AWS Lambda with DynamoDB Streams: Processing Duplicate Events
I'm getting frustrated with Quick question that's been bugging me - I'm upgrading from an older version and I'm maintaining legacy code that I've looked through the documentation and I'm still confused about I've looked through the documentation and I'm still confused about I'm currently working on an AWS Lambda function that processes events from a DynamoDB stream... The function is intended to update a corresponding item in another DynamoDB table whenever a new item is added. However, I am encountering issues with duplicate processing of events, particularly when there are multiple updates to the same item within a short timeframe. My Lambda has a concurrency limit of 5, and I've set up the stream to trigger the Lambda immediately. Here's the code for my Lambda function: ```python import json import boto3 dynamodb = boto3.resource('dynamodb') def lambda_handler(event, context): table = dynamodb.Table('TargetTable') for record in event['Records']: if record['eventName'] == 'INSERT': new_image = record['dynamodb']['NewImage'] # Extract relevant fields item_id = new_image['ItemID']['S'] item_value = new_image['ItemValue']['S'] # Update target table table.put_item(Item={'ItemID': item_id, 'ItemValue': item_value}) return { 'statusCode': 200, 'body': json.dumps('Processed') } ``` When testing, I noticed that if I insert multiple items quickly, the Lambda processes the events in parallel, leading to updates with potentially stale data. I received a warning about throttling, and in some cases, I'm seeing outdated values being recorded. For instance, if I insert two records with the same `ItemID` but different `ItemValue` in quick succession, the final state in `TargetTable` is not as expected. I've tried implementing a deduplication strategy by checking existing items before processing, but that doesn't fully mitigate the issue since DynamoDB Streams can batch records. I also explored using DynamoDB's conditional writes, but the logic is getting complicated and doesn't seem to prevent all duplicates. What strategies can I employ to ensure that my Lambda function handles DynamoDB Stream events without duplicating entries or processing stale data? Are there best practices or patterns in AWS for resolving such scenarios efficiently? Is there a better approach? For context: I'm using Python on macOS. What's the best practice here? My development environment is Windows. This is happening in both development and production on Ubuntu 22.04. Thanks for taking the time to read this! This is for a web app running on Debian. Any pointers in the right direction? The stack includes Python and several other technologies. Any help would be greatly appreciated!