AWS Lambda Timing Out with S3 Event Trigger - How to Optimize for Large Files?
I've been struggling with this for a few days now and could really use some help. I'm stuck on something that should probably be simple... I'm encountering a timeout issue with my AWS Lambda function that's triggered by S3 events. The Lambda function processes large files (typically around 500 MB) and it's timing out after the default 3 seconds. I've tried increasing the timeout setting in the Lambda configuration to 30 seconds, but it still fails to complete within that time frame. My current Lambda function is set up in Python 3.8 and uses the `boto3` library to read the file from S3. Here's a snippet of my function: ```python import boto3 import json def lambda_handler(event, context): s3 = boto3.client('s3') bucket_name = event['Records'][0]['s3']['bucket']['name'] object_key = event['Records'][0]['s3']['object']['key'] try: response = s3.get_object(Bucket=bucket_name, Key=object_key) file_content = response['Body'].read() # This seems to hang for large files # Process file_content here except Exception as e: return { 'statusCode': 500, 'body': json.dumps('Error processing file: ' + str(e)) } return { 'statusCode': 200, 'body': json.dumps('File processed successfully') } ``` Despite increasing the timeout, it appears that the function gets stuck when trying to read the body of the S3 object. I've also considered chunking the file, but I'm unsure how to implement this effectively with S3 events since they trigger the Lambda function with a specific object reference. How can I optimize my Lambda function to handle larger files without hitting the timeout limit? Are there any best practices or design patterns I should be aware of? This is part of a larger API I'm building. Has anyone else encountered this? I'm on Windows 10 using the latest version of Python. Has anyone else encountered this? This issue appeared after updating to Python 3.9. What would be the recommended way to handle this?