Creating a hybrid cloud analytics solution integrating on-premises databases with AWS Redshift using AWS Data Migration ServicePython
Based on your request, it seems like we will need several steps to accomplish this task as it involves a few different AWS services.
Here is the high-level overview:
Create an Amazon Redshift Cluster (using
pulumi_aws.redshift.Cluster). Your analytics workloads will run in this Redshift database.
Create an AWS DMS (Data Migration Service) instance (using
Create a DMS endpoint for both your on-premises database and the Redshift database (using
Create a DMS replication task (using
pulumi_aws.dms.ReplicationTask), that will defines the migration type and replication rules (replication job or chore).
Now let's put that into a Pulumi program.
The following is a rough skeleton for the Python Pulumi program. Please note that this is a high-level example and not a fully-working program. You need to provide appropriate configurations options replacing the TODOs.
table_mappingsattribute should follow AWS DMS's JSON format for table mappings (selecting schemas, tables, and columns, and specifying how to load and replicate data). You can find more information in the AWS DMS documentation.
For more detailed information about each resource, please visit their corresponding links:
Please replace all placeholders (such as
todo_replace_with_...) with appropriate values as per your environment.