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DMS and Kinesis data firehose can stream data changes from MySQL onto Redshift and S3. This is common pattern for transactional sources with primary key in source tables. Here is a blog that describes how to load ongoing changes from source using Glue and DMS https://aws.amazon.com/blogs/big-data/loading-ongoing-data-lake-changes-with-aws-dms-and-aws-glue/ .
For historical data load into S3 and Redshift use DMS for low to moderate amount of data given that the customer have significant network bandwidth to AWS. For significant size data such as 10's TB exporting the MySQL data into raw files and move to AWS Snowball and import to S3 can be more reasonable and time efficient.
If the customer wants to have seamless ETL experience with sourcing capability from MySQL into Redshift and S3 they can use 3rd party product like Snaplogic. Here is a blog https://aws.amazon.com/blogs/apn/migrating-data-warehouse-workloads-from-on-premises-databases-to-amazon-redshift-with-snaplogic/
How to export data from RDS to S3 file SELECT * FROM users INTO OUTFILE S3 's3://some-bucket-name/users';
or you could use glue to load the data from RDS to S3 :https://www.mssqltips.com/sqlservertip/5918/serverless-etl-using-aws-glue-for-rds-databases/
