Monitoring with Atlas metrics in MongoDB - Step-by-Step Execution

Concept Flow - Monitoring with Atlas metrics

Enable Atlas Monitoring

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Collect Metrics from Cluster

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Store Metrics in Atlas

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Visualize Metrics on Dashboard

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Set Alerts Based on Thresholds

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Respond to Alerts or Analyze Trends

This flow shows how Atlas collects, stores, and displays metrics for monitoring your MongoDB cluster, enabling alerting and analysis.

Execution Sample

MongoDB

db.adminCommand({ getFreeMonitoringStatus: 1 })
// Check if monitoring is enabled

// View metrics in Atlas UI dashboard

// Set alert thresholds in Atlas console

This sequence checks monitoring status, then uses Atlas UI to view metrics and configure alerts.

Execution Table

Step	Action	Command/Operation	Result/Output
1	Check monitoring status	db.adminCommand({ getFreeMonitoringStatus: 1 })	{"state": "enabled"}
2	Atlas collects metrics	Automatic background process	Metrics like CPU, memory, ops/sec collected
3	Store metrics	Atlas backend	Metrics stored securely and updated every minute
4	Visualize metrics	Atlas UI dashboard	Graphs show cluster health and performance
5	Set alert	Configure alert for CPU > 80%	Alert rule saved in Atlas
6	Trigger alert	CPU usage spikes above 80%	Alert notification sent to user
7	Respond to alert	User investigates issue	Issue diagnosed and resolved
8	Exit	Monitoring continues	Continuous data collection and alerting

💡 Monitoring runs continuously; this trace shows one alert cycle.

Variable Tracker

Variable	Start	After Step 1	After Step 4	After Step 6	Final
Monitoring Status	unknown	enabled	enabled	enabled	enabled
CPU Usage (%)	N/A	N/A	45	85	70
Alert Triggered	false	false	false	true	false

Key Moments - 3 Insights

Why does the monitoring status need to be checked first?

Checking monitoring status (Step 1) confirms if Atlas is collecting metrics; without it enabled, no data appears on the dashboard.

How does Atlas know when to send an alert?

Atlas compares live metrics against alert thresholds (Step 5). When CPU usage exceeds 80% (Step 6), it triggers an alert notification.

Does monitoring stop after an alert is sent?

No, monitoring runs continuously (Step 8). Alerts notify issues but data collection and visualization keep going.

Visual Quiz - 3 Questions

Look at the execution table, what is the monitoring status after Step 1?

A "unknown"

B "enabled"

C "disabled"

D "pending"

💡 Hint

Check the 'Result/Output' column in Step 1 of the execution table.

At which step does the alert get triggered due to high CPU usage?

A Step 4

B Step 5

C Step 6

D Step 7

💡 Hint

Look for the step mentioning CPU usage spikes above 80% in the execution table.

If the monitoring status was "disabled" at Step 1, what would happen to the metrics collection?

A Metrics would not be collected or displayed

B Metrics would still be collected normally

C Alerts would trigger regardless

D Only CPU metrics would be collected

💡 Hint

Refer to the key moment about why checking monitoring status is important.

Concept Snapshot

Monitoring with Atlas metrics:
- Enable monitoring via db.adminCommand
- Atlas collects and stores cluster metrics
- Metrics shown on Atlas dashboard
- Set alerts for thresholds (e.g., CPU > 80%)
- Alerts notify you to act
- Monitoring runs continuously

Full Transcript

Monitoring with Atlas metrics involves enabling monitoring on your MongoDB cluster, which allows Atlas to collect performance data like CPU usage and operations per second. This data is stored and visualized in the Atlas dashboard, where you can watch your cluster's health. You can set alert rules to notify you when metrics cross thresholds, such as CPU usage exceeding 80%. When an alert triggers, you receive a notification to investigate. Monitoring continues running in the background, collecting data and sending alerts as needed.