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AWS DVA-C02 Drill: DynamoDB Streams - Event-Driven Processing Without Operational Overhead

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 event-driven integration to minimize operational complexity while ensuring reliability and realtime processing. In production, this is about understanding exactly how DynamoDB Streams seamlessly trigger Lambda functions for near-instant item processing without the need for polling or custom infrastructure. Let’s drill down.

The Certification Drill (Simulated Question)
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Scenario
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AtlasTech, a rapidly growing IoT sensor management startup, stores sensor metadata in a DynamoDB table with configured TTL attributes to automatically expire stale device records. The engineering team needs to build a data pipeline that captures these expired device items immediately upon expiry, processes their metadata, and archives the processed data to Amazon S3 for long-term storage. From expiry to S3 storage, the entire pipeline should complete within five minutes without the team having to manage servers or orchestrate complex polling logic.

The Requirement:
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Design a solution to automatically detect expired DynamoDB items, process them, and store them in Amazon S3 with the least operational overhead and within a five-minute window.

The Options
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  • A) Configure DynamoDB Accelerator (DAX) to query the table for expired items based on TTL and batch save the results to S3.
  • B) Enable DynamoDB Streams to trigger an AWS Lambda function that processes each expired item and stores it in S3.
  • C) Build and deploy a custom application on Amazon ECS running on EC2 instances that scans the table for expired items and uploads them to S3.
  • D) Use an Amazon EventBridge scheduled rule to invoke a Lambda function that queries expired items from DynamoDB and stores them in S3.

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Correct Answer
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B

Quick Insight: The Developer’s Event-Driven Imperative
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For DVA-C02 candidates, this scenario tests your mastery of DynamoDB Streams as a scalable event source and your knowledge that TTL deletions trigger stream records. The ability to react in near real-time using Lambda eliminates polling and manual orchestration, reducing operational overhead to nearly zero.

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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DynamoDB Streams capture item-level changes, including TTL expiration deletions, and can invoke Lambda functions in response. This creates a fully managed, event-driven architecture with minimal operational overhead—no polling or scheduled tasks needed. The Lambda function can process the expired item shortly after deletion and upload it to S3 efficiently, all within the required 5-minute window.

  • DynamoDB TTL expiration leads to removal events in streams, enabling immediate triggers.
  • Lambda’s autoscaling and pay-per-execution model minimize cost and operational burden.
  • This pattern respects best practices for serverless event-driven design and data archival workflows.

The Trap (Distractor Analysis)
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  • Why not A? DAX is an in-memory acceleration cache for DynamoDB read operations; it does not notify or track item expirations. It cannot react to TTL deletions or trigger workflows automatically.
  • Why not C? Building custom ECS container apps on EC2 introduces significant operational overhead—managing clusters, scaling, monitoring, and complex polling logic—which contradicts the requirement of minimal overhead.
  • Why not D? EventBridge rules invoked on schedules require polling DynamoDB within the Lambda, which is inefficient and introduces unnecessary latency and complexity compared to event-driven streams.

The Technical Blueprint
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# Enable DynamoDB Streams on the table with NEW_IMAGE or OLD_IMAGE data capture
aws dynamodb update-table \
    --table-name SensorDevices \
    --stream-specification StreamEnabled=true,StreamViewType=OLD_IMAGE

# Example Lambda trigger configuration (simplified)
aws lambda create-event-source-mapping \
    --function-name ProcessExpiredItems \
    --event-source-arn arn:aws:dynamodb:region:account-id:table/SensorDevices/stream/timestamp \
    --starting-position LATEST

The Comparative Analysis
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Option API/Event Complexity Performance Use Case
A Low — uses DAX cache Poor No event notifications on TTL expiry
B Moderate — streams + Lambda trigger High Serverless, event-driven, minimal overhead
C High — custom app + polling Moderate Heavy management overhead, complex to scale
D Moderate — EventBridge scheduled Lambda Low Scheduled polling, more latency & overhead

Real-World Application (Practitioner Insight)
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Exam Rule
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For the exam, always pick DynamoDB Streams + Lambda when you see TTL expiration processing requirements.

Real World
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In production, many teams complement this pattern with dead-letter queues and monitoring alarms on Lambda errors to ensure no expired item is lost during ingestion and archival.


(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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