[FIXED] Best way to set up jupyter notebook project in AWS

Issue

My current project have the following structure:

Starts with a script in jupyter notebook which dowloads data from a CRM API to put in a local PostgressSql database I run with PgAdmin. After that it runs cluster analysis, return some scoring values, creates a table in database with the results and updates this values in the CRM with another API call. This process will take between 10 to 20 hours (the API only allows 400 requests per minute).

The second notebook reads the database, detects last update, runs api call to update database since the last call, runs kmeans analysis to cluster the data, compare results with the previous call, updates the new ones and the CRM via API. This second process takes less than 2 hours in my estimation and I want this script to run every 24 hours.

After testing, this works fine. Now I'm evaluating how to put this in production in AWS. I understand for the notebooks I need Sagemaker and from I have seen is not that complicated, my only doubt here is if I can call the API without implementing aditional code or need some configuration. My second problem is database. I don't understand the difference between RDS which is the one I think I have to use for this and Aurora or S3. My goal is to write the less code as possible, but a have try some tutorial of RDS like this one: [1]: https://www.youtube.com/watch?v=6fDTre5gikg&t=10s, and I understand this connect my local postgress to AWS but I can't find the data in the amazon page, only creates an instance?? and how to connect to it to analysis this data from SageMaker. My final goal is to run the notebooks in the cloud and connect to my postgres in the cloud. Just some orientation about how to use this tools would be appreciated.

Solution

I don't understand the difference between RDS which is the one I think I have to use for this and Aurora or S3

RDS and Aurora are relational databases fully managed by AWS. "Regular" RDS allows you to launch the existing popular databases such as MySQL, PostgreSQSL and other which you can launch at home/work as well.

Aurora is in-house, cloud-native implementation databases compatible with MySQL and PosrgreSQL. It can store the same data as RDS MySQL or PosrgreSQL, but provides a number of features not available for RDS, such as more read replicas, distributed storage, global databases and more.

S3 is not a database, but an object storage, where you can store your files, such as images, csv, excels, similarly like you would store them on your computer.

I understand this connect my local postgress to AWS but I can't find the data in the amazon page, only creates an instance??

You can migrate your data from your local postgress to RDS or Aurora if you wish. But RDS nor Aurora will not connect to your existing local database, as they are databases themselfs.

My final goal is to run the notebooks in the cloud and connect to my postgres in the cloud.

I don't see a reason why you wouldn't be able to connect to the database. You can try to make it work, and if you encounter difficulties you can make new question on SO with RDS/Aurora setup details.

Answered By - Marcin