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Monitoring and TroubleshootingmediumMultiple SelectObjective-mapped

DBS-C01 Monitoring and Troubleshooting Practice Question

A database administrator is troubleshooting a performance issue on an Amazon Aurora MySQL cluster. The application is experiencing high latency on write operations. Which TWO CloudWatch metrics should the administrator analyze to identify the root cause?

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

DMLThroughput

The correct metrics to analyze for high write latency are DMLThroughput and CommitLatency. DMLThroughput measures the rate of Data Manipulation Language operations, including INSERT, UPDATE, and DELETE, which are write-intensive. High DMLThroughput may indicate excessive write operations. CommitLatency measures the time taken to commit transactions; high commit latency directly contributes to write latency. The other options are not directly related to write performance.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ReadLatency

    Why it's wrong here

    ReadLatency measures the time for read operations, not relevant to write latency.

  • DMLThroughput

    Why this is correct

    DMLThroughput measures the rate of write operations (INSERT/UPDATE/DELETE) and helps identify if high throughput is causing contention.

  • CommitLatency

    Why this is correct

    CommitLatency measures the time to commit transactions, directly impacting write latency.

  • SelectLatency

    Why it's wrong here

    SelectLatency is a read metric, not relevant to write latency.

  • FreeableMemory

    Why it's wrong here

    FreeableMemory indicates available memory but is not a direct indicator of write latency.

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Last reviewed: Jun 20, 2026

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