Monitoring with Atlas metrics in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

💻 Command Output

intermediate

Understanding Atlas Metrics Query Output

You run the following Atlas API command to fetch CPU usage metrics for your cluster over the last hour:

curl -X GET 'https://cloud.mongodb.com/api/atlas/v1.0/groups/{GROUP-ID}/processes/{HOST}:{PORT}/measurements?granularity=PT1M&period=PT1H&metrics=CPU_USER'

What type of data will the response contain?

A A JSON object containing only the cluster name and status without metrics.

B A JSON object with timestamped CPU usage percentages sampled every minute for the last hour.

C An error message indicating invalid API endpoint.

D A plain text list of CPU usage values without timestamps.

💡 Hint

Think about what 'measurements' and 'granularity' parameters imply in the API call.

The Atlas API returns metrics data as JSON with timestamps and values. The granularity=PT1M means data points every minute, and period=PT1H means last hour.

🧠 Conceptual

intermediate

Choosing Metrics for Performance Monitoring

Which Atlas metric is best to monitor if you want to detect slow query performance caused by disk I/O bottlenecks?

A DISK_QUEUE_DEPTH

B CONNECTIONS_CURRENT

C NETWORK_BYTES_IN

D OPCOUNTERS_COMMAND

💡 Hint

Disk queue depth indicates how many operations are waiting for disk access.

DISK_QUEUE_DEPTH shows how many disk operations are waiting, which directly relates to disk I/O bottlenecks affecting query speed.

❓ Troubleshoot

advanced

Diagnosing Missing Metrics in Atlas Dashboard

You notice that your Atlas cluster dashboard is not showing any data for the 'MEMORY_RESIDENT' metric for the past day. What is the most likely cause?

A Your API key lacks permissions to view memory metrics.

B The MEMORY_RESIDENT metric is deprecated and no longer available.

C The cluster is paused or stopped, so no metrics are collected.

D The Atlas UI has a bug and needs a browser refresh.

💡 Hint

Think about what happens to metrics collection when the cluster is not running.

If the cluster is paused or stopped, Atlas cannot collect or report metrics, so the dashboard will show no data.

🔀 Workflow

advanced

Setting Up Alerts for High CPU Usage

You want to create an alert in Atlas that triggers when CPU usage exceeds 80% for more than 5 minutes. Which steps correctly describe this setup?

A Enable cluster auto-scaling to automatically reduce CPU usage above 80%.

B Modify the cluster configuration to limit CPU usage to 80%.

C Set up a backup schedule to run when CPU usage is above 80%.

D Create an alert configuration with metric CPU_USER, threshold 80%, duration 5 minutes, and notification channel.

💡 Hint

Alerts are based on metric thresholds and notification settings.

Atlas alerts are configured by selecting a metric, setting a threshold and duration, and linking to notification channels like email or Slack.

✅ Best Practice

expert

Optimizing Atlas Monitoring Costs

To reduce costs while maintaining effective monitoring in Atlas, which practice is recommended?

A Adjust metric granularity to a coarser level like 5 minutes instead of 1 minute for less frequent data points.

B Disable all metrics except CPU usage to minimize data collection.

C Increase the retention period of metrics to keep data longer for analysis.

D Run multiple monitoring agents on the same cluster to ensure data accuracy.

💡 Hint

Less frequent data points reduce storage and processing costs.

Using coarser granularity reduces the number of data points collected and stored, lowering monitoring costs without losing essential trend information.

Practice

1. What is the main purpose of monitoring MongoDB Atlas metrics?

easy

A. To track database health and performance

B. To write database queries faster

C. To create new database users

D. To backup data manually

Solution

1. Step 1: Understand the role of monitoring

   Monitoring helps watch how well the database is working and if there are any problems.

2. Step 2: Identify the purpose of Atlas metrics

   Atlas metrics provide data about database health and performance to keep it running smoothly.

3. Final Answer:

   To track database health and performance -> Option A

4. Quick Check:

   Monitoring = Track health and performance [OK]

Hint: Monitoring means watching health and speed [OK]

Common Mistakes:

• Confusing monitoring with query writing
• Thinking monitoring creates users
• Assuming monitoring is for manual backups

2. Which of the following is the correct way to access Atlas metrics via the API?

easy

A. GET /api/atlas/v1.0/groups/{GROUP-ID}/processes/{PROCESS-ID}/measurements

B. POST /api/atlas/v1.0/groups/{GROUP-ID}/processes/{PROCESS-ID}/measurements

C. DELETE /api/atlas/v1.0/groups/{GROUP-ID}/processes/{PROCESS-ID}/measurements

D. PUT /api/atlas/v1.0/groups/{GROUP-ID}/processes/{PROCESS-ID}/measurements

Solution

1. Step 1: Identify the HTTP method for fetching data

   To get metrics, we use the GET method because it retrieves information.

2. Step 2: Confirm the API endpoint format

   The endpoint includes group and process IDs and ends with /measurements to fetch metrics.

3. Final Answer:

   GET /api/atlas/v1.0/groups/{GROUP-ID}/processes/{PROCESS-ID}/measurements -> Option A

4. Quick Check:

   GET method fetches data [OK]

Hint: GET method reads data from API [OK]

Common Mistakes:

• Using POST instead of GET to fetch data
• Confusing DELETE or PUT with data retrieval
• Missing required path parameters

3. Given this API call to Atlas metrics:

curl -X GET \
'https://cloud.mongodb.com/api/atlas/v1.0/groups/12345/processes/cluster0-shard-00-00/measurements?granularity=PT1M&metricNames=CPU_USER'

What does the response mainly contain?

medium

A. A list of database users created in the last minute

B. A list of error logs from the last minute

C. A list of backup snapshots taken every minute

D. A list of CPU user usage values sampled every minute

Solution

1. Step 1: Analyze the API parameters

   The metricNames=CPU_USER means it requests CPU usage by user processes.

2. Step 2: Understand granularity=PT1M

   This means data is sampled every 1 minute (PT1M is ISO 8601 duration for 1 minute).

3. Final Answer:

   A list of CPU user usage values sampled every minute -> Option D

4. Quick Check:

   CPU_USER metric with 1-minute samples = CPU usage data [OK]

Hint: metricNames shows what data is returned [OK]

Common Mistakes:

• Thinking it returns user accounts
• Confusing metrics with backups
• Assuming error logs are returned

4. You run this API call but get a 400 Bad Request error:

curl -X GET \
'https://cloud.mongodb.com/api/atlas/v1.0/groups/12345/processes/cluster0-shard-00-00/measurements?granularity=1m&metricNames=CPU_USER'

What is the likely cause?

medium

A. Missing API key in the request headers

B. Incorrect granularity format; should be ISO 8601 duration like PT1M

C. Wrong HTTP method; should be POST instead of GET

D. Invalid process ID format

Solution

1. Step 1: Check the granularity parameter format

   The API expects granularity in ISO 8601 duration format, e.g., PT1M for 1 minute.

2. Step 2: Identify the error cause

   Using '1m' instead of 'PT1M' causes the 400 Bad Request error due to invalid parameter format.

3. Final Answer:

   Incorrect granularity format; should be ISO 8601 duration like PT1M -> Option B

4. Quick Check:

   Granularity format must be ISO 8601 [OK]

Hint: Use PT1M, not 1m, for granularity [OK]

Common Mistakes:

• Using shorthand time like '1m' instead of 'PT1M'
• Forgetting API key causes 401, not 400
• Using wrong HTTP method causes 405, not 400

5. You want to monitor both CPU and memory usage for your MongoDB cluster every 5 minutes using Atlas API. Which query parameter setup is correct?

hard

A. metricNames=CPU_USER,MEMORY_USAGE&granularity=5minutes

B. metricNames=CPU_USER;MEMORY_USAGE&granularity=5m

C. metricNames=CPU_USER,MEMORY_USAGE&granularity=PT5M

D. metricNames=CPU_USER+MEMORY_USAGE&granularity=PT5M

Solution

1. Step 1: Understand metricNames format

   Multiple metrics are separated by commas, so 'CPU_USER,MEMORY_USAGE' is correct.

2. Step 2: Use correct granularity format

   Granularity must be ISO 8601 duration, so 'PT5M' means 5 minutes.

3. Final Answer:

   metricNames=CPU_USER,MEMORY_USAGE&granularity=PT5M -> Option C

4. Quick Check:

   Comma separates metrics; PT5M means 5 minutes [OK]

Hint: Use commas for metrics and PT5M for 5 minutes [OK]

Common Mistakes:

• Using semicolons or plus signs instead of commas
• Using '5m' or '5minutes' instead of PT5M
• Mixing wrong separators and time formats