Integrate Live AlloyDB Data into Amazon SageMaker Canvas with RDS

Amazon SageMaker Canvas is a no-code machine learning platform that lets you generate predictions, prepare data, and build models without writing code. When paired with CData Connect AI, you get instant, cloud-to-cloud access to AlloyDB data for building custom machine-learning models, predicting customer churn, generating texts, building chatbots, and more. This article shows how to connect to Connect AI from Amazon SageMaker Canvas using the RDS connector and integrate live AlloyDB data into your ML model deployments.

CData Connect AI provides a pure SQL, cloud-to-cloud interface for AlloyDB, allowing you to easily integrate with live AlloyDB data in Amazon SageMaker Canvas — without replicating the data. CData Connect AI looks exactly like a SQL Server database to Amazon SageMaker Canvas and uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc) directly to AlloyDB, leveraging server-side processing to quickly return AlloyDB data.

Configure AlloyDB Connectivity for Amazon SageMaker Canvas

Connectivity to AlloyDB from Amazon SageMaker Canvas is made possible through CData Connect AI. To work with AlloyDB data from Amazon SageMaker Canvas, we start by creating and configuring a AlloyDB connection.

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "AlloyDB" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to AlloyDB.

   The following connection properties are usually required in order to connect to AlloyDB.

   • Server: The host name or IP of the server hosting the AlloyDB database.
   • User: The user which will be used to authenticate with the AlloyDB server.
   • Password: The password which will be used to authenticate with the AlloyDB server.

   You can also optionally set the following:

   • Database: The database to connect to when connecting to the AlloyDB Server. If this is not set, the user's default database will be used.
   • Port: The port of the server hosting the AlloyDB database. This property is set to 5432 by default.

   Authenticating with Standard Authentication

   Standard authentication (using the user/password combination supplied earlier) is the default form of authentication.

   No further action is required to leverage Standard Authentication to connect.

   Authenticating with pg_hba.conf Auth Schemes

   There are additional methods of authentication available which must be enabled in the pg_hba.conf file on the AlloyDB server.

   Find instructions about authentication setup on the AlloyDB Server here.

   Authenticating with MD5 Authentication

   This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to md5.

   Authenticating with SASL Authentication

   This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to scram-sha-256.

   Authenticating with Kerberos

   The authentication with Kerberos is initiated by AlloyDB Server when the ∏ is trying to connect to it. You should set up Kerberos on the AlloyDB Server to activate this authentication method. Once you have Kerberos authentication set up on the AlloyDB Server, see the Kerberos section of the help documentation for details on how to authenticate with Kerberos. 👁 Configuring a connection (Salesforce is shown)
   

4. Click Save & Test
5. Navigate to the Permissions tab in the Add AlloyDB Connection page and update the User-based permissions. 👁 Updating permissions
   

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to AlloyDB data from Amazon SageMaker Canvas.

Connecting to CData Connect AI from Amazon SageMaker Canvas

With the connection in CData Connect AI configured, you are ready to integrate live AlloyDB data into Amazon SageMaker Canvas using its RDS connector.

1. Select a domain and user profile in Amazon SageMaker Canvas and click on "Open Canvas". 👁 Open SageMaker Canvas application
   
2. Once the Canvas application opens, navigate to the left panel, and select "My models". 👁 Select My models
   
3. Click on "Create new model" in the My models screen.
4. Specify a Model name in Create new model window and select a Problem type. Click on "Create". 👁 Create a new model
   
5. Once the model version gets created, click on "Create dataset" in the Select dataset tab. 👁 Select a dataset
   
6. In the Create a tabular dataset window, add a "Dataset name" and click on "Create". 👁 Create a tabular dataset
   
7. Click on the "Data Source" drop-down and search for or navigate to the RDS connector and click on " Add Connection". 👁 Select RDS connector
   
8. In the Add a new RDS connection window, set the following properties:
   
   
   • Connection Name: a relevant connection name
   • Set Engine type to sqlserver-web
   • Set Port to 14333
   • Set Address as tds.cdata.com
   • Set Username to a Connect AI user (e.g. [email protected])
   • Set Password to the PAT for the above user
   • Set Database name the AlloyDB connection (e.g., AlloyDB1) 👁 Create an RDS connection
     
9. Click on "Create connection".

Integrating AlloyDB Data into Amazon SageMaker Canvas

With the connection to Connect AI configured in the RDS, you are ready to integrate live AlloyDB data into your Amazon SageMaker Canvas dataset.

1. In the tabular dataset created in RDS with AlloyDB data, search for the AlloyDB connection configured on Connect AI in the search bar or from the list of connections. 👁 Search for the AlloyDB connection
   
2. Select the table of your choice from AlloyDB, drag and drop it into the canvas on the right. 👁 Select a table of your choice
   
3. You can create workflows by joining any number of tables from the AlloyDB connection (as shown below). Click on "Create dataset". 👁 Create the workflow and the dataset
   
4. Once the dataset is created, click on "Select dataset" to build your model. 👁 Select the dataset to build a model
   👁 Build a model from the dataset
   
5. Perform analysis, generate prediction, and deploy the model.

At this point, you have access to live AlloyDB data in Amazon SageMaker that you can utilize to build custom ML models to generate predictive business insights and grow your organization.

SQL Access to AlloyDB Data from Cloud Applications

Now you have a direct connection to live AlloyDB data from Amazon SageMaker Canvas. You can create more connections, datasets, and predictive models to drive business — all without replicating AlloyDB data.

To get real-time data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, see the CData Connect AI.