Translation, Video, Tables) – Custom model training
• Cloud Vision, Speech, Translation, Text‑to‑Speech APIs – Pre‑built AI services
• Dialogflow – Conversational UI builder
• Document AI – Intelligent document understanding
• Cloud TPU – Accelerated ML training
• Recommendation AI – Personalized recommendation engine

Networking

• VPC – Software‑defined private networks
• Cloud CDN – Global content delivery
• Cloud Load Balancing – Global, multi‑region load distribution
• Cloud Armor – DDoS protection and WAF
• Interconnect (Dedicated, Partner) – Private connectivity to on‑prem
• Cloud DNS – Programmable DNS
• Cloud NAT & VPN – Secure outbound connectivity
• Network Intelligence Center – Visibility into network topology

Identity & Security

• Cloud IAM & IAM‑Aware Proxy – Granular access control
• Cloud Security Command Center – Unified security dashboard
• Cloud KMS & Cloud HSM – Key management and hardware security modules
• Cloud Data Loss Prevention API – Data classification and redaction
• Binary Authorization – Policy‑based image signing
• Access Transparency & Audit Logs – Detailed audit trails
• VPC Service Controls – Data exfiltration protection

Management & Developer Tools

• Cloud Console & Cloud Shell – Web and CLI access
• Cloud SDK – Local command‑line utilities
• Cloud Build, Cloud Deploy – CI/CD and release management
• Cloud Code – IDE extensions for IntelliJ, VS Code
• Cloud Scheduler, Cloud Tasks – Job scheduling and queuing
• Artifact & Container Registry – Private image and package storage
• Cloud Debugger, Cloud Profiler, Cloud Trace – Runtime diagnostics

Migration to GCP

• Storage Transfer Service – Bulk data import
• BigQuery Data Transfer Service – Ingest analytics data
• Cloud Migration Hub – Centralized migration tracking
• Migrate for Compute Engine – VM lift‑and‑shift to GCE
• Migrate for Anthos – VM to Kubernetes lift‑and‑shift
• Google Transfer Appliance – Physical data transport

API Platform & Ecosystems

• Apigee – API design, monitoring, and monetization
• Cloud Endpoints – Managed API gateway
• Cloud Healthcare API – Interoperability for health data
• API Analytics & Monetization – Usage insights and revenue models

Google Maps Platform

• Maps JavaScript, SDKs for Android, iOS, Unity – Dynamic map rendering
• Directions, Distance Matrix, Geocoding, Geolocation APIs – Location services
• Places API, Roads API, Street View APIs – Local information and imagery
• Time Zone API – Coordinate‑to‑time‑zone conversion

G Suite (Google Workspace) APIs

• Admin SDK, Drive API, Docs API, Sheets API, Gmail API, Calendar API – Core productivity tools
• Cloud Search, Data Studio, Looker – Enterprise search and BI
• G Suite Marketplace & Add‑ons – Extending workspace functionality

Mobile & Firebase

• Cloud Firestore, Realtime Database – NoSQL storage for mobile
• Cloud Functions for Firebase, Cloud Messaging – Serverless backend and push notifications
• Crashlytics, Performance Monitoring – Real‑time app diagnostics
• Authentication, Remote Config, A/B Testing – User management and experimentation
• Firebase Hosting, Cloud Storage for Firebase – Web hosting and asset storage

Open‑Source Projects

• Apache Beam, TensorFlow, Kubeflow – Data processing and ML frameworks
• Istio, Knative, gRPC, gVisor – Service mesh, serverless, RPC, and container security
• OpenCensus – Observability for cloud native applications

Getting Started on GCP

Begin with these foundational tasks to familiarize yourself with GCP’s core capabilities:

• Create, SSH into, and delete a Linux VM on Compute Engine.
• Set up a Cloud Storage bucket, upload a file, and share it with others.
• Deploy a containerized application to Cloud Run or GKE using Cloud Shell.
• Train a TensorFlow model on Cloud AI Platform and deploy it via Cloud Functions.
• Run a label detection job with the Cloud Vision API on an image.
• Deploy a simple Python App Engine application to understand managed services.

Further Resources

• 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
• 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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