Why managed Kubernetes matters in GCP - See It in Action

Why Managed Kubernetes Matters

📖 Scenario: You are working in a small company that wants to deploy applications on the cloud. You have heard about Kubernetes but find it complex to manage. Your team is considering using a managed Kubernetes service on Google Cloud Platform (GCP) to simplify deployment and maintenance.

🎯 Goal: Learn why using a managed Kubernetes service like Google Kubernetes Engine (GKE) is helpful. You will create a simple data structure to represent Kubernetes clusters, add configuration for managed services, filter clusters that are managed, and display the benefits.

📋 What You'll Learn

Create a dictionary with Kubernetes clusters and their types

Add a variable to identify managed clusters

Use a loop to find all managed clusters

Print the list of managed clusters

💡 Why This Matters

🌍 Real World

Companies use managed Kubernetes services like GKE to avoid the complexity of setting up and maintaining Kubernetes themselves. This saves time and reduces errors.

💼 Career

Understanding why managed Kubernetes matters helps you communicate with cloud teams and supports decisions about infrastructure management in DevOps roles.

1

Create Kubernetes clusters dictionary

Create a dictionary called clusters with these exact entries: 'cluster1': 'self-managed', 'cluster2': 'managed', 'cluster3': 'self-managed', 'cluster4': 'managed'.

GCP

# Create the clusters dictionary with exact entries
# Your code here

Need a hint?

Use curly braces to create a dictionary with keys as cluster names and values as their types.

2

Add managed cluster type variable

Create a variable called managed_type and set it to the string 'managed'.

GCP

clusters = {
    'cluster1': 'self-managed',
    'cluster2': 'managed',
    'cluster3': 'self-managed',
    'cluster4': 'managed'
}
# Create the managed_type variable
# Your code here

Need a hint?

Assign the string 'managed' to the variable managed_type.

3

Find all managed clusters

Create a list called managed_clusters that contains the names of clusters from clusters where the cluster type equals managed_type. Use a for loop with variables cluster and ctype to iterate over clusters.items().

GCP

clusters = {
    'cluster1': 'self-managed',
    'cluster2': 'managed',
    'cluster3': 'self-managed',
    'cluster4': 'managed'
}
managed_type = 'managed'
# Create managed_clusters list using a for loop
# Your code here

Need a hint?

Use a loop to check each cluster's type and add the cluster name to the list if it is managed.

4

Display managed clusters

Write a print statement to display the text 'Managed Kubernetes clusters:' followed by the managed_clusters list.

GCP

clusters = {
    'cluster1': 'self-managed',
    'cluster2': 'managed',
    'cluster3': 'self-managed',
    'cluster4': 'managed'
}
managed_type = 'managed'
managed_clusters = []
for cluster, ctype in clusters.items():
    if ctype == managed_type:
        managed_clusters.append(cluster)
# Print the managed clusters
# Your code here

Need a hint?

Use print('Managed Kubernetes clusters:', managed_clusters) to show the result.