Which solution will meet these requirements?

Explanations:

While using AWS Lambda and Step Functions can help orchestrate processing, invoking a Lambda function for each record can lead to performance issues if the number of records is large. Lambda has limitations on execution time and concurrency, making it less suitable for processing multiple records efficiently within a specified time frame.

Containerizing the processing logic and using Amazon EKS with Fargate allows for more efficient resource management and scaling. This solution can handle larger volumes of records more effectively and allows for running containers without managing the underlying EC2 instances. Scheduling with Amazon EventBridge ensures that the processing starts at midnight with minimal operational overhead.

Using a single Lambda function to process all records could exceed the function’s timeout limits and may not efficiently handle larger workloads. S3 Event Notifications would not be an appropriate choice for this batch processing scenario as they trigger on individual object uploads rather than on a schedule.

While containerizing the logic is beneficial, using Amazon ECS with SNS for scheduling does not provide the most efficient solution for this batch job scenario. SNS is more suited for event-driven architectures rather than for scheduled batch processing. Additionally, it adds unnecessary complexity compared to using EventBridge.