Amazon Machine Learning Console Now Makes It Easier to Connect to Amazon Redshift
You can now more easily set up or select your Identity and Access Management (IAM) role when connecting to an Amazon Redshift cluster from the Amazon Machine Learning (Amazon ML) console. To streamline the process of setting up your connection to Amazon Redshift, Amazon ML now pre-populates an interactive drop-down menu of existing IAM roles that have an Amazon ML managed policy for Amazon Redshift, and other IAM roles that you might prefer. From the Amazon ML console, you have the option of dynamically creating a new IAM role, enabling you to quickly connect to your Amazon Redshift cluster.
You can now more easily set up or select your Identity and Access Management (IAM) role when connecting to an Amazon Redshift cluster from the Amazon Machine Learning (Amazon ML) console. To streamline the process of setting up your connection to Amazon Redshift, Amazon ML now pre-populates an interactive drop-down menu of existing IAM roles that have an Amazon ML managed policy for Amazon Redshift, and other IAM roles that you might prefer. From the Amazon ML console, you have the option of dynamically creating a new IAM role, enabling you to quickly connect to your Amazon Redshift cluster.
In addition, you now have the ability to test the Amazon Redshift connection from Amazon ML, as part of the Amazon Redshift datasource creation through the console wizard. Once your Amazon Redshift connection parameters are entered – IAM role, cluster ID (name), database name, database username and database password – selecting the “Test Access” button will immediately attempt to create your Amazon Redshift connection with the parameters provided, without retrieving any data. You will be notified if the connection fails so you can easily make changes and quickly try again.
You can find more information about IAM role management and connection testing to Amazon Redshift in the Amazon Machine Learning documentation.