Operational excellence in GCP - Mini Project: Build & Apply

Operational Excellence with Google Cloud

📖 Scenario: You are working as a cloud engineer for a small company that wants to improve its cloud operations on Google Cloud Platform (GCP). The company wants to set up a simple monitoring and alerting system to ensure their application runs smoothly and any issues are quickly detected and resolved.

🎯 Goal: Build a basic Google Cloud Monitoring setup that includes a metric descriptor, an alerting policy, and a notification channel to achieve operational excellence by monitoring uptime and sending alerts.

📋 What You'll Learn

Create a custom metric descriptor for tracking application uptime

Configure a notification channel for email alerts

Set up an alerting policy that triggers when uptime drops below 99%

Use clear and exact resource names and values as specified

💡 Why This Matters

🌍 Real World

Monitoring uptime and setting alerts is critical for maintaining reliable cloud applications and quickly responding to issues.

💼 Career

Cloud engineers and DevOps professionals use monitoring and alerting to ensure operational excellence and meet service level objectives.

1

Create a custom metric descriptor for uptime

Create a variable called uptime_metric_descriptor that holds a dictionary with these exact keys and values: name set to "custom.googleapis.com/application/uptime", type set to "GAUGE", and description set to "Tracks application uptime percentage".

GCP

# Create the uptime_metric_descriptor dictionary with name, type, and description
# Your code here

Need a hint?

Use a Python dictionary with keys exactly as name, type, and description.

2

Configure an email notification channel

Create a variable called email_notification_channel that holds a dictionary with these exact keys and values: type set to "email", and email_address set to "[e-mail]".

GCP

uptime_metric_descriptor = {
    "name": "custom.googleapis.com/application/uptime",
    "type": "GAUGE",
    "description": "Tracks application uptime percentage"
}
# Create the email_notification_channel dictionary with type and email_address
# Your code here

Need a hint?

Use a dictionary with keys type and email_address exactly as shown.

3

Set up an alerting policy for uptime

Create a variable called alert_policy that holds a dictionary with these exact keys and values: display_name set to "Uptime Alert", condition set to a nested dictionary with metric equal to "custom.googleapis.com/application/uptime" and threshold equal to 99, and notification_channels set to a list containing the string "email_notification_channel".

GCP

uptime_metric_descriptor = {
    "name": "custom.googleapis.com/application/uptime",
    "type": "GAUGE",
    "description": "Tracks application uptime percentage"
}

email_notification_channel = {
    "type": "email",
    "email_address": "[e-mail]"
}
# Create the alert_policy dictionary with display_name, condition, and notification_channels
# Your code here

Need a hint?

Use nested dictionaries for condition and a list for notification_channels.

4

Complete the monitoring configuration

Add a variable called monitoring_configuration that holds a dictionary with these exact keys and values: metric_descriptor set to the variable uptime_metric_descriptor, notification_channel set to the variable email_notification_channel, and alert_policy set to the variable alert_policy.

GCP

uptime_metric_descriptor = {
    "name": "custom.googleapis.com/application/uptime",
    "type": "GAUGE",
    "description": "Tracks application uptime percentage"
}

email_notification_channel = {
    "type": "email",
    "email_address": "[e-mail]"
}

alert_policy = {
    "display_name": "Uptime Alert",
    "condition": {
        "metric": "custom.googleapis.com/application/uptime",
        "threshold": 99
    },
    "notification_channels": ["email_notification_channel"]
}
# Create the monitoring_configuration dictionary linking metric_descriptor, notification_channel, and alert_policy
# Your code here

Need a hint?

Combine the previous variables into one dictionary for the full monitoring setup.