Best Practice for streaming CDC from multiple tables

Question

I'm using DMS to capture CDC from an RDS PostgreSQL Database, then writing the changes to a Kinesis Data Stream and finally using a Glue Streaming Job to process the data and write it to a Hudi Data Lake in S3. 
For multiple tables is the best practice to have 1 DMS task, 1 Kinesis Data Stream and 1 Glue Job for each table or is there a way to process multiple tables at a time? 
Thanks in advance!

Answer

Yes, in the code if you call the forEachLoop/await in a thread, you can start multiple streaming queries in the same cluster (Glue streaming job), for instance if using PySpark using a [ThreadPool and tasks](https://docs.python.org/3/library/concurrent.futures.html)  
This is complicate monitoring, tuning and operations in general but will save you cost significantly.

Answer

Thanks for the answer. So, in terms of maintainability it would be best to have one for each, but for cost saving parallel tasks would be better, right?

Best Practice for streaming CDC from multiple tables

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