Metrics and dashboards in GCP - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a metric in Google Cloud Monitoring?

A metric is a time series data that measures a specific aspect of your cloud resources or applications, like CPU usage or request count.

beginner

What is the purpose of a dashboard in Google Cloud Monitoring?

A dashboard visually displays metrics and logs in charts and widgets to help you understand the health and performance of your cloud resources at a glance.

intermediate

How can you create a custom dashboard in Google Cloud Monitoring?

You can create a custom dashboard by selecting metrics, choosing chart types, and arranging widgets to monitor specific resources or applications.

intermediate

What is an alerting policy in Google Cloud Monitoring?

An alerting policy watches metrics and sends notifications when certain conditions, like thresholds, are met to help you respond quickly to issues.

beginner

Why is it important to monitor metrics regularly?

Regular monitoring helps detect problems early, understand system behavior, and improve performance and reliability of your cloud services.

What does a metric represent in Google Cloud Monitoring?

A A user account permission

B A static configuration setting

C A billing invoice

D A measurement of resource or application performance over time

Metrics are measurements collected over time to track performance or usage.

Which of the following is NOT a feature of dashboards in Google Cloud Monitoring?

A Visualizing metrics with charts

B Sending email alerts automatically

C Customizing layout with widgets

D Monitoring multiple resources in one view

Dashboards display data visually but do not send alerts; alerting policies handle notifications.

What is required to create an alerting policy?

A Set up a virtual machine

B Create a billing account

C Define a metric condition and notification channel

D Install monitoring agents manually

Alerting policies need a metric condition to watch and a notification channel to send alerts.

Which Google Cloud service provides metrics and dashboards?

A Cloud Monitoring

B Cloud Storage

C Cloud Functions

D Cloud SQL

Cloud Monitoring is the service for metrics, dashboards, and alerting.

Why should you use custom dashboards?

A To focus on metrics important to your specific applications

B To disable monitoring

C To increase billing costs

D To delete all metrics

Custom dashboards let you organize and view the metrics that matter most to your needs.

Explain how metrics and dashboards work together in Google Cloud Monitoring.

Think about how data is collected and then shown to users.

Describe the steps to create an alerting policy based on a metric threshold.

Focus on what you watch, when to alert, and how to notify.

Practice

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

easy

A. To visually display metrics and help monitor cloud resources

B. To store data permanently for backup

C. To write code for cloud functions

D. To manage user permissions

Solution

1. Step 1: Understand what dashboards do

   Dashboards show visual summaries of metrics to help users watch cloud resources easily.

2. Step 2: Identify the correct purpose

   Among the options, only displaying metrics visually matches the dashboard's role.

3. Final Answer:

   To visually display metrics and help monitor cloud resources -> Option A

4. Quick Check:

   Dashboard = Visual metric display [OK]

Hint: Dashboards show data visually, not store or code [OK]

Common Mistakes:

• Confusing dashboards with storage or coding tools
• Thinking dashboards manage permissions

2. Which of the following is the correct way to filter CPU usage metric in a Google Cloud Monitoring dashboard widget?

easy

A. filter: cpu_usage_metric

B. metric = "cpu_usage"

C. metric.type = "compute.googleapis.com/instance/cpu/utilization"

D. metric.cpu = "usage"

Solution

1. Step 1: Recall correct metric filter syntax

   Google Cloud Monitoring uses metric.type with full metric names like "compute.googleapis.com/instance/cpu/utilization".

2. Step 2: Match options to syntax

   Only metric.type = "compute.googleapis.com/instance/cpu/utilization" uses the correct full metric.type format.

3. Final Answer:

   metric.type = "compute.googleapis.com/instance/cpu/utilization" -> Option C

4. Quick Check:

   Correct metric filter uses metric.type with full name [OK]

Hint: Use full metric.type path for filters [OK]

Common Mistakes:

• Using incomplete or shorthand metric names
• Wrong filter keywords like 'filter:' or 'metric.cpu'

3. Given this snippet for a dashboard widget filter:
metric.type = "compute.googleapis.com/instance/disk/read_bytes_count" AND resource.label.instance_id = "12345"
What does this filter show?

medium

A. Disk read bytes count for instance with ID 12345

B. CPU usage for instance 12345

C. Network bytes sent by instance 12345

D. Disk write bytes count for instance 12345

Solution

1. Step 1: Analyze metric.type value

   The metric is "disk/read_bytes_count", which means bytes read from disk.

2. Step 2: Check resource label filter

   The filter limits data to instance with ID "12345".

3. Final Answer:

   Disk read bytes count for instance with ID 12345 -> Option A

4. Quick Check:

   Disk read bytes + instance filter = Disk read bytes count for instance with ID 12345 [OK]

Hint: Match metric.type and resource label to understand filter [OK]

Common Mistakes:

• Confusing read bytes with write bytes
• Mixing disk metrics with CPU or network

4. You created a dashboard widget but it shows no data. Which of these is the most likely cause?

medium

A. The user has read access to the project

B. The dashboard widget is set to refresh every 5 seconds

C. The dashboard has more than 5 widgets

D. The metric filter uses an incorrect metric type name

Solution

1. Step 1: Identify common reasons for no data

   Incorrect metric type names cause filters to match no data, so widget shows empty.

2. Step 2: Evaluate other options

   Refresh rate or widget count do not prevent data display; read access is needed but assumed correct here.

3. Final Answer:

   The metric filter uses an incorrect metric type name -> Option D

4. Quick Check:

   No data usually means wrong metric filter [OK]

Hint: Check metric type spelling if no data shows [OK]

Common Mistakes:

• Blaming refresh rate or widget count
• Ignoring permission issues but assuming access is correct

5. You want to create a dashboard showing both CPU utilization and network bytes sent for multiple instances, but only for instances tagged with "env:production". Which approach is best?

hard

A. Create a widget with a filter for "env:production" but only for disk metrics

B. Create two widgets with filters for CPU and network metrics, each filtering resource labels for "env:production"

C. Create a widget filtering only CPU metrics for all instances, ignoring network metrics

D. Create one widget showing CPU and network metrics without filters, then manually check instance tags

Solution

1. Step 1: Understand the requirement

   You need to show two different metrics (CPU and network) filtered by instance tag "env:production".

2. Step 2: Choose filtering and widget setup

   Best practice is separate widgets for each metric with proper filters on resource labels for the tag.

3. Step 3: Evaluate other options

   Options A, B, and C either miss filtering, use wrong metrics, or ignore one of the required metrics.

4. Final Answer:

   Create two widgets with filters for CPU and network metrics, each filtering resource labels for "env:production" -> Option B

5. Quick Check:

   Separate widgets + correct filters = best dashboard [OK]

Hint: Use separate widgets with filters for each metric [OK]

Common Mistakes:

• Trying to combine unrelated metrics in one widget without filters
• Ignoring resource label filters for tags
• Showing irrelevant metrics