Day 3: Cloud Storage, BigQuery, and Databases

Today's Objective

GCS buckets, lifecycle policies, Cloud SQL, Cloud Spanner, Firestore, and BigQuery — the data layer that underpins every GCP-native application.

Cloud Storage Buckets

gsutil commands

# Create a bucket (name must be globally unique) gsutil mb gs://my-unique-bucket-name # Upload files gsutil cp file.txt gs://my-bucket/ gsutil cp -r ./folder gs://my-bucket/folder/ # List bucket contents gsutil ls gs://my-bucket/ # Make a file public gsutil acl ch -u AllUsers:R gs://my-bucket/file.txt # Make entire bucket public (for static sites) gsutil iam ch allUsers:objectViewer gs://my-bucket

Python SDK

from google.cloud import storage

client = storage.Client()
bucket = client.bucket('my-bucket')

# Upload
blob = bucket.blob('uploads/photo.jpg')
blob.upload_from_filename('/local/photo.jpg')

# Generate signed URL (temporary private access)
url = blob.generate_signed_url(
    expiration=datetime.timedelta(hours=1),
    method='GET'
)

Cloud SQL

# Create a PostgreSQL instance
gcloud sql instances create my-db \
  --database-version=POSTGRES_15 \
  --tier=db-f1-micro \
  --region=us-central1

# Create a database
gcloud sql databases create myapp --instance=my-db

# Create a user
gcloud sql users create dbuser --instance=my-db --password=secret

# Connect via proxy
gcloud sql connect my-db --user=dbuser --database=myapp

📝 Day 3 Exercise

Build a File Upload App

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Day 3 Summary

GCS buckets store any file type. gsutil CLI + Python SDK for automation.
Signed URLs grant temporary access to private objects without making the bucket public.
Cloud SQL is managed PostgreSQL/MySQL — same SQL you know, GCP handles backups and updates.
db-f1-micro is the smallest Cloud SQL tier. Use it for development to minimize cost.

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Day 2: Compute: Cloud Run and GCE

Day 4: BigQuery for Analytics

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What's Next

The foundations from today carry directly into Day 4. In the next session the focus shifts to Cloud Run and Serverless — building directly on everything covered here.

Supporting Videos & Reading

Go deeper with these external references.

YouTube

Cloud Storage, BigQuery, and Databases — Video Walkthroughs Community tutorials and walkthroughs covering the concepts in this lesson.

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YouTube

Cloud Storage, BigQuery, and Databases Explained Deep-dive explanations and live-coding sessions from top educators.

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Official Docs

Official Documentation Primary reference documentation for the technologies covered in this lesson.

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GitHub

Open Source Examples Real-world codebases demonstrating the patterns taught in this lesson.

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Day 3 Checkpoint

Before moving on, verify you can answer these without looking:

What is the core concept introduced in this lesson, and why does it matter?
What are the two or three most common mistakes practitioners make with this topic?
Can you explain the key code pattern from this lesson to a colleague in plain language?
What would break first if you skipped the safeguards or best practices described here?
How does today's topic connect to what comes in Day 4?

Live Bootcamp

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Continue To Day 4

Day 4: BigQuery for Analytics

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