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PCDE Practice Question: Manage a solution that can span multiple database technologies

A company uses Cloud Bigtable to store session data. They need to monitor replication lag between clusters in different zones. Which metric should they use?

⚠ Common exam trap

Google Cloud often tests the distinction between metrics that measure performance (like CPU load) versus metrics that measure data freshness (like replication lag), and candidates may confuse Key Visualizer's diagnostic capabilities with real-time monitoring metrics.

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

Instance-level 'replication_lag' metric.

Cloud Bigtable exposes an instance-level 'replication_lag' metric that measures the time delay (in seconds) between clusters in a replicated instance. This metric directly reflects how far behind a replica cluster is relative to the primary cluster, making it the appropriate choice for monitoring replication lag between zones.

Answer analysis

Option-by-option breakdown

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

  • Instance-level 'replication_lag' metric.

    Why this is correct

    Correct. Replication lag is measured in seconds and available in Cloud Monitoring.

  • Cluster-level 'cpu_load' metric.

    Why it's wrong here

    CPU load is not a direct measure of replication lag.

  • Use Key Visualizer to identify replication delays.

    Why it's wrong here

    Key Visualizer identifies hot spots, not replication lag.

  • Table-level 'rows_returned' metric.

    Why it's wrong here

    Rows returned is about query volume, not replication.

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Last reviewed: Jul 4, 2026

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