Default vs custom metrics in AWS - Hands-On Comparison

Default vs Custom Metrics in AWS CloudWatch

📖 Scenario: You are managing a web application hosted on AWS. You want to monitor its performance using AWS CloudWatch metrics. AWS provides default metrics automatically, but you also want to create a custom metric to track the number of user sign-ups per hour.

🎯 Goal: Build an AWS CloudWatch setup that includes both default metrics for an EC2 instance and a custom metric for user sign-ups.

📋 What You'll Learn

Create a CloudWatch metric namespace called MyAppMetrics

Use the default CPU utilization metric for an EC2 instance

Create a custom metric called UserSignUps under the MyAppMetrics namespace

Set the custom metric value to 5 sign-ups

💡 Why This Matters

🌍 Real World

Monitoring cloud resources with both default and custom metrics helps keep applications healthy and responsive.

💼 Career

Cloud engineers and DevOps professionals often create and manage custom metrics alongside default ones to get detailed insights.

1

Create a CloudWatch metric namespace and default metric reference

Create a variable called namespace and set it to the string 'MyAppMetrics'. Then create a variable called default_metric and set it to the string 'CPUUtilization' which represents the default EC2 CPU metric.

AWS

# Your code here

Hint

Use simple string assignments for namespace and default_metric.

2

Define the custom metric name and value

Create a variable called custom_metric_name and set it to the string 'UserSignUps'. Then create a variable called custom_metric_value and set it to the integer 5 representing the number of sign-ups.

AWS

namespace = 'MyAppMetrics'
default_metric = 'CPUUtilization'
# Your code here

Hint

Assign the exact string and integer values to the variables.

3

Create a dictionary representing the custom metric data

Create a dictionary called custom_metric_data with keys 'Namespace', 'MetricName', and 'Value'. Set their values to the variables namespace, custom_metric_name, and custom_metric_value respectively.

AWS

namespace = 'MyAppMetrics'
default_metric = 'CPUUtilization'
custom_metric_name = 'UserSignUps'
custom_metric_value = 5
# Your code here

Hint

Use a dictionary with the exact keys and assign the variables as values.

4

Add the default metric to a list with the custom metric data

Create a list called metrics_to_monitor that contains two items: the string default_metric and the dictionary custom_metric_data.

AWS

namespace = 'MyAppMetrics'
default_metric = 'CPUUtilization'
custom_metric_name = 'UserSignUps'
custom_metric_value = 5
custom_metric_data = {'Namespace': namespace, 'MetricName': custom_metric_name, 'Value': custom_metric_value}
# Your code here

Hint

Create a list with the exact two items in order.

Practice

1. Which statement best describes AWS default metrics in CloudWatch?

easy

A. They are automatically collected and free within certain limits.

B. They require manual setup and extra charges.

C. They only track custom application data.

D. They are disabled by default and need activation.

Solution

1. Step 1: Understand default metrics collection

   AWS CloudWatch automatically collects default metrics for many services without extra setup.

2. Step 2: Recognize cost and availability

   These default metrics are free within certain usage limits, making them easy to use.

3. Final Answer:

   They are automatically collected and free within certain limits. -> Option A

4. Quick Check:

   Default metrics = automatic + free [OK]

Hint: Default metrics are automatic and free within limits [OK]

Common Mistakes:

• Thinking default metrics need manual setup
• Assuming default metrics track custom data
• Believing default metrics are disabled by default

2. Which of the following is the correct way to send a custom metric to AWS CloudWatch using the AWS CLI?

easy

A. aws cloudwatch send-metric --name CPUUtilization --value 70

B. aws cloudwatch add-metric-data --metric-name CPUUtilization --value 70

C. aws cloudwatch create-metric --metric CPUUtilization --value 70

D. aws cloudwatch put-metric-data --metric-name CPUUtilization --namespace AWS/EC2 --value 70

Solution

1. Step 1: Identify the correct AWS CLI command

   The correct command to send custom metric data is put-metric-data under aws cloudwatch.

2. Step 2: Check the syntax and parameters

   The command requires --metric-name, --namespace, and --value parameters as shown in aws cloudwatch put-metric-data --metric-name CPUUtilization --namespace AWS/EC2 --value 70.

3. Final Answer:

   aws cloudwatch put-metric-data --metric-name CPUUtilization --namespace AWS/EC2 --value 70 -> Option D

4. Quick Check:

   Use put-metric-data with metric-name and namespace [OK]

Hint: Use 'put-metric-data' with metric-name and namespace [OK]

Common Mistakes:

• Using incorrect command names like send-metric or create-metric
• Omitting the namespace parameter
• Confusing metric creation with data sending

3. Given the following AWS CloudWatch custom metric data sent every minute:

aws cloudwatch put-metric-data --metric-name PageViews --namespace MyApp --value 5

What will be the average value shown in CloudWatch after 3 minutes if the command is run 3 times with values 5, 7, and 8 respectively?

medium

A. 6.67

B. 7

C. 20

D. 5

Solution

1. Step 1: Sum the metric values sent

   The values sent are 5, 7, and 8. Their sum is 5 + 7 + 8 = 20.

2. Step 2: Calculate the average over 3 data points

   Average = Total sum / Number of data points = 20 / 3 ≈ 6.67.

3. Final Answer:

   6.67 -> Option A

4. Quick Check:

   Average = sum/3 = 6.67 [OK]

Hint: Average = sum of values divided by count [OK]

Common Mistakes:

• Adding values but not dividing by count
• Taking the last value as average
• Multiplying values instead of averaging

4. You tried to send a custom metric to CloudWatch but it does not appear in the console. Which of the following is the most likely cause?

medium

A. CloudWatch only shows metrics after 24 hours delay.

B. You forgot to specify the metric namespace in the command.

C. Custom metrics are automatically visible without sending data.

D. Default metrics do not require namespaces, so this is normal.

Solution

1. Step 1: Check required parameters for custom metrics

   Custom metrics require a namespace to organize and display them properly in CloudWatch.

2. Step 2: Understand impact of missing namespace

   If the namespace is missing, CloudWatch cannot categorize the metric, so it won't appear in the console.

3. Final Answer:

   You forgot to specify the metric namespace in the command. -> Option B

4. Quick Check:

   Missing namespace hides custom metric [OK]

Hint: Always specify namespace when sending custom metrics [OK]

Common Mistakes:

• Assuming default metrics need namespaces
• Expecting immediate visibility without data sent
• Believing CloudWatch delays metric display by 24 hours

5. You want to monitor a custom application metric that tracks the number of user logins per hour. The default AWS metrics do not provide this data. What is the best approach to achieve this?

hard

A. Enable detailed monitoring on EC2 instances to get user login data.

B. Use the default CPUUtilization metric to estimate user logins.

C. Send custom metric data for user logins to CloudWatch using a unique namespace and metric name.

D. Create an alarm on default network metrics to infer user logins.

Solution

1. Step 1: Identify the need for custom data

   User logins per hour is specific to the application and not tracked by default AWS metrics.

2. Step 2: Use custom metrics for application-specific data

   Sending custom metric data with a unique namespace and metric name allows tracking exactly this information in CloudWatch.

3. Final Answer:

   Send custom metric data for user logins to CloudWatch using a unique namespace and metric name. -> Option C

4. Quick Check:

   Custom metrics track app-specific data [OK]

Hint: Use custom metrics for app-specific tracking [OK]

Common Mistakes:

• Trying to use unrelated default metrics for app data
• Assuming detailed monitoring tracks application events
• Using alarms on unrelated metrics to guess user activity