Monitoring with Atlas metrics in MongoDB - Mini Project: Build & Apply

Monitoring with Atlas metrics

📖 Scenario: You are managing a MongoDB database hosted on Atlas. You want to monitor the database's performance by collecting key metrics such as CPU usage, memory usage, and operation counts.This helps you keep your database healthy and respond quickly if something goes wrong.

🎯 Goal: Build a simple Python script to filter and display sample Atlas monitoring metrics for CPU usage, memory usage, and operation counts above a threshold.

📋 What You'll Learn

Create a variable called metrics with sample Atlas metrics data as a list of dictionaries.

Create a variable called threshold set to 70 to represent a usage alert level.

Use a for loop with variables metric to iterate over metrics and select only those metrics where metric['value'] is greater than threshold.

Print the filtered list of high usage metrics.

💡 Why This Matters

🌍 Real World

Monitoring database performance is crucial to avoid downtime and ensure smooth user experience. Atlas metrics help track resource usage and operation counts.

💼 Career

DevOps engineers and database administrators use monitoring scripts like this to maintain healthy cloud databases and respond quickly to issues.

1

Create sample Atlas metrics data

Create a variable called metrics and assign it a list of dictionaries with these exact entries: {'name': 'cpuUsage', 'value': 65}, {'name': 'memoryUsage', 'value': 75}, {'name': 'operationCount', 'value': 50}.

MongoDB

# Create the metrics list with sample data
# Your code here

Need a hint?

Think of metrics as a list holding small boxes (dictionaries), each with a name and a value.

2

Set the alert threshold

Create a variable called threshold and set it to the integer 70.

MongoDB

metrics = [
    {'name': 'cpuUsage', 'value': 65},
    {'name': 'memoryUsage', 'value': 75},
    {'name': 'operationCount', 'value': 50}
]
# Set the threshold value
# Your code here

Need a hint?

The threshold is a number that tells us when usage is too high.

3

Filter metrics above the threshold

Create an empty list called high_usage_metrics. Use a for loop with variable metric to iterate over metrics. Inside the loop, use an if statement to check if metric['value'] is greater than threshold. If yes, append metric to high_usage_metrics.

MongoDB

metrics = [
    {'name': 'cpuUsage', 'value': 65},
    {'name': 'memoryUsage', 'value': 75},
    {'name': 'operationCount', 'value': 50}
]
threshold = 70

# Filter metrics above threshold
# Your code here

Need a hint?

Think of checking each metric's value and collecting only those that are too high.

4

Display the high usage metrics

Write a print statement to display the variable high_usage_metrics.

MongoDB

metrics = [
    {'name': 'cpuUsage', 'value': 65},
    {'name': 'memoryUsage', 'value': 75},
    {'name': 'operationCount', 'value': 50}
]
threshold = 70

high_usage_metrics = []
for metric in metrics:
    if metric['value'] > threshold:
        high_usage_metrics.append(metric)

# Print the high usage metrics
# Your code here

Need a hint?

The output should show only the metrics with values above 70.