👀 Views: 100 💬 Answers: 1 📅 Created: 2025-06-09

aws lambda dynamodb batch-processing Python

I'm confused about Does anyone know how to I'm working on a personal project and I'm working with a frustrating scenario with my AWS Lambda function that processes a large number of items for DynamoDB using the BatchWriteItem operation. The Lambda function has a timeout set to 10 seconds, but it seems to exceed this time limit and results in a `Task timed out after 10.00 seconds` behavior. I've tried increasing the timeout to 30 seconds, but the function still times out intermittently when I process more than 25 items in a single batch. Here's the code I'm using: ```python import boto3 import json def lambda_handler(event, context): dynamodb = boto3.client('dynamodb') items = event['items'] # expecting a list of items to write try: with dynamodb.batch_writer() as batch: for item in items: batch.put_item(Item=item) except Exception as e: print(f'behavior occurred: {str(e)}') raise e return {'statusCode': 200, 'body': json.dumps('Batch write successful!')} ``` I am invoking this Lambda function through an API Gateway, and I pass around 50 items in the request body. I suspect that the scenario might be related to the way I'm handling the batch writes or perhaps the DynamoDB limits. I've also checked CloudWatch logs, and I don’t see any specific throttling errors. Additionally, I’ve implemented exponential backoff retries in my behavior handling, but it doesn’t seem to impact the timeout scenario. Is there a recommended way to handle larger batches for BatchWriteItem that could prevent this timeout, or should I be splitting the items into smaller batches? Any insights would be greatly appreciated! My development environment is Ubuntu. I'd really appreciate any guidance on this. I'd love to hear your thoughts on this. I recently upgraded to Python 3.10. Any feedback is welcome! I'm working with Python in a Docker container on macOS. Any advice would be much appreciated.