Cost optimization strategies in GCP - Mini Project: Build & Apply

Cost Optimization Strategies in GCP

📖 Scenario: You are managing cloud resources for a small company using Google Cloud Platform (GCP). The company wants to reduce its monthly cloud costs without affecting the performance of its applications.

🎯 Goal: Build a simple GCP resource configuration that demonstrates cost optimization by selecting appropriate machine types, setting up budget alerts, and enabling autoscaling.

📋 What You'll Learn

Create a dictionary named instances with three VM instances and their machine types

Add a variable named budget_limit set to 500 (representing $500 monthly budget)

Write a loop to create a list optimized_instances that includes only instances with machine types costing less than or equal to 2 vCPUs

Add a final configuration dictionary autoscaling_config with keys enabled set to true and max_instances set to 5

💡 Why This Matters

🌍 Real World

Cloud engineers often need to optimize resource usage and costs by selecting appropriate machine types, setting budgets, and enabling autoscaling.

💼 Career

Understanding cost optimization strategies in GCP is essential for roles like Cloud Engineer, DevOps Engineer, and Cloud Architect.

1

Create VM instances with machine types

Create a dictionary called instances with these exact entries: 'vm1': 'n1-standard-1', 'vm2': 'n1-standard-4', 'vm3': 'e2-medium'.

GCP

# Create the instances dictionary with specified VM names and machine types
# Your code here

Need a hint?

Use a Python dictionary with VM names as keys and machine types as values.

2

Set the monthly budget limit

Add a variable called budget_limit and set it to 500 representing the monthly budget in dollars.

GCP

instances = {'vm1': 'n1-standard-1', 'vm2': 'n1-standard-4', 'vm3': 'e2-medium'}
# Set the budget_limit variable to 500
# Your code here

Need a hint?

Just assign the number 500 to the variable budget_limit.

3

Filter instances by machine type vCPU count

Create a list called optimized_instances that includes only the instance names from instances whose machine types have 2 or fewer vCPUs. Use a for loop with variables vm and machine to iterate over instances.items(). Use this vCPU mapping: 'n1-standard-1': 1, 'n1-standard-4': 4, 'e2-medium': 2.

GCP

instances = {'vm1': 'n1-standard-1', 'vm2': 'n1-standard-4', 'vm3': 'e2-medium'}
budget_limit = 500
# Create optimized_instances list filtering by vCPU count <= 2
# Your code here

Need a hint?

Use a dictionary for vCPU counts and a for loop to filter instance names.

4

Add autoscaling configuration

Add a dictionary called autoscaling_config with keys enabled set to true and max_instances set to 5.

GCP

instances = {'vm1': 'n1-standard-1', 'vm2': 'n1-standard-4', 'vm3': 'e2-medium'}
budget_limit = 500
vcpu_map = {'n1-standard-1': 1, 'n1-standard-4': 4, 'e2-medium': 2}
optimized_instances = []
for vm, machine in instances.items():
    if vcpu_map[machine] <= 2:
        optimized_instances.append(vm)
# Add autoscaling_config dictionary with enabled=true and max_instances=5
# Your code here

Need a hint?

Create a dictionary with the specified keys and values.