1. Storing Feature Data for Machine Learning Models on OCI MySQL


    To store feature data for Machine Learning models on Oracle Cloud Infrastructure (OCI) using a MySQL database, you will need to provision a MySQL DB System. With Pulumi, you can define your cloud resources using familiar programming languages and then deploy and manage those resources as part of your infrastructure as code practices.

    Here's what we are going to do:

    1. Set up a MySQL DB System: We will define an OCI MySQL DB System resource using Pulumi. This will serve as the database where you can store your feature data. We're using the oci.Mysql.MysqlDbSystem class for this.

    2. Configure Database Access: To access the database, we will define a username and a password. This will be set on the MySQL DB System we're creating. Credentials should be kept secure, hence we will use Pulumi's secret management.

    3. Exporting Connection Details: We will export the necessary information such as the instance's hostname and port, which can be used to connect to the MySQL database.

    Below is the Pulumi Python program that creates a MySQL DB System in OCI:

    import pulumi import pulumi_oci as oci # Create an Oracle Cloud Infrastructure MySQL DB System. mysql_db_system = oci.mysql.MysqlDbSystem("my-mysql-db-system", # The following are some example parameters. You will need to update them to match your OCI environment and requirements. # You can find all available parameters at https://www.pulumi.com/registry/packages/oci/api-docs/mysql/mysqldbsystem/ compartment_id='YOUR_OCI_COMPARTMENT_ID', # Replace with your Compartment ID. shape_name='MySQL.VM.Standard.E3.1.4GB', # Shape is chosen based on needed compute and memory for your workload. admin_username='myadmin', # Define the admin username. admin_password=oci.mysql.DbSystemAdminPasswordArgs( secret='my$ecureP@ssw0rd' # Set a secure password. This is marked as a secret. ), data_storage_size_in_gb=50, # Define the size of the data storage. mysql_version='8.0.28', # Specify the version of MySQL. subnet_id='YOUR_OCI_SUBNET_ID', # Replace with your Subnet ID. ) # Export important connection details that you will need to connect to the database. pulumi.export('mysql_db_system_hostname', mysql_db_system.hostname) pulumi.export('mysql_db_system_port', mysql_db_system.port)

    Before running this program:

    • Replace 'YOUR_OCI_COMPARTMENT_ID' and 'YOUR_OCI_SUBNET_ID' with the appropriate ID values for your OCI Compartment and Subnet.
    • Update the shape_name if you require a different compute or memory requirements.
    • Use a strong, secure password for your admin user. Pulumi handles this as a secret, keeping it out of plaintext files or console output.

    After you run this program with pulumi up, Pulumi will provision a new MySQL DB System in your OCI environment. The admin username, hostname, and the port of the MySQL DB system will be outputted by Pulumi, which you can use to connect to your database and begin storing feature data for your machine learning models.

    Keep in mind, the actual insertion and management of the data within the MySQL database will require additional steps and potentially other tools or services, depending on your requirements, such as setting up schemas, tables, and insertion queries. Pulumi is flexible and can be integrated with CI/CD pipelines for automated deployment and management.