Cloud Monitoring overview in GCP - Mini Project: Build & Apply

Cloud Monitoring overview

📖 Scenario: You are managing a small web application running on Google Cloud Platform (GCP). You want to keep track of your application's health by monitoring CPU usage and uptime. This will help you quickly spot problems and keep your app running smoothly.

🎯 Goal: Build a simple Cloud Monitoring setup using Google Cloud SDK commands to create a monitored resource, configure an uptime check, and list the configured uptime checks.

📋 What You'll Learn

Use the gcloud command-line tool

Create a monitored resource descriptor for a virtual machine instance

Configure an uptime check for the web application

List all uptime checks to verify the setup

💡 Why This Matters

🌍 Real World

Cloud Monitoring helps keep applications healthy by automatically checking if they are up and running. This project shows how to set up basic uptime checks for your services.

💼 Career

Knowing how to configure and manage uptime checks is a key skill for cloud engineers and DevOps professionals to ensure system reliability and quick incident response.

1

Create a monitored resource descriptor

Use the gcloud monitoring resource-descriptors list command to list available monitored resource types. Then create a monitored resource descriptor for a virtual machine instance named my-instance in zone us-central1-a.

GCP

# Use gcloud to list resource descriptors and create a monitored resource for 'my-instance'
# Your code here

Hint

First, list resource descriptors with gcloud monitoring resource-descriptors list. Then define a dictionary with type as gce_instance and labels for instance_id and zone.

2

Configure an uptime check

Create a variable called uptime_check_config that defines an uptime check for the URL http://my-instance.example.com with a check interval of 60 seconds and timeout of 10 seconds.

GCP

# Create an uptime check configuration for 'http://my-instance.example.com'
uptime_check_config = {}
# Your code here

Hint

Define uptime_check_config as a dictionary with keys display_name, http_check, resource, period, and timeout. Use the monitored resource from Step 1.

3

Create the uptime check using gcloud

Use the gcloud monitoring uptime-checks create http command to create an uptime check for the URL http://my-instance.example.com with a check interval of 60 seconds and timeout of 10 seconds.

GCP

# Use gcloud to create the uptime check for 'http://my-instance.example.com'
# Your code here

Hint

Use the gcloud monitoring uptime-checks create http command with flags --display-name, --host, --path, --period, and --timeout.

4

List all uptime checks

Use the gcloud monitoring uptime-checks list command to display all configured uptime checks and verify that your uptime check named My Instance Uptime Check is listed.

GCP

# List all uptime checks to verify your setup
# Your code here

Hint

Run gcloud monitoring uptime-checks list to see all uptime checks. Look for the name My Instance Uptime Check in the output.

Practice

1. What is the main purpose of Cloud Monitoring in Google Cloud Platform?

easy

A. To watch and track the health and performance of cloud resources

B. To create virtual machines automatically

C. To store large amounts of data securely

D. To manage user permissions and roles

Solution

1. Step 1: Understand Cloud Monitoring's role

   Cloud Monitoring is designed to observe and report on the status and performance of cloud resources.

2. Step 2: Compare options with this role

   Options B, C, and D describe other services like Compute Engine, Cloud Storage, and IAM, not monitoring.

3. Final Answer:

   To watch and track the health and performance of cloud resources -> Option A

4. Quick Check:

   Cloud Monitoring = watch cloud health [OK]

Hint: Monitoring means watching resource health and performance [OK]

Common Mistakes:

• Confusing monitoring with storage or VM creation
• Thinking monitoring manages user access
• Assuming monitoring creates resources automatically

2. Which command correctly lists all alert policies using the gcloud tool?

easy

A. gcloud alert-policies show

B. gcloud monitoring alerts list

C. gcloud monitoring alert-policies list

D. gcloud monitoring policies get

Solution

1. Step 1: Recall gcloud command structure for alert policies

   The correct command to list alert policies is under 'monitoring alert-policies list'.

2. Step 2: Verify each option's correctness

   gcloud monitoring alert-policies list matches the correct syntax. Options A, B, and D use incorrect verbs or resource names.

3. Final Answer:

   gcloud monitoring alert-policies list -> Option C

4. Quick Check:

   List alert policies = gcloud monitoring alert-policies list [OK]

Hint: Use 'gcloud monitoring alert-policies list' to see alerts [OK]

Common Mistakes:

• Using 'alerts' instead of 'alert-policies'
• Using 'show' instead of 'list' to list policies
• Mixing command verbs and resource names

3. What will be the output of this command?

gcloud monitoring metrics list --filter="metric.type=compute.googleapis.com/instance/cpu/utilization" --limit=1

medium

A. Deletes the CPU utilization metric

B. Shows an error because the filter syntax is wrong

C. Lists all metrics without filtering

D. Lists one metric descriptor for CPU utilization of Compute Engine instances

Solution

1. Step 1: Understand the command components

   The command lists metric descriptors filtered by CPU utilization metric type, limiting output to one.

2. Step 2: Analyze expected output

   The output will show one metric descriptor matching the filter. No deletion or error occurs.

3. Final Answer:

   Lists one metric descriptor for CPU utilization of Compute Engine instances -> Option D

4. Quick Check:

   Filter + limit = one matching metric listed [OK]

Hint: Filter with --filter and limit results with --limit [OK]

Common Mistakes:

• Assuming filter syntax is invalid
• Expecting all metrics without filter
• Confusing list with delete command

4. You tried to create an alert policy with this command:

gcloud monitoring alert-policies create --notification-channels=1234567890 --condition-display-name="High CPU" --condition-filter="metric.type=compute.googleapis.com/instance/cpu/utilization" --condition-threshold-value=0.8

But it failed. What is the likely error?

medium

A. Missing required flag --condition-aggregations

B. Notification channel ID is invalid or missing

C. Condition filter syntax is incorrect

D. Threshold value must be a string, not a number

Solution

1. Step 1: Check notification channel usage

   The notification channel ID must be a valid existing channel; '1234567890' is likely a placeholder or invalid.

2. Step 2: Verify other flags

   Flags like condition filter and threshold value are syntactically correct; aggregation is optional.

3. Final Answer:

   Notification channel ID is invalid or missing -> Option B

4. Quick Check:

   Invalid notification channel causes failure [OK]

Hint: Check notification channel IDs exist before using [OK]

Common Mistakes:

• Assuming aggregation is always required
• Misformatting condition filter
• Using wrong data type for threshold

5. You want to create a dashboard that shows CPU utilization and memory usage for your Compute Engine instances. Which steps should you follow?

hard

A. Use Cloud Console to create a dashboard, add widgets for CPU and memory metrics, then save

B. Run gcloud commands to create a dashboard and add metrics in one command

C. Create alert policies for CPU and memory, then dashboards are created automatically

D. Use Cloud Storage to upload a JSON file with dashboard configuration

Solution

1. Step 1: Understand dashboard creation process

   Dashboards are created in Cloud Console by adding widgets for desired metrics.

2. Step 2: Evaluate options for dashboard creation

   Use Cloud Console to create a dashboard, add widgets for CPU and memory metrics, then save describes the correct manual process. Run gcloud commands to create a dashboard and add metrics in one command is incorrect as gcloud does not support full dashboard creation in one command. Create alert policies for CPU and memory, then dashboards are created automatically confuses alerts with dashboards. Use Cloud Storage to upload a JSON file with dashboard configuration misuses Cloud Storage.

3. Final Answer:

   Use Cloud Console to create a dashboard, add widgets for CPU and memory metrics, then save -> Option A

4. Quick Check:

   Dashboards made via Console with widgets [OK]

Hint: Create dashboards in Console by adding metric widgets [OK]

Common Mistakes:

• Thinking gcloud can create dashboards fully
• Confusing alert policies with dashboards
• Uploading dashboard configs to Cloud Storage