AWS Lambda Timeout scenarios with DynamoDB Queries on Large Datasets
I've spent hours debugging this and I'm working on a project and hit a roadblock. I'm experiencing a timeout scenario with my AWS Lambda function when it tries to query a DynamoDB table that has a large dataset (around 10 million items). The function is set to run for a maximum of 30 seconds, but I'm getting a timeout behavior after about 25 seconds. I've optimized my DynamoDB queries using indexes, but I still face the timeout scenario. Here’s a snippet of my code where I perform the query: ```python import boto3 import json def lambda_handler(event, context): dynamodb = boto3.resource('dynamodb') table = dynamodb.Table('MyTable') response = table.query( KeyConditionExpression=Key('PartitionKey').eq(event['key']), Limit=1000 # Limiting results for each query ) return { 'statusCode': 200, 'body': json.dumps(response['Items']) } ``` I've tried increasing the Lambda memory from 128MB to 512MB and set a timeout to 30 seconds, but it didn’t help. I also considered breaking up the queries into smaller batches, but I’m unsure how to implement this without complicating the code. Is there a better approach I can take to avoid this timeout scenario while still efficiently querying my DynamoDB table? Any tips or best practices would be greatly appreciated! This is part of a larger CLI tool I'm building.