1. Automated Email Notifications for Model Training Completion with AWS SES

    Python

    To set up automated email notifications for model training completion using AWS Simple Email Service (AWS SES), you will need to follow these steps:

    1. Verify Email Addresses or Domains: Before you can send an email with AWS SES, you need to verify the email addresses or domain that you'll use to send emails. This is a necessary step to ensure that you're the owner of the email address or domain.

    2. Create an IAM User and Policies: You'll require an IAM user with permissions to send emails using SES. This user will be used by your application or script that triggers the email notification upon model training completion.

    3. Set up AWS SES: You need to configure AWS SES with the necessary settings such as email format, content, recipient, and sender.

    4. Trigger Email Notification: Implement a mechanism within your model training process to trigger an email sending function when the training is complete.

    5. Handle Bounces and Complaints: Optionally, you can set up mechanisms to handle bounces and complaints to maintain a good sender reputation.

    In this program, we'll focus on setting up SES to send an email notification. We will define a sender and recipient email addresses, subject, and body for the email. We will also demonstrate how to send an email. However, we will not cover the actual model training part or the event that triggers this email.

    Here is how you can set up automated email notifications with Pulumi and AWS SES:

    import json import pulumi import pulumi_aws as aws # Step 1: Verify an email address. This is the email address that will send the notification. # In a real-world case, this address should be verified with AWS. Here we are using an example address. # You must replace it with a verified address. sender_email = "sender@example.com" # Verify a new email address (replace with your email to receive notifications). verification = aws.ses.EmailIdentity("emailVerification", email=sender_email) # Step 2: Specify the recipient email address for the notification. # This should also be a verified email address. recipient_email = "recipient@example.com" # Step 3: Create the SES email template. # You would typically have a template for emails that are sent regularly. # Replace 'Subject Part' and 'HTML Part' with your actual content. template = aws.ses.EmailTemplate("emailTemplate", subject_part="Model Training Completion Notification", html_part="<h1>Model Training Completed</h1><p>The model training has finished successfully.</p>", text_part="Your model training has finished successfully." ) # Step 4: When your model training is completed, you will trigger the sending of this email. # Here we define the python function which can be used to send email via AWS SES. # This is a placeholder for the actual trigger mechanism which will be part of your model training script. def send_notification(): # Sending the email using the earlier verified email and the created template. # Here we are dynamically creating the SendEmail resource, in real case, you would # replace 'json_input' with actual dynamic data for your use case. json_input = { "ToAddresses": [recipient_email], } email_sending = aws.ses.SendEmail("sendNotification", source=sender_email, destination={ "to_addresses": [recipient_email] }, message={ "subject": {"data": "Model Training Completion Notification"}, "body": { "text": {"data": "Your model training has finished successfully."}, "html": {"data": "<h1>Model Training Completed</h1><p>The model training has finished successfully.</p>"} } }, template=template.name, template_data=json.dumps(json_input) ) return email_sending # Trigger the email sending function (you'll replace this with your actual model training completion event). send_notification() # Export the verification status and email sending resource. pulumi.export("verificationStatus", verification.verification_status) pulumi.export("notificationEmailId", send_notification().id)

    This code sets up the necessary AWS SES resources to send an email and defines a send_notification function that actually sends the email when called. The process of verifying email addresses is skipped here for clarity but is a required step in any SES setup.

    To make this work in a real-world scenario, you should trigger the send_notification function upon completion of your model training. The triggering mechanism might include monitoring a file in an S3 bucket, database update, or an event from AWS Lambda.

    Remember to replace sender@example.com and recipient@example.com with actual verified sender and recipient email addresses. Additionally, customize your email content in the html_part and subject_part appropriately for your needs.

    The pulumi.export statements at the end of the program are used to output the created resources' important attributes, including the verification status of the email identity and the unique identifier of the sent email. This is helpful for debugging and logging purposes, especially when automating this process.


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