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AWS DVA-C02 Drill: Lambda-SQS Workflow Delay - Choosing the Most Operationally Efficient 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 AWS DVA-C02 candidates, the confusion often lies in how to implement delays in event-driven workflows with minimal operational overhead and code complexity. In production, this is about knowing exactly which service features support message delay natively and which require complex custom logic. Let’s drill down.

The Certification Drill (Simulated Question)
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Scenario
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TechFlow Innovations is building a system where incoming messages land first in an Amazon Simple Queue Service (SQS) queue to buffer workload spikes. However, before each message is processed by an AWS Lambda function, the system must enforce a controlled delay — for example, to allow dependent resources to be ready or to throttle downstream processing.

The Requirement:
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Design a solution that delays invocation of the Lambda function to process messages after they arrive in the SQS queue, with the goal of maximizing operational efficiency by minimizing custom code and infrastructure management.

The Options
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  • A) Implement an AWS Step Functions state machine triggered on a schedule via Amazon EventBridge. In the state machine, add a Wait state to pause for the required delay, then invoke the Lambda function with the message from the SQS queue.
  • B) Configure the Lambda function to poll the SQS queue directly. Modify the Lambda code to republish messages with a custom timestamp attribute representing when processing should occur, and have the Lambda check this timestamp to process messages only after the delay passes.
  • C) Set the SQS queue’s DelaySeconds attribute to the required delay time for message delivery postponement. Then configure an event source mapping directly from the SQS queue to the Lambda function.
  • D) Set the Visibility Timeout parameter on the SQS queue to the required delay, and configure an event source mapping for the Lambda function from the queue.

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Correct Answer
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C

Quick Insight: The Developer Imperative
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Implementing delay using the native SQS DelaySeconds feature is the simplest, most operationally efficient option for this use case. It requires no additional orchestration, no custom republishing logic, and minimal Lambda code changes.

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 C

The Winning Logic
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The key here is leveraging SQS’s native DelaySeconds attribute, which delays the delivery of each message to consumers by the specified number of seconds. When you set DelaySeconds on the queue, any message sent to the queue will be hidden from consumers (including Lambda via event source mapping) for that duration. This enables the required delay before Lambda invocation, exactly matching the requirement.

  • From a developer standpoint, this means no extra code needed to handle timing or republishing. The Lambda function receives the message only after the intended wait.
  • The event source mapping triggers Lambda immediately once the message becomes visible, maintaining low-latency processing and operational simplicity.

The Trap (Distractor Analysis):
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  • Why not A? Using Step Functions plus EventBridge adds unnecessary complexity and cost. Scheduled workflows can introduce latency inaccuracies and operational overhead managing state machines.
  • Why not B? Polling plus republishing messages with custom attributes complicates Lambda logic significantly, increasing risk for bugs and maintenance burden.
  • Why not D? Visibility Timeout controls message invisibility after a Lambda receives and processes the message, primarily for retry scenarios, not for delaying initial delivery. Using it for delay can cause unintended side effects like duplicate processing or message loss.

The Technical Blueprint
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# Example CLI command to create SQS queue with DelaySeconds=60 (delay by 60 seconds)
aws sqs create-queue --queue-name DelayedProcessingQueue \
    --attributes DelaySeconds=60

# Example setting the event source mapping for Lambda polling from this queue
aws lambda create-event-source-mapping \
    --function-name ProcessDelayedMessages \
    --batch-size 10 \
    --event-source-arn arn:aws:sqs:region:account-id:DelayedProcessingQueue

The Comparative Analysis
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Option API Complexity Performance Use Case
A High (Step Functions + EventBridge) Higher latency due to polling schedule Complex workflows with dynamic delays
B Very High (Lambda message republishing + timestamp logic) Latency depends on polling frequency, error-prone Custom delay logic with complex business rules
C Low (native SQS DelaySeconds) Optimal, minimal latency Simple delayed processing scenarios
D Moderate (Visibility Timeout misused) Risk of message duplication, not intended for delay Retry/backoff control, not delays

Real-World Application (Practitioner Insight)
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Exam Rule
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For the exam, always pick SQS DelaySeconds when you see “delay delivery of messages before Lambda processing”.

Real World
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In production, if delays require conditional logic or complex branching, Step Functions or custom polling might be justified. But for straightforward fixed delays, native SQS delays keep code simple and operational overhead low.


(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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