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AWS DVA-C02 Drill: Sensitive Data Detection Across Regions - Macie’s Minimal Effort Solution

Jeff Taakey
Author
Jeff Taakey
21+ Year Enterprise Architect | AWS SAA/SAP & Multi-Cloud Expert.

Jeff’s Note
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Unlike generic exam dumps, ADH analyzes this scenario through the lens of a Real-World Lead Developer.

For DVA-C02 candidates, the confusion often lies in choosing the right managed service that does most of the heavy lifting with minimal custom code. In production, this is about knowing exactly which AWS service natively analyzes sensitive data and how to consolidate findings across regions efficiently. Let’s drill down.

The Certification Drill (Simulated Question)
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Scenario
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A tech startup called DataVista stores customer profiles and documents in Amazon S3 buckets spread across multiple AWS Regions for compliance and locality reasons. The lead developer must implement a solution that automatically identifies sensitive information—like personally identifiable information (PII)—in these distributed S3 buckets. Crucially, all analysis results must be centralized and quickly accessible in the eu-west-2 (London) Region.

The Requirement:
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Design a solution to analyze sensitive data in multiple S3 buckets spanning several regions and consolidate the findings into a single S3 bucket located in eu-west-2, with the least amount of development effort required.

The Options
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  • A) Create an AWS Lambda function that analyzes each bucket’s data and sends the generated findings to a dedicated S3 bucket in eu-west-2.

  • B) Configure Amazon Macie to scan all S3 buckets and generate findings. Use Amazon EventBridge rules to copy these findings to the eu-west-2 region.

  • C) Set up Amazon Inspector to scan the S3 buckets and generate findings. Use Amazon EventBridge rules to copy the results to eu-west-2.

  • D) Enable Amazon Macie to generate sensitive data findings and publish them to AWS CloudTrail. Configure a CloudTrail trail to copy the findings to an S3 bucket in eu-west-2.


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Correct Answer
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B

Quick Insight: The Developer Imperative
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  • Amazon Macie is purpose-built for sensitive data discovery in S3, unlike Inspector which focuses on instance vulnerabilities.
  • EventBridge can efficiently route Macie findings cross-region without heavy custom glue code.
  • This combination minimizes development overhead while meeting multi-region aggregation needs.

Content Locked: The Expert Analysis
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You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?


The Expert’s Analysis
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Correct Answer
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Option B

The Winning Logic
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Amazon Macie is AWS’s managed service designed specifically for discovering, classifying, and protecting sensitive data in Amazon S3. It can scan buckets across multiple regions. Macie automatically generates findings for sensitive information, which can be routed using Amazon EventBridge to other AWS targets—including an S3 bucket in eu-west-2.

This out-of-the-box connectivity reduces the need for custom Lambda code or manual copying workflows, enabling a developer to meet the requirement with minimal code (mostly configuration). EventBridge acts as the event router, efficiently handling the cross-region data replication of findings.

The Trap (Distractor Analysis):
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  • Why not Option A?
    Building a custom Lambda function to analyze sensitive data would require implementing sensitive data detection logic or calling Macie’s APIs and handling error retries, scaling, and cross-region data transfer manually. That involves significantly more developer effort.

  • Why not Option C?
    Amazon Inspector focuses on security assessment of EC2 instances and container workloads, not on analyzing sensitive data inside S3 objects. So, it is the wrong service for this use case.

  • Why not Option D?
    Macie findings are not published to CloudTrail. CloudTrail logs API calls but does not stream Macie’s data classification findings. Using CloudTrail trails for copying findings would not work for this analytic aggregation scenario.


The Technical Blueprint
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B) For Developer (Code/CLI Snippet):

Example EventBridge rule snippet to route Macie findings to an S3 bucket in eu-west-2:

aws events put-rule \
    --name "MacieFindingsToEUWest2" \
    --event-pattern '{
      "source": ["aws.macie2"],
      "detail-type": ["Macie Finding"]
    }' \
    --region eu-west-2

aws events put-targets \
    --rule "MacieFindingsToEUWest2" \
    --targets "Id"="1","Arn"="arn:aws:s3:::centralized-macie-findings-bucket"

(Assuming Macie is enabled in all regions and configured to send findings.)


The Comparative Analysis
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Option API Complexity Performance Use Case
A High – Custom code Moderate Custom analysis & data aggregation
B (Correct) Low – Managed integration High Automated sensitive data detection & centralized findings aggregation
C N/A – Service mismatch N/A Not applicable for S3 data analysis
D Incorrect integration N/A CloudTrail does not support Macie findings publishing

Real-World Application (Practitioner Insight)
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Exam Rule
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“For the exam, always pick Amazon Macie when you see ‘sensitive data discovery’ in S3 across multiple regions.”

Real World
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“In reality, enterprises also integrate Macie findings with SIEM tools or AWS Security Hub for centralized compliance monitoring, but EventBridge remains the glue for robust cross-service event routing.”


(CTA) Stop Guessing, Start Mastering
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Disclaimer

This is a study note based on simulated scenarios for the AWS DVA-C02 exam.

The DevPro Network: Mission and Founder

A 21-Year Tech Leadership Journey

Jeff Taakey has driven complex systems for over two decades, serving in pivotal roles as an Architect, Technical Director, and startup Co-founder/CTO.

He holds both an MBA degree and a Computer Science Master's degree from an English-speaking university in Hong Kong. His expertise is further backed by multiple international certifications including TOGAF, PMP, ITIL, and AWS SAA.

His experience spans diverse sectors and includes leading large, multidisciplinary teams (up to 86 people). He has also served as a Development Team Lead while cooperating with global teams spanning North America, Europe, and Asia-Pacific. He has spearheaded the design of an industry cloud platform. This work was often conducted within global Fortune 500 environments like IBM, Citi and Panasonic.

Following a recent Master’s degree from an English-speaking university in Hong Kong, he launched this platform to share advanced, practical technical knowledge with the global developer community.


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