Automatic Autoscaling Tagging from Database Cluster

Currently, Aurora Autoscaling does not extend the cluster tags to the Read-Replicas dynamically created. Customers would like to extend cluster tags to all autoscaling read replicas created from "Add Replica Auto Scaling" for several reasons,such as cost allocation purposes.

How does it work?

When the autoscaling read replica is created, a CreateDBInstance event is generated and it can be captured by EventBridge with the corresponding rule. The rule will trigger a lambda function that makes some checks to verify if it is an autoscaling event. Then, it extracts the cluster name from the autoscaling instance event Tags, to retrieve the corresponding cluster identifier to read the tags which are applied to the autoscaling instance.

Instructions

Deploy via CloudFormation template

This sample can be setup via CloudFormation templates available in YAML or JSON. Create the stack with "Upload Template File" to upload the corresponding YAML or JSON. Review the resulting services configured.

Manual deploy

Step 1. Create a new policy

Create a new IAM policy autoscaling-tagging-policy to allow the following actions related to RDS. Replace AWSREGION and AWSACCOUNT in the policy below, with the corresponding region and account ID it will run on

 {
     "Version": "2012-10-17",
     "Statement": [
         {
             "Sid": "Autoscaling",
             "Effect": "Allow",
             "Action": [
                 "rds:AddTagsToResource",
                 "rds:DescribeDBInstances",
                 "rds:ListTagsForResource"
             ],
             "Resource": "arn:aws:rds:AWSREGION:AWSACCOUNT:db:application-autoscaling-*"
         },
         {
             "Sid": "Cluster",
             "Effect": "Allow",
             "Action": [
                 "rds:DescribeDBClusters",
                 "rds:ListTagsForResource"
             ],
             "Resource": "arn:aws:rds:**AWSREGION**:**AWSACCOUNT**:cluster:*"
         }
     ]
}

Step 2. Create a Lambda function

Create a Lambda with

• Function name: aurora-autoscaling-tagging-from-cluster
• Runtime: Python 3.12

while leaving the other parameters as default. Once the function has been created, copy the code available in automatic-autoscaling-tagging-from-dabatase-cluster.py and paste it in the lambda Code tab, then press Deploy to commit the changes.

Then, move into the Lambda configuration tab, on the left select the Permissions and click on the Role name which looks like automatic-autoscaling-tagging-from-dabatase-cluste-role-a1b2c3d4, click on Attach Policy, type in the search bar autoscaling-tagging-policy, tick the policy called autoscaling-tagging-policy and press "Add permissions". The lambda should have the default permissions for writing logs into CloudWatch.

Step 3. Create an EventBridge rule

Go to EventBridge, select Rule on the left menu and press Create Rule. Define the Rule detail as follow:

• Name: Create-DB-Instance-Rule
• Event bus: default
• Rule type: Rule with an event pattern

Press Next. Now, scroll down to Event pattern and press Edit Pattern pasting the following rule

{
  "source": ["aws.rds"],
  "detail-type": ["RDS DB Instance Event"],
  "detail": {
    "EventCategories": ["creation"],
    "SourceType": ["DB_INSTANCE"],
    "Message": ["DB instance created"],
    "EventID": ["RDS-EVENT-0005"]
  }
}

Click on {}Prettify and click Next.

In the Select target(s) window

• Target Type: AWS service
• Select Target: Lambda Function
• Function: aurora-autoscaling-tagging-from-cluster

press Next, and again Next, review the rule and press Finish.

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.