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Google Cloud Platform – GCP Core Cheat Sheet

Google Cloud Platform – GCP Core Cheat Sheet

Back to Cloud Computing
Updated 2026-04-20
Next Topic: Google Cloud Run Cheat Sheet

Google Cloud Platform (GCP) is Google's public cloud computing platform offering on-demand compute, storage, networking, databases, machine learning, and managed services that run on the same infrastructure powering Google Search, YouTube, and Gmail. GCP competes with AWS and Azure by emphasizing deep AI/ML integration (Gemini models, Vertex AI Agent Builder), global networking performance, and serverless-first architectures. A key mental model: GCP services are organized around a resource hierarchy (organizations → folders → projects → resources) with IAM for fine-grained access control, making multi-project, multi-team deployments easier to govern at scale than flat permission models.


What This Cheat Sheet Covers

This topic spans 20 focused tables and 114 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Compute ServicesTable 2: Storage ServicesTable 3: Cloud Storage ClassesTable 4: Database ServicesTable 5: Networking ServicesTable 6: Networking AdvancedTable 7: Security and IdentityTable 8: Monitoring and LoggingTable 9: Data Analytics and ProcessingTable 10: Machine Learning and AITable 11: DevOps and CI/CDTable 12: Serverless and Event-DrivenTable 13: API ManagementTable 14: Container and Artifact ManagementTable 15: Caching and In-MemoryTable 16: Resource ManagementTable 17: Billing and Cost ManagementTable 18: Regions and ZonesTable 19: Migration ServicesTable 20: Command-Line Tools

Table 1: Compute Services

Compute is where your code actually runs, and GCP gives you a full spectrum of options — from raw virtual machines you fully control, through managed Kubernetes and serverless containers, down to event-driven functions that scale to zero. The right choice usually comes down to how much of the underlying infrastructure you want to manage versus hand off to Google, with Cloud Run and Cloud Functions sitting at the most hands-off end and Compute Engine at the most flexible.

ServiceExampleDescription
Compute Engine
gcloud compute instances create my-vm --zone=us-central1-a --machine-type=e2-medium
• Virtual machines (VMs) on Google infrastructure
• choose predefined or custom machine types across families (E2, N2, C3, C4, H4D), supports GPUs and persistent disks
Cloud Run
gcloud run deploy my-service --image gcr.io/project/image --platform managed
• Serverless container platform that scales HTTP containers from zero to thousands
• pay-per-request, supports GPU workloads, websockets, and gRPC
Google Kubernetes Engine (GKE)
gcloud container clusters create my-cluster --num-nodes=3
• Managed Kubernetes for container orchestration
• Autopilot mode (Google manages nodes) and Standard mode (you manage nodes)
App Engine
gcloud app deploy app.yaml
• Platform-as-a-Service (PaaS) for web apps and APIs
• Standard environment (sandboxed, fast startup) or Flexible environment (custom runtimes on VMs)

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