AWS Lambda Function Timing Out When Accessing DynamoDB on High Load
I've been banging my head against this for hours... I've been struggling with this for a few days now and could really use some help. This might be a silly question, but I'm experiencing a timeout scenario with my AWS Lambda function when it tries to access DynamoDB under high load conditions. The function is set to handle user authentication requests and is triggered via API Gateway. When the number of concurrent requests exceeds 50, I consistently get a `Task timed out after 3.00 seconds` behavior, even though I've increased the timeout setting to 10 seconds. Here’s a snippet of my Lambda function: ```python import boto3 import json def lambda_handler(event, context): dynamodb = boto3.resource('dynamodb') table = dynamodb.Table('UserTable') user_id = event['user_id'] try: response = table.get_item(Key={'user_id': user_id}) return { 'statusCode': 200, 'body': json.dumps(response.get('Item', {})) } except Exception as e: return { 'statusCode': 500, 'body': json.dumps({'behavior': str(e)}) } ``` I’ve already tried increasing the provisioned throughput on my DynamoDB table, and I've enabled enhanced monitoring to track read/write capacity. My table is set to allow auto-scaling, but it seems like the throttling is happening with the Lambda invocations instead. I've also verified that the IAM role associated with the Lambda function has the necessary permissions to access the DynamoDB table. Would configuring the Lambda to use an Amazon VPC improve performance under load? Or should I consider using AWS Step Functions to better handle the execution? Any suggestions or best practices would be greatly appreciated. Is there a better approach? My development environment is Windows. Any help would be greatly appreciated! I'm working with Python in a Docker container on Windows 11. Any suggestions would be helpful. For context: I'm using Python on Ubuntu 22.04. Has anyone dealt with something similar?