Introduction

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. One of its powerful features is DynamoDB Streams, which allows you to capture and act upon data changes made to items in DynamoDB tables. This article will dive deep into setting up a DynamoDB stream trigger that only responds to insert operations. We'll cover the technical aspects of streams, triggers, and how to filter for specific operations.

Understanding DynamoDB Streams

DynamoDB streams capture changes to items in the form of stream records and store them for up to 24 hours. Each stream record contains information about a single data modification in the DynamoDB table. The stream record can include:

• Keys: Primary key attribute(s) of the modified item.
• NewImage: A view of the item after it was modified.
• OldImage: A view of the item before it was modified.
• SequenceNumber: A unique identifier for the modification across all items.
• StreamViewType: Controls the information that is written to the stream for each table modification.

The possible options for StreamViewType are:

• KEYS_ONLY: Only the key attributes of modified items.
• NEW_IMAGE: The entire item, as it appeared after it was modified.
• OLD_IMAGE: The entire item, as it appeared before it was modified.
• NEW_AND_OLD_IMAGES: Both the new and old item images.

For capturing inserts only, NEW_IMAGE could be the most useful choice as it focuses on the item state after an insert operation occurs.

Setting Up DynamoDB Stream for Inserts

To effectively capture only insert operations, you need to establish a trigger, typically using AWS Lambda, that processes the DynamoDB stream and filters only for inserts.

Step 1: Enabling DynamoDB Streams

To enable streams on a DynamoDB table:

1. Go to your DynamoDB table in the AWS Management Console.
2. Select the "Exports and streams" tab.
3. Choose "Enable" in the DynamoDB Streams section.
4. Select NEW_IMAGE for StreamViewType to focus on new entries.
5. Save the settings.

Step 2: Configuring an AWS Lambda Function

AWS Lambda can be seamlessly integrated with DynamoDB Streams, allowing processing of stream records. Here’s how to create and configure a Lambda function to process insert events:

1. Create a new Lambda function:
   • Use Node.js, Python, or another language supported by AWS Lambda.
   • Define the necessary IAM roles that include permissions to read from DynamoDB Streams and write logs to CloudWatch.
2. Set up a trigger for DynamoDB:
   • In the Lambda function configuration, add a trigger.
   • Select "DynamoDB" as the trigger source.
   • Choose the relevant table and stream.
3. Write code to filter insert operations: Example using Python:

1   import json
2
3   def lambda_handler(event, context):
4       for record in event['Records']:
5           # Check if the event type is INSERT
6           if record['eventName'] == 'INSERT':
7               new_image = record['dynamodb']['NewImage']
8               # Process new entry
9               process_new_entry(new_image)
10
11   def process_new_entry(new_image):
12       # Placeholder function to handle the new insert
13       print("New insertion:", json.dumps(new_image, indent=4))

Step 3: Deploy and Test the Function

• Deploy the Lambda code and activate the trigger.
• Test the functionality by adding new items to the DynamoDB table.
• Verify that your Lambda function processes only the insertions, as shown in logs in AWS CloudWatch.

Example Use-case: Building an Audit Log

Imagine a scenario where you want to create an audit log of all new entries added to your database. By setting up the Lambda function as described, you can:

1. Capture every new record added to a table.
2. Store details such as timestamps, user IDs, or other metadata relevant to each insert operation.
3. Push this data to a logging service, another database table, or an analytics pipeline.

Summary Table

Here's a summary of key concepts and steps:

Conclusion

Configuring a DynamoDB stream trigger to process only insert operations involves enabling streaming on the database, configuring AWS Lambda to handle stream events, and filtering for specific operations such as inserts. This capability opens up powerful use-cases such as building audit logs, real-time notifications, and other analytics tasks that require immediate awareness of new data in your system. By tailoring stream processing to specific operations, resources are used efficiently, ensuring that your architecture meets your business needs effectively.