Jeff’s Note #
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 best to minimize development overhead when reacting to DynamoDB Stream events. In production, this is about knowing exactly how Lambda’s native event filtering can reduce boilerplate code and simplify your function logic. Let’s drill down.
The Certification Drill (Simulated Question) #
Scenario #
DataPulse Inc., an online retail startup, stores transaction records in an Amazon DynamoDB table. Each record contains a field called TransactionStatus which can only have three values: failed, pending, or completed. They also have a Price attribute for each transaction. DataPulse enabled DynamoDB Streams on their sales table to track changes.
Now, the company wants to get notified instantly when transactions fail and the price exceeds a predefined threshold. The development team’s mandate is to implement this notification mechanism with the least amount of coding and ongoing maintenance effort.
The Requirement: #
Set up a notification system that alerts of failed sales transactions where the price is above the threshold, using DynamoDB Streams, but minimizing the development effort needed.
The Options #
- A) Create an event source mapping between DynamoDB Streams and an AWS Lambda function. Use Lambda event filtering to trigger the Lambda function only if sales fail when the price is above the specified threshold. Configure the Lambda function to publish the data to an Amazon Simple Notification Service (Amazon SNS) topic.
- B) Create an event source mapping between DynamoDB Streams and an AWS Lambda function. Configure the Lambda function handler code to publish to an Amazon Simple Notification Service (Amazon SNS) topic if sales fail when the price is above the specified threshold.
- C) Create an event source mapping between DynamoDB Streams and an Amazon Simple Notification Service (Amazon SNS) topic. Use event filtering to publish to the SNS topic if sales fail when the price is above the specified threshold.
- D) Create an Amazon CloudWatch alarm to monitor the DynamoDB Streams sales data. Configure the alarm to publish to an Amazon Simple Notification Service (Amazon SNS) topic if sales fail due when the price is above the specified threshold.
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Correct Answer #
A
Quick Insight: The Developer Imperative #
Lambda event filtering allows you to reduce the code complexity by preventing the Lambda function from being invoked unless the event data matches specific attribute patterns. This means you don’t have to write condition checks inside the function itself, boosting performance and lowering maintenance.
Content Locked: The Expert Analysis #
You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?
The Expert’s Analysis #
Correct Answer #
Option A
The Winning Logic #
Lambda event filtering is a feature that lets you specify simple JSON matching rules to filter the events your Lambda function receives before invocation. This means:
- Only relevant events (failed transactions with price above threshold) trigger the Lambda.
- Your Lambda code can be streamlined, focusing purely on notification logic with SNS.
- Minimizes runtime overhead and costly invocations.
- Requires less code since you don’t need to parse or filter events yourself.
Lambda’s event filtering is ideal here because DynamoDB Streams can contain many changes, only some of which need action.
The Trap (Distractor Analysis): #
- Option B: Manually filtering inside the Lambda function works but requires you to write and maintain event-parsing logic, thus more development effort than using Lambda event filtering.
- Option C: There’s no direct event source mapping between DynamoDB Streams and SNS. SNS cannot be a direct event source for streams—only for certain event rules or Lambda.
- Option D: CloudWatch Alarms do not monitor individual DynamoDB Stream events or data content; they monitor metrics. There’s no metric for “failed transaction with price above threshold,” making this ineffective.
The Technical Blueprint #
B) For Developer (Code/CLI Snippet): #
Example snippet of event source mapping with Lambda event filtering (using AWS CLI):
aws lambda create-event-source-mapping \
--function-name NotifyFailedSales \
--batch-size 100 \
--event-source-arn arn:aws:dynamodb:us-east-1:123456789012:table/SalesTable/stream/2024-04-14T00:00:00.000 \
--filter-criteria '{"Filters":[{"Pattern":"{\"dynamodb\":{\"NewImage\":{\"TransactionStatus\":{\"S\":[\"failed\"]},\"Price\":{\"N\":[\">100\"]}}}}]}'
In your Lambda, simply send the event to SNS without extra filtering inside the handler.
The Comparative Analysis #
| Option | API/Feature Complexity | Development Effort | Pros | Cons |
|---|---|---|---|---|
| A | Medium (event filtering + Lambda) | Low | Efficient filtering, less code, low latency | Slightly more setup on mapping |
| B | Low (standard Lambda code) | High | Direct control in code | More logic + maintenance burden |
| C | Invalid (no direct SNS for streams) | N/A | None | Not supported by AWS |
| D | Medium (CloudWatch alarms) | Medium | Uses CloudWatch, no code needed | Cannot filter specific data events |
Real-World Application (Practitioner Insight) #
Exam Rule #
“For the exam, choose Lambda event filtering when you want to minimize code logic filtering on event-driven architectures.”
Real World #
“In real-world scenarios, developers might skip event filters and handle logic inside Lambda due to complex filtering or when pre-filtering isn’t supported—but when the AWS feature exists and the filter condition is simple, event filtering is the cleanest approach.”
(CTA) Stop Guessing, Start Mastering #
Disclaimer
This is a study note based on simulated scenarios for the AWS DVA-C02 exam.