Event-driven architecture patterns in DynamoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Querying DynamoDB Stream Events for Specific Event Types

You have a DynamoDB table with streams enabled. The stream records include events of types INSERT, MODIFY, and REMOVE. Which query expression will correctly filter and return only the INSERT events from the stream records?

DynamoDB

SELECT * FROM StreamRecords WHERE eventName = 'INSERT';

A SELECT * FROM StreamRecords WHERE eventName = 'ADD';

B SELECT * FROM StreamRecords WHERE eventType = 'INSERT';

C SELECT * FROM StreamRecords WHERE eventName = 'INSERT';

D SELECT * FROM StreamRecords WHERE eventName = 'CREATE';

💡 Hint

Check the exact attribute name used for event type in DynamoDB streams.

DynamoDB stream records use the attribute 'eventName' to indicate the type of event, such as INSERT, MODIFY, or REMOVE. Using 'eventName = 'INSERT'' correctly filters for insert events.

🧠 Conceptual

intermediate

Understanding Event Sourcing with DynamoDB

In an event-driven architecture using DynamoDB, what is the main advantage of using event sourcing to store changes as events rather than storing only the current state?

A It allows reconstructing the entire state history by replaying events.

B It reduces the storage size by storing only the latest state.

C It eliminates the need for DynamoDB streams.

D It automatically indexes all events for faster queries.

💡 Hint

Think about how event sourcing helps with state recovery and auditing.

Event sourcing stores all changes as events, enabling the system to rebuild the current state by replaying these events. This provides a full history and audit trail.

📝 Syntax

advanced

Correct Syntax for DynamoDB Stream Event Processing in Lambda

Which of the following AWS Lambda event handler code snippets correctly accesses the new image of a DynamoDB stream record for an INSERT event?

DynamoDB

exports.handler = async (event) => {
  for (const record of event.Records) {
    if (record.eventName === 'INSERT') {
      const newImage = record.dynamodb.NewImage;
      // process newImage
    }
  }
};

A const newImage = record.dynamodb.NewImage;

B const newImage = record.dynamodb.newImage;

C const newImage = record.DynamoDB.NewImage;

D const newImage = record.dynamodb.OldImage;

💡 Hint

Check the exact casing and property names in the DynamoDB stream record object.

The correct property to access the new image is 'NewImage' under 'dynamodb' in the stream record. It is case-sensitive.

❓ optimization

advanced

Optimizing Event Processing with DynamoDB Streams and Lambda

You want to optimize your Lambda function triggered by DynamoDB streams to process events efficiently. Which approach will best reduce cold start latency and improve throughput?

A Set the batch size to 1 to process events one by one for simplicity.

B Use batch processing by setting the batch size to a higher number in the event source mapping.

C Disable parallelization to ensure events are processed sequentially.

D Increase the Lambda timeout to the maximum allowed to avoid timeouts.

💡 Hint

Think about how batch size affects invocation frequency and processing speed.

Increasing batch size allows Lambda to process multiple records in one invocation, reducing overhead and cold starts, thus improving throughput.

🔧 Debug

expert

Debugging Missing Events in DynamoDB Stream Processing

Your Lambda function processing DynamoDB stream events sometimes misses INSERT events. Which of the following is the most likely cause?

A The Lambda function code incorrectly accesses 'OldImage' instead of 'NewImage'.

B The DynamoDB table does not have streams enabled.

C The Lambda event source mapping has a filter that excludes INSERT events.

D The DynamoDB stream is set to KEYS_ONLY, so new images are not available.

💡 Hint

Consider the stream view type configuration and what data it provides.

If the stream is set to KEYS_ONLY, only keys are included in stream records, so the Lambda cannot access the full new image of inserted items, causing missing event data.