How Can You Confirm PostgreSQL Is Causing DMS CDC Latency?

DEA-C01 By islever Editorial Last updated Oct 20, 2026

Maintain and monitor data pipelines. Perform data ingestion.

Short answer

D Monitor the DMS task's CDCLatencySource metric in Amazon CloudWatch to confirm whether delays originate while reading changes from the PostgreSQL source.

Question

A company needs to send customer call data from its on-premises PostgreSQL database to AWS to generate near real-time insights. The solution must capture and load updates from operational data stores that run in the PostgreSQL database. The data changes continuously. A data engineer configures an AWS Database Migration Service (AWS DMS) ongoing replication task. The task reads changes in near real time from the PostgreSQL source database transaction logs for each table. The task then sends the data to an Amazon Redshift cluster for processing. The data engineer discovers latency issues during the change data capture (CDC) of the task. The data engineer thinks that the PostgreSQL source database is causing the high latency. Which solution will confirm that the PostgreSQL database is the source of the high latency?

Use Amazon CloudWatch to monitor the DMS task. Examine the CDCIncomingChanges metric to identify delays in the CDC from the source database.
Verify that logical replication of the source database is configured in the postgresql.conf configuration file.
Enable Amazon CloudWatch Logs for the DMS endpoint of the source database. Check for error messages.
Use Amazon CloudWatch to monitor the DMS task. Examine the CDCLatencySource metric to identify delays in the CDC from the source database. Correct Answer

Key Takeaways

It tests the distinction between source-side CDC read latency and target-side backlog; the trap is choosing CDCIncomingChanges, which reflects queued changes rather than time spent reading PostgreSQL transaction logs.

This question tests how to isolate change data capture latency in an AWS DMS ongoing replication task from PostgreSQL to Amazon Redshift. The page establishes that CDCLatencySource, not CDCIncomingChanges or endpoint logs, confirms whether the PostgreSQL source is causing the delay.

Common mistake: Many learners choose CDCIncomingChanges (A) because it sounds like incoming changes from the source, but that metric tracks change events waiting to be applied and does not isolate PostgreSQL source read latency.

Expert Analysis

Why the Answer Is Correct

CDCLatencySource measures the time between reading a change from the PostgreSQL source transaction logs and the AWS DMS task receiving it, so an elevated value points specifically at source-side capture. Amazon CloudWatch is the supported monitoring surface for DMS task metrics, making CDCLatencySource a direct, non-invasive diagnostic. In an ongoing replication task with continuous changes, this metric separates source read delay from Redshift target apply delay. As tgv notes, "This metric measures the latency between the source database and the DMS task."

Why the Other Options Are Wrong

CDCIncomingChanges (A) shows change events waiting to be applied, so a high value can result from a Redshift bottleneck rather than PostgreSQL capture delay. Verifying logical replication in postgresql.conf (B) is a prerequisite check: if logical replication were not configured, CDC would fail outright, but this does not confirm the source of measured latency. Enabling CloudWatch Logs for the source endpoint (C) may reveal connection or permission errors, but logs do not quantify source-side CDC latency, and an absence of errors does not prove the PostgreSQL database is the bottleneck.

Community Comment Notes

Community consensus is unanimous for D. tgv links the official DMS monitoring metrics page and explains the source-to-task meaning, while sdas1 links the latency troubleshooting page and summarizes that a high CDCLatencySource indicates delayed source capture. HunkyBunky adds that "only D makes sense." No comment defends A, B, or C as a way to confirm PostgreSQL source latency.

Official Reference

These links open the official vendor documentation in a new tab.

Exam Strategy

For DMS CDC latency questions, first decide whether the delay is on the source read side or target apply side, then map that to CDCLatencySource or CDCLatencyTarget. Do not pick configuration checks or endpoint logs when the question asks which metric confirms the source of latency.

Frequently Asked Questions

Why does CDCIncomingChanges not confirm PostgreSQL source latency?

CDCIncomingChanges reflects change events waiting to be applied, so it can rise from Redshift target bottlenecks; it does not measure time spent reading PostgreSQL transaction logs.

What does a high CDCLatencySource value mean in an AWS DMS CDC task?

It means changes are waiting between the PostgreSQL source and the DMS task, indicating source-side capture delay rather than Redshift apply latency.

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Community Votes

100%

100% of anonymous learners picked answer D. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 3 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 3

tgv 👍 5 Answered D

CDCLatencySource Metric: This metric measures the latency between the source database and the DMS task. It shows how long it takes for changes to be read from the source database's transaction logs. https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Monitoring.html#CHAP_Monitoring.Metrics
sdas1 👍 1

https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Troubleshooting_Latency.html A high CDCLatencySource metric indicates that the process of capturing changes from the source is delayed. Answer is D
HunkyBunky 👍 1 Answered D

only D makes sense

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