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Creating and Connecting to an Aurora Serverless Database via CLI

Aurora Serverless is an excellent choice for your relational database workloads without needing to worry about scaling, disaster recovery, or maintenance. In this lab, we use the AWS CLI to create an Aurora Serverless (MySQL) database and show how we can run queries against it using the RDS Data API. All of this will be done from the command line.

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Path Info

Level
Clock icon Intermediate
Duration
Clock icon 45m
Published
Clock icon Nov 01, 2019

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Table of Contents

  1. Challenge

    Create Aurora Serverless DB Cluster

    1. Run the following command, replacing <DB_SUBNET_NAME> with the database subnet group name provided on the lab page:

      aws rds create-db-cluster --engine-version 5.7 --db-cluster-identifier serverlessdb --engine-mode serverless --engine aurora-mysql --master-username <USERNAME> --master-user-password <SECURE_PASSWORD> --db-subnet-group-name <DB_SUBNET_NAME> --scaling-configuration MinCapacity=2,MaxCapacity=4,AutoPause=false,TimeoutAction=ForceApplyCapacityChange --enable-http-endpoint --region us-east-1

  2. Challenge

    Create a Secret in Secrets Manager for DB Credentials

    1. Create a secret in Secrets Manager, replacing <USERNAME> and <SECURE_PASSWORD> with the credentials you set in the previous command:

      aws secretsmanager create-secret --name "ServerlessDBSecret" --description "Credentials for serverless DB" --secret-string '{"username":"<USERNAME>" , "password":"<SECURE_PASSWORD>"}' --region us-east-1

  3. Challenge

    Connect to and Execute SQL Query Against Your Provisioned Serverless Aurora DB Instance

    1. Connect to and execute a SQL query against the provisioned Aurora Serverless DB instance:

      aws rds-data execute-statement --resource-arn <DB_CLUSTER_ARN> --secret-arn <SECRET_ARN> --database information_schema --sql "select * from information_schema.tables LIMIT 1" --region us-east-1

    Note: The command requires the DB cluster ARN and Secrets Manager secret ARN you provisioned in previous tasks. You can get them via the AWS Management Console or when you executed the CLI commands to create these resources.

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