Stop 10 · Cloud Platforms (AWS / GCP / Azure)Topics · 4/11

GCP Fundamentals (Overview)

In short

Google Cloud is popular with data, analytics and ML teams, and its building blocks map closely to AWS. Once you know one cloud, learning the second is mostly learning new names.

Google Cloud's equivalent core services — Compute Engine, Cloud Storage, VPC, and IAM — conceptually similar to AWS's equivalents, useful to know at least at an overview level given GCP's strong presence in data/ML-heavy companies.

The mascot compares two plates from different restaurants holding the same dishes arranged differently.

Think of it like this

Same dishes, different restaurant

Two restaurants both serve dal, rice and paneer, but one calls it 'Dal Tadka Special' and plates it differently. You still know what you're eating. GCP and AWS are like that: the same core dishes under different names, with a few house specialities.

Watch it happen

GCP names for things you already know

Compute Engine

Cloud Storage

VPC

IAM

GKE

Cloud Run

1/5Compute Engine runs virtual machines, like EC2.

The big ideas

What you need to know

Projects hold everything

Every resource belongs to a project, which also carries billing and API settings. Use one project per app per environment.

Service accounts

Apps run as service accounts. Grant them narrow roles instead of using personal credentials.

Regions in India

asia-south1 is Mumbai and asia-south2 is Delhi, handy for low latency to Indian users.

Data strengths

BigQuery, Google's serverless data warehouse, is a big reason data teams pick GCP.

See it in code

Walk through the code

bash

1gcloud projects list2gcloud config set project my-first-project-1233gcloud compute instances create web-1 --zone=asia-south1-a --machine-type=e2-micro4gcloud storage buckets create gs://riya-notes-demo-2026 --location=asia-south15gcloud compute instances delete web-1 --zone=asia-south1-a

1/3Choose which project the following commands act on.

Replace the project ID with your own. Free tier limits change and often apply only to certain regions, so check the current terms first.

Save yourself the pain

Common mistakes

Oops

Putting dev and prod resources in one GCP project.

Do this instead

Use separate projects. It keeps permissions, quotas and billing apart, and makes cleanup safe.

Oops

Downloading service account JSON keys for apps running on GCP.

Do this instead

Attach the service account to the VM, Cloud Run service or GKE workload instead. Downloaded keys leak.

Your mission

Translate an AWS setup

~20 min

Quick check

In GCP, what is the main container for resources, billing and API settings?

Go deeper

1Explore GCP's free tier and compare its console layout to AWS's.
2Map GCP's core services to their AWS equivalents (Compute Engine ≈ EC2, Cloud Storage ≈ S3).
3Learn GCP's particular strengths (data/ML tooling, global network) at a high level.