Apply suggestions from code review

Co-authored-by: Anthony <russo555@gmail.com>
Co-authored-by: Brian McClain <brianmmcclain@gmail.com>

Author: 3 people

content/well-architected-framework/docs/docs/optimize-systems/manage-cost/create-cloud-budgets.mdx

@@ -66,8 +66,8 @@ resource "aws_budgets_budget" "ec2" {
 Some of the key components in the previous example include:
 
 - **limit_amount:** Defines the monthly spend limit.
-- **notification:** Defines the notification criteria and sends an email to test@example.com.
-- **tags:** The tag is applied to the budget resource, not the EC2 instance. The tags allow you to filter and organize budgets in the billing console.
+- **notification:** Defines the notification criteria, including the recipient email.
+- **tags:** Applies tags to the budget resource, not the EC2 instance. Tags allow you to filter and organize budgets in the billing console.
 
 For AWS environments, you can use the `aws_budgets_budget` resource to create budgets that track spending by service, linked account, tag, or other dimensions. You can specify the budget amount, time period, and notification thresholds. 
 
@@ -90,7 +90,7 @@ External resources:
 
 ## Detect spending anomalies
 
-Anomaly detection identifies unusual patterns rather than absolute thresholds. For example, if your monthly EC2 spending suddenly doubles from $2,000 to $4,000 but remains under your $5,000 budget, a budget alert would not trigger. However, anomaly detection would flag this unusual increase for investigation. Anomaly detection helps you catch issues like misconfigured autoscaling, forgotten resources, or unauthorized usage before they significantly impact costs.
+Anomaly detection identifies unusual spending patterns rather than absolute thresholds. For example, if your monthly EC2 spending suddenly doubles from $2,000 to $4,000 but remains under your $5,000 budget, a budget alert would not trigger. However, anomaly detection would flag this unusual increase for investigation. Anomaly detection helps you catch issues like misconfigured autoscaling, forgotten resources, or unauthorized usage before they significantly impact costs.
 
 Most cloud providers offer machine learning-based anomaly detection that learns your normal usage patterns and alerts you when spending deviates from the baseline. You can configure anomaly detection using Terraform for AWS Cost Anomaly Detection and Azure Cost Management.