GCP Essentials
Core GCP services for developers: Compute Engine, Cloud Run, Cloud Build, Artifact Registry, Storage, SQL, Secrets, VPC, BigQuery, Vertex AI, and Firestore.
Cloud basics & GCP
What a cloud provider is, how GCP is organized (projects, regions, IAM, billing), and the mental model to navigate it.
Compute Engine — Virtual Machines
Rent raw virtual servers from Google. Maximum control, but you manage the OS, patches, scaling, and everything else.
Cloud Run — Serverless containers
Deploy a container and forget about servers: Cloud Run runs it, scales it to zero when idle, scales up under load, and gives you an HTTPS URL.
Cloud Build — CI/CD pipelines
Google's built-in build service: on every git push, it fetches your code, builds a container, runs tests, pushes to Artifact Registry, and can deploy to Cloud Run.
Artifact Registry — Container & package storage
A private Docker registry (and npm, Maven, Python) hosted by Google. Cloud Build pushes images here, Cloud Run pulls them from here.
Cloud Storage — Object storage
Buckets of files (images, backups, logs, static assets) accessible via URL or API. Cheap, infinitely scalable, not a filesystem.
Cloud SQL — Managed relational databases
PostgreSQL, MySQL, or SQL Server run by Google: backups, high availability, upgrades, and patches handled for you.
Secret Manager — Store secrets safely
A vault for API keys, DB passwords, and JWT secrets. Versioned, IAM-controlled, mounted as env vars in Cloud Run or fetched at build time by Cloud Build.
VPC — Virtual Private Cloud
The private network that glues your GCP resources together: subnets, firewall rules, routes, and how your Cloud Run or VM talks to your Cloud SQL without going through the internet.
BigQuery — Serverless analytics warehouse
A serverless SQL data warehouse. Load billions of rows, run analytical queries in seconds, pay per byte scanned. Not a transactional database.
Vertex AI — Google's ML platform
A unified platform to train, tune, deploy, and call ML models — including Google's Gemini family via the Gemini API. Covers the full ML lifecycle.
Firestore — Serverless NoSQL document database
A real-time NoSQL database with offline sync, live listeners, and granular security rules. Ideal for mobile/web apps that want live updates without building a backend.