Resource naming and labels in GCP - Mini Project: Build & Apply

Resource naming and labels

📖 Scenario: You are managing cloud resources for a small company. To keep things organized, you need to name your resources clearly and add labels that describe their purpose and environment.

🎯 Goal: Create a Google Cloud Storage bucket with a proper name and add labels to it for environment and team ownership.

📋 What You'll Learn

Create a bucket name variable with the exact name 'company-data-prod'.

Create a labels dictionary with keys 'environment' and 'team' and values 'production' and 'analytics' respectively.

Use the Google Cloud Storage client to create a bucket with the given name and labels.

Ensure the bucket creation code includes the labels in the bucket metadata.

💡 Why This Matters

🌍 Real World

In real cloud projects, naming resources clearly and adding labels helps teams find, manage, and automate resources easily.

💼 Career

Cloud engineers and administrators use naming conventions and labels daily to organize resources and control costs.

1

Create the bucket name variable

Create a variable called bucket_name and set it to the string 'company-data-prod'.

GCP

# Create a variable called bucket_name and set it to 'company-data-prod'
# Your code here

Need a hint?

Use simple assignment to create the variable bucket_name.

2

Create the labels dictionary

Create a dictionary called labels with the exact keys and values: 'environment': 'production' and 'team': 'analytics'.

GCP

bucket_name = 'company-data-prod'
# Create a dictionary called labels with keys 'environment' and 'team' and values 'production' and 'analytics'
# Your code here

Need a hint?

Use curly braces to create the dictionary with the exact keys and values.

3

Import the storage client and initialize it

Import storage from google.cloud and create a client instance called storage_client.

GCP

bucket_name = 'company-data-prod'
labels = {'environment': 'production', 'team': 'analytics'}
# Import storage from google.cloud and create storage_client
# Your code here

Need a hint?

Use from google.cloud import storage and then create storage.Client().

4

Create the bucket with labels

Use storage_client to create a bucket with the name bucket_name. Set the bucket's labels property to the labels dictionary before creating it with storage_client.create_bucket().

GCP

from google.cloud import storage

bucket_name = 'company-data-prod'
labels = {'environment': 'production', 'team': 'analytics'}

storage_client = storage.Client()
# Create a bucket object with bucket_name
# Set the bucket's labels to the labels dictionary
# Create the bucket using storage_client.create_bucket
# Your code here

Need a hint?

Create a bucket object, assign labels, then call create_bucket with it.