Post status of long running aws lambda function

I have an AWS lambda function that runs a machine learning model on frames of a short video. It might take a few minutes to run, depending on the video.

I invoke the lambda from another lambda asynchronously. The second lambda just launches the first lambda and returns an S3 location where the results are stored.

I would like some way of checking the status of the lambda. E.g. what percent of the frames have been processed.

Right now I am just writing the status to the S3 location and periodically checking that file. Is there any better way of storing and retrieving this kind of status information?

For some context this is just for an educational project so there are no real requirements. The S3 method works fine for my use-case but I'm wondering what would be the best for a real production system.

I can think of couple approaches:

1. What you did is actually fine even for production system. I would probably use DynamoDB instead of S3 for this, as it's faster and probably cheaper at large scale for this use case.
2. If there are clear steps that you could break down your processing into, then you could use Step Functions (likely express workflows) instead of Lambda, and then you could check the state of the workflow via API to check how far processing has progressed.
3. Finally, if every frame can be processed independently, you could put an SQS queue in-between and parallelise processing. This would not only improve performance and error-handling, but also enable progress tracking by checking queue size (though that might not be trivial if you can have multiple parallel works in progress)