Redshift
Integrating Amazon Redshift with Upriver
Amazon Redshift is a fully managed, petabyte-scale data warehouse solution provided by Amazon Web Services (AWS). By integrating Redshift with Upriver, you can streamline data governance and maintain high data quality directly within your data warehouse. This integration enables efficient data monitoring, traceability, and consistency, ensuring your analytics and reporting pipelines remain accurate and reliable.
Prerequisites
To monitor Amazon Redshift with Upriver, you will need the following:
Provision AWS for Upriver operation.
Configure a Redshift integration in Upriver:
Create a Redshift user for Upriver.
Grant Upriver's user access to your Redshift.
Step 1: Provision AWS
Before connecting Redshift to Upriver, make sure your AWS account is properly set up. Follow the guidelines provided in this page to ensure correct setup.
Provisioning AWS for Redshift access is only needed in Hybrid/Outpost deployment methods.
Step 2: Configure Redshift integration in Upriver's Platform
Once your AWS account is set up, its time to configure a Redshift integration in the Upriver platform by providing the following the next steps:
Navigate to
Settings->Data Integrations, click "+ Add" in the top-right corner.Fill in basic settings:
Name - A user defined name.
Type - Type of integration. Redshift should be chosen.
In the Redshift console: Granting Upriver's user access to the Redshift instance:
SaaS
Select the region of the AWS account.
In your Redshift account under the desired cluster or workgroup:
Press "Grant access".
Enter the provided Uriver's Account ID and the VPC IDs.

Fill the connection details (from step 3):
Username: Upriver's Redshift username.
Password: Upriver's Redshift user's password.

Hybrid
Please set up a redshift-managed VPC endpoint according to the following guide by AWS. Alternatively, set the redshift as publicly accessible, and use security group/firewall to limit access as you wish. Connect to the VPC created by the cloud formation script (details available in the outputs of the cloud formation). Note that you'll need to create a security group allowing redshift access for that VPC yourself.
Fill in the connection details:
Host: The url of the host for your redshift. If you've set up a VPC endpoint, it's the host for that endpoint (for SaaS deployment - you'll receive the host from the Upriver representative). In a publicly accessible redshift, for serverless redshift, this is the host of the workgroup. For provisioned redshift, this is the cluster endpoint.
Port: The port used in the connection. By default, this is 5439.
User: Upriver's Redshift username as created on step 3.
Password: Upriver's Redshift user's password.

In the Redshift console: Create a Redshift user for Upriver: In order to connect to redshift, Upriver will need a user created in the database we the sufficient permissions. Run the following script in order to create a user called
upriver:Replace
<password>a desired password.Replace
<schema_name>with any schema you want to grant access to (can be more than one)For multiple schemas duplicate these rows and change the
<schema_name>accordingly.
Upriver supports different users for different hosts, however does not support different users for different databases/schemas accessed via the same host.
Insert the password back in Upriver platform.
For hybrid: insert the host and port as well.
Step 3: Configure the Data Source in Upriver's Platform
Now that your Amazon Redshift integration is set up, you can configure Data Sources to be monitored.
To do this:
Follow the instructions provided in Data Source Configuration section of the documentation.
When configuring a Amazon Redshift Data Source, choose the correct integration in the Connection step. The integration chosen should point to the Redshift instance that holds the relevant table you wish to monitor.
Provide the required Database, Schema and Table.
Continue with the rest of the configuration as needed.

Monitor and Manage Your Data
After configuring a Redshift datasource, Upriver will automatically monitor it for you. You can track data issues and enforce governance policies, ensuring your data is consistently accurate and trustworthy throughout the pipeline.
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