Navigate to AWS Console > S3 and click on Create bucket. Create the bucket with the default settings.

Once inside the bucket, click on Upload > Add files and select Utilities.zip from the cloned GitHub repository on your system.

Navigate to AWS Console > AWS Simple Email Service (SES) > SMTP Settings and click on Create SMTP credentials

Enter an IAM User Name or leave it at the default value and click on Create User. Save the SMTP user name and SMTP password for further use.

Skip this step if SES SMTP setup is already in place.

Navigate to AWS Console > CloudFormation > Create stack > With New Resources (Standard).

Prepare template: Template is ready
Specify template: Upload a template file
Choose file: Browse to the cloned GitHub repo and select fsxn-monitoring-solution.yaml

Enter the stack details. Click on Next and check the checkbox for "I acknowledge that AWS CloudFormation might create IAM resources" and click on Submit.

If "Does VPC have internet access?" is set to False, "SMTP Username for AWS SES" and "SMTP Password for AWS SES" are required. Otherwise, they can be left empty.

Once the CloudFormation deployment starts, the email ID mentioned in the "sender email ID" will get an email asking them to authorize the use of the email address with AWS SES. Click on the link to verify the email address.

Once the CloudFormation stack deployment is completed, if there are any warnings/notifications, an email will be sent to the recipient email ID with the notification details.

Navigate to AWS Console > AWS Simple Email Service (SES) > SMTP Settings and click on Create SMTP credentials

Enter an IAM User Name or leave it at the default value and click on Create. Save the username and password for further use.

Navigate to AWS Console > VPC > Endpoints and click on Create Endpoint and enter the following details:

Name: <Any name for the vpc endpoint>
Service category: AWS Services
Services: com.amazonaws.<region>.fsx
vpc: <select the vpc where lambda will be deployed>
subnets: <select the subnets where lambda will be deployed>
Security groups: <select the security group>
Policy: <Either choose Full access or set your own custom policy>

Follow the same process for creating SES and SSM VPC endpoints. All parameters remain the same as above except Services which will correspond to com.amazonaws.<region>.smtp and com.amazonaws.<region>.ssm respectively.

Navigate to AWS Console > AWS Lambda > Functions and click on Create function in the same region as FSx ONTAP

Use the default Author from scratch and update the following fields:

Function name: <Any name of your choice>
Runtime: Python 3.9
Architecture: x86_64
Permissions: Select "Create a new role with basic Lambda permissions"
Advanced Settings:
  Enable VPC: Checked
    VPC: <Choose either the same VPC as FSx ONTAP or a VPC that can access both FSx ONTAP and the internet via a private subnet>
    Subnets: <Choose 2 private subnets that have NAT gateway attached pointing to public subnets with internet gateway and subnets that have internet access>
    Security Group: <Choose a Security Group>

Navigate to the newly created Lambda function > Scroll down to the Layers section and click on Add a layer.

Click on create a new layer under Layer source

Create a Layer and upload Utilities.zip file. Select Python 3.9 as the compatible runtime and click on Create.

Navigate back to AWS Lambda function > Add Layer > Custom Layers and add the utilities layer.

Navigate to the Configuration tab of the Lambda function and click on Edit under General Configuration. Change the Timeout to 5 mins and click Save.

Navigate to Permissions tab of the Lambda function and click on the role assigned. In the permissions tab of the role, click on Add permissions > Create Inline policy.

Copy the contents of fsxn_monitoring_resizing_lambda.py from the git repo to lambda_function.py in the AWS Lambda function Code Source section.

Create a new file in the same level as lambda_function.py and name it vars.py and copy the contents of vars.py from the git repo to the lambda function vars.py file. Update the variable values in vars.py. Reference variable definitions below and click on Deploy:

Click on Test, create a test event with an empty JSON object and run the test by clicking Invoke to check if the script is running properly.

Once tested successfully, navigate to Configuration > Triggers > Add Trigger.

Select a Source: EventBridge
Rule: Create a new rule
Rule name: <Enter any name>
Rule type: Schedule expression
Schedule expression: <Use "rate(1 day)" if you want the function to run daily or add your own cron expression>