DOP-C02 Monitoring and Logging Practice Question
A company is using Amazon RDS for MySQL and wants to monitor database connections. They need to set up an alarm when the number of connections exceeds 80% of the maximum connections for more than 5 minutes. Which CloudWatch metric and statistic should be used?
⚠ Common exam trap
Test-takers frequently choose Maximum because they think it is the most conservative for detecting high usage, but they overlook that the requirement is for sustained breaches over 5 minutes, not instantaneous spikes, making Average the correct choice for avoiding false alarms.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
DatabaseConnections metric with Average statistic
The Average statistic of the DatabaseConnections metric over a 5-minute period provides a smoothed representation of connection usage, which is appropriate for detecting sustained breaches of the 80% threshold. Using Average reduces sensitivity to transient spikes, ensuring the alarm triggers only when the average number of connections remains above the threshold for the entire evaluation period, aligning with the requirement of 'more than 5 minutes'.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
DatabaseConnections metric with Maximum statistic
Why it's wrong here
The Maximum statistic reports the single highest DatabaseConnections sample within the 5-minute period. That value can be driven by a brief, momentary spike (for example, a short-lived connection burst) and does not indicate whether connections stayed near the 80% ceiling for a sustained duration. Because the alarm requirement is to detect more than 5 minutes of sustained high usage, using Maximum would produce false positives from transient load and fail to isolate persistent behaviour.
- ✓
DatabaseConnections metric with Average statistic
Why this is correct
The Average statistic computes the mean DatabaseConnections over the 5-minute interval, which inherently dampens short-lived fluctuations and reveals the central tendency of connection concurrency. If the average exceeds the 80% threshold, it means the typical number of connections during the entire window was too high, matching the criterion of sustained usage for more than 5 minutes. This is the most appropriate aggregation for a threshold alarm aimed at detecting prolonged saturation of the connection pool.
- ✗
DatabaseConnections metric with Sum and then divide by the number of data points
Why it's wrong here
Using the Sum statistic and dividing by the number of data points yields an average over the period, not the peak connection count. The requirement is to detect when connections exceed 80% of the maximum for more than 5 minutes, which requires the Maximum statistic to capture the highest value within each period. This option is tempting because Sum divided by data points calculates a mean, which is useful for smoothing bursty metrics to assess overall utilisation, such as average CPU over an hour.
- ✗
DatabaseConnections metric with Sum statistic
Why it's wrong here
The Sum statistic aggregates individual sample values into a cumulative total, yielding a number that scales with the number of monitoring data points and the sample interval. Such a cumulative total has no meaningful relationship to the MySQL max_connections limit, making it impossible to compare against an 80% utilisation threshold. Even if you divided by the number of points to obtain an average, that calculation would be redundant with the Average statistic and would still not convey peak concurrency; thus Sum is inherently unsuitable for connection-count monitoring.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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