Amazon Relational Database Service Construct Library
import * as rds from '@aws-cdk/aws-rds';
Starting a clustered database
To set up a clustered database (like Aurora), define a DatabaseCluster
. You must
always launch a database in a VPC. Use the vpcSubnets
attribute to control whether
your instances will be launched privately or publicly:
declare const vpc: ec2.Vpc;
const cluster = new rds.DatabaseCluster(this, 'Database', {
engine: rds.DatabaseClusterEngine.auroraMysql({ version: rds.AuroraMysqlEngineVersion.VER_2_08_1 }),
credentials: rds.Credentials.fromGeneratedSecret('clusteradmin'),
instanceProps: {
instanceType: ec2.InstanceType.of(ec2.InstanceClass.BURSTABLE2, ec2.InstanceSize.SMALL),
vpcSubnets: {
subnetType: ec2.SubnetType.PRIVATE_WITH_NAT,
},
vpc,
},
});
If there isn't a constant for the exact version you want to use,
all of the Version
classes have a static of
method that can be used to create an arbitrary version.
const customEngineVersion = rds.AuroraMysqlEngineVersion.of('5.7.mysql_aurora.2.08.1');
By default, the master password will be generated and stored in AWS Secrets Manager with auto-generated description.
Your cluster will be empty by default. To add a default database upon construction, specify the
defaultDatabaseName
attribute.
Use DatabaseClusterFromSnapshot
to create a cluster from a snapshot:
declare const vpc: ec2.Vpc;
new rds.DatabaseClusterFromSnapshot(this, 'Database', {
engine: rds.DatabaseClusterEngine.aurora({ version: rds.AuroraEngineVersion.VER_1_22_2 }),
instanceProps: {
vpc,
},
snapshotIdentifier: 'mySnapshot',
});
Starting an instance database
To set up a instance database, define a DatabaseInstance
. You must
always launch a database in a VPC. Use the vpcSubnets
attribute to control whether
your instances will be launched privately or publicly:
declare const vpc: ec2.Vpc;
const instance = new rds.DatabaseInstance(this, 'Instance', {
engine: rds.DatabaseInstanceEngine.oracleSe2({ version: rds.OracleEngineVersion.VER_19_0_0_0_2020_04_R1 }),
instanceType: ec2.InstanceType.of(ec2.InstanceClass.BURSTABLE3, ec2.InstanceSize.SMALL),
credentials: rds.Credentials.fromGeneratedSecret('syscdk'),
vpc,
vpcSubnets: {
subnetType: ec2.SubnetType.PRIVATE_WITH_NAT,
}
});
If there isn't a constant for the exact engine version you want to use,
all of the Version
classes have a static of
method that can be used to create an arbitrary version.
const customEngineVersion = rds.OracleEngineVersion.of('19.0.0.0.ru-2020-04.rur-2020-04.r1', '19');
By default, the master password will be generated and stored in AWS Secrets Manager.
To use the storage auto scaling option of RDS you can specify the maximum allocated storage.
This is the upper limit to which RDS can automatically scale the storage. More info can be found
here
Example for max storage configuration:
declare const vpc: ec2.Vpc;
const instance = new rds.DatabaseInstance(this, 'Instance', {
engine: rds.DatabaseInstanceEngine.postgres({ version: rds.PostgresEngineVersion.VER_12_3 }),
instanceType: ec2.InstanceType.of(ec2.InstanceClass.BURSTABLE2, ec2.InstanceSize.SMALL),
vpc,
maxAllocatedStorage: 200,
});
Use DatabaseInstanceFromSnapshot
and DatabaseInstanceReadReplica
to create an instance from snapshot or
a source database respectively:
declare const vpc: ec2.Vpc;
new rds.DatabaseInstanceFromSnapshot(this, 'Instance', {
snapshotIdentifier: 'my-snapshot',
engine: rds.DatabaseInstanceEngine.postgres({ version: rds.PostgresEngineVersion.VER_12_3 }),
instanceType: ec2.InstanceType.of(ec2.InstanceClass.BURSTABLE2, ec2.InstanceSize.LARGE),
vpc,
});
declare const sourceInstance: rds.DatabaseInstance;
new rds.DatabaseInstanceReadReplica(this, 'ReadReplica', {
sourceDatabaseInstance: sourceInstance,
instanceType: ec2.InstanceType.of(ec2.InstanceClass.BURSTABLE2, ec2.InstanceSize.LARGE),
vpc,
});
Automatic backups of read replica instances are only supported for MySQL and MariaDB. By default,
automatic backups are disabled for read replicas and can only be enabled (using backupRetention
)
if also enabled on the source instance.
Creating a "production" Oracle database instance with option and parameter groups:
example of setting up a production oracle instance
Setting Public Accessibility
You can set public accessibility for the database instance or cluster using the publiclyAccessible
property.
If you specify true
, it creates an instance with a publicly resolvable DNS name, which resolves to a public IP address.
If you specify false
, it creates an internal instance with a DNS name that resolves to a private IP address.
The default value depends on vpcSubnets
.
It will be true
if vpcSubnets
is subnetType: SubnetType.PUBLIC
, false
otherwise.
declare const vpc: ec2.Vpc;
new rds.DatabaseInstance(this, 'Instance', {
engine: rds.DatabaseInstanceEngine.mysql({
version: rds.MysqlEngineVersion.VER_8_0_19,
}),
vpc,
vpcSubnets: {
subnetType: ec2.SubnetType.PRIVATE_WITH_NAT,
},
publiclyAccessible: true,
});
new rds.DatabaseCluster(this, 'DatabaseCluster', {
engine: rds.DatabaseClusterEngine.AURORA,
instanceProps: {
vpc,
vpcSubnets: {
subnetType: ec2.SubnetType.PRIVATE_WITH_NAT,
},
publiclyAccessible: true,
},
});
Instance events
To define Amazon CloudWatch event rules for database instances, use the onEvent
method:
declare const instance: rds.DatabaseInstance;
declare const fn: lambda.Function;
const rule = instance.onEvent('InstanceEvent', { target: new targets.LambdaFunction(fn) });
Login credentials
By default, database instances and clusters (with the exception of DatabaseInstanceFromSnapshot
and ServerlessClusterFromSnapshot
) will have admin
user with an auto-generated password.
An alternative username (and password) may be specified for the admin user instead of the default.
The following examples use a DatabaseInstance
, but the same usage is applicable to DatabaseCluster
.
declare const vpc: ec2.Vpc;
const engine = rds.DatabaseInstanceEngine.postgres({ version: rds.PostgresEngineVersion.VER_12_3 });
new rds.DatabaseInstance(this, 'InstanceWithUsername', {
engine,
vpc,
credentials: rds.Credentials.fromGeneratedSecret('postgres'),
});
new rds.DatabaseInstance(this, 'InstanceWithUsernameAndPassword', {
engine,
vpc,
credentials: rds.Credentials.fromPassword('postgres', SecretValue.ssmSecure('/dbPassword', '1')),
});
const mySecret = secretsmanager.Secret.fromSecretName(this, 'DBSecret', 'myDBLoginInfo');
new rds.DatabaseInstance(this, 'InstanceWithSecretLogin', {
engine,
vpc,
credentials: rds.Credentials.fromSecret(mySecret),
});
Secrets generated by fromGeneratedSecret()
can be customized:
declare const vpc: ec2.Vpc;
const engine = rds.DatabaseInstanceEngine.postgres({ version: rds.PostgresEngineVersion.VER_12_3 });
const myKey = new kms.Key(this, 'MyKey');
new rds.DatabaseInstance(this, 'InstanceWithCustomizedSecret', {
engine,
vpc,
credentials: rds.Credentials.fromGeneratedSecret('postgres', {
secretName: 'my-cool-name',
encryptionKey: myKey,
excludeCharacters: '!&*^#@()',
replicaRegions: [{ region: 'eu-west-1' }, { region: 'eu-west-2' }],
}),
});
Snapshot credentials
As noted above, Databases created with DatabaseInstanceFromSnapshot
or ServerlessClusterFromSnapshot
will not create user and auto-generated password by default because it's not possible to change the master username for a snapshot. Instead, they will use the existing username and password from the snapshot. You can still generate a new password - to generate a secret similarly to the other constructs, pass in credentials with fromGeneratedSecret()
or fromGeneratedPassword()
.
declare const vpc: ec2.Vpc;
const engine = rds.DatabaseInstanceEngine.postgres({ version: rds.PostgresEngineVersion.VER_12_3 });
const myKey = new kms.Key(this, 'MyKey');
new rds.DatabaseInstanceFromSnapshot(this, 'InstanceFromSnapshotWithCustomizedSecret', {
engine,
vpc,
snapshotIdentifier: 'mySnapshot',
credentials: rds.SnapshotCredentials.fromGeneratedSecret('username', {
encryptionKey: myKey,
excludeCharacters: '!&*^#@()',
replicaRegions: [{ region: 'eu-west-1' }, { region: 'eu-west-2' }],
}),
});
Connecting
To control who can access the cluster or instance, use the .connections
attribute. RDS databases have
a default port, so you don't need to specify the port:
declare const cluster: rds.DatabaseCluster;
cluster.connections.allowFromAnyIpv4(ec2.Port.allTraffic(), 'Open to the world');
The endpoints to access your database cluster will be available as the .clusterEndpoint
and .readerEndpoint
attributes:
declare const cluster: rds.DatabaseCluster;
const writeAddress = cluster.clusterEndpoint.socketAddress;
For an instance database:
declare const instance: rds.DatabaseInstance;
const address = instance.instanceEndpoint.socketAddress;
Rotating credentials
When the master password is generated and stored in AWS Secrets Manager, it can be rotated automatically:
import * as cdk from '@aws-cdk/core';
declare const instance: rds.DatabaseInstance;
instance.addRotationSingleUser({
automaticallyAfter: cdk.Duration.days(7),
excludeCharacters: '!@#$%^&*',
});
example of setting up master password rotation for a cluster
The multi user rotation scheme is also available:
declare const instance: rds.DatabaseInstance;
declare const myImportedSecret: rds.DatabaseSecret;
instance.addRotationMultiUser('MyUser', {
secret: myImportedSecret,
});
It's also possible to create user credentials together with the instance/cluster and add rotation:
declare const instance: rds.DatabaseInstance;
const myUserSecret = new rds.DatabaseSecret(this, 'MyUserSecret', {
username: 'myuser',
secretName: 'my-user-secret',
masterSecret: instance.secret,
excludeCharacters: '{}[]()\'"/\\',
});
const myUserSecretAttached = myUserSecret.attach(instance);
instance.addRotationMultiUser('MyUser', {
secret: myUserSecretAttached,
});
Note: This user must be created manually in the database using the master credentials.
The rotation will start as soon as this user exists.
Access to the Secrets Manager API is required for the secret rotation. This can be achieved either with
internet connectivity (through NAT) or with a VPC interface endpoint. By default, the rotation Lambda function
is deployed in the same subnets as the instance/cluster. If access to the Secrets Manager API is not possible from
those subnets or using the default API endpoint, use the vpcSubnets
and/or endpoint
options:
declare const instance: rds.DatabaseInstance;
declare const myEndpoint: ec2.InterfaceVpcEndpoint;
instance.addRotationSingleUser({
vpcSubnets: { subnetType: ec2.SubnetType.PRIVATE_WITH_NAT },
endpoint: myEndpoint,
});
See also @aws-cdk/aws-secretsmanager for credentials rotation of existing clusters/instances.
IAM Authentication
You can also authenticate to a database instance using AWS Identity and Access Management (IAM) database authentication;
See https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/UsingWithRDS.IAMDBAuth.html for more information
and a list of supported versions and limitations.
Note: grantConnect()
does not currently work - see this GitHub issue.
The following example shows enabling IAM authentication for a database instance and granting connection access to an IAM role.
declare const vpc: ec2.Vpc;
const instance = new rds.DatabaseInstance(this, 'Instance', {
engine: rds.DatabaseInstanceEngine.mysql({ version: rds.MysqlEngineVersion.VER_8_0_19 }),
vpc,
iamAuthentication: true,
});
const role = new iam.Role(this, 'DBRole', { assumedBy: new iam.AccountPrincipal(this.account) });
instance.grantConnect(role);
The following example shows granting connection access for RDS Proxy to an IAM role.
declare const vpc: ec2.Vpc;
const cluster = new rds.DatabaseCluster(this, 'Database', {
engine: rds.DatabaseClusterEngine.AURORA,
instanceProps: { vpc },
});
const proxy = new rds.DatabaseProxy(this, 'Proxy', {
proxyTarget: rds.ProxyTarget.fromCluster(cluster),
secrets: [cluster.secret!],
vpc,
});
const role = new iam.Role(this, 'DBProxyRole', { assumedBy: new iam.AccountPrincipal(this.account) });
proxy.grantConnect(role, 'admin');
Note: In addition to the setup above, a database user will need to be created to support IAM auth.
See https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/UsingWithRDS.IAMDBAuth.DBAccounts.html for setup instructions.
Kerberos Authentication
You can also authenticate using Kerberos to a database instance using AWS Managed Microsoft AD for authentication;
See https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/kerberos-authentication.html for more information
and a list of supported versions and limitations.
The following example shows enabling domain support for a database instance and creating an IAM role to access
Directory Services.
declare const vpc: ec2.Vpc;
const role = new iam.Role(this, 'RDSDirectoryServicesRole', {
assumedBy: new iam.ServicePrincipal('rds.amazonaws.com'),
managedPolicies: [
iam.ManagedPolicy.fromAwsManagedPolicyName('service-role/AmazonRDSDirectoryServiceAccess'),
],
});
const instance = new rds.DatabaseInstance(this, 'Instance', {
engine: rds.DatabaseInstanceEngine.mysql({ version: rds.MysqlEngineVersion.VER_8_0_19 }),
vpc,
domain: 'd-????????',
domainRole: role,
});
Note: In addition to the setup above, you need to make sure that the database instance has network connectivity
to the domain controllers. This includes enabling cross-VPC traffic if in a different VPC and setting up the
appropriate security groups/network ACL to allow traffic between the database instance and domain controllers.
Once configured, see https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/kerberos-authentication.html for details
on configuring users for each available database engine.
Metrics
Database instances and clusters both expose metrics (cloudwatch.Metric
):
declare const instance: rds.DatabaseInstance;
const dbConnections = instance.metricDatabaseConnections();
declare const cluster: rds.DatabaseCluster;
const cpuUtilization = cluster.metricCPUUtilization();
const readLatency = instance.metric('ReadLatency', { statistic: 'Average', period: Duration.seconds(60) });
Enabling S3 integration
Data in S3 buckets can be imported to and exported from certain database engines using SQL queries. To enable this
functionality, set the s3ImportBuckets
and s3ExportBuckets
properties for import and export respectively. When
configured, the CDK automatically creates and configures IAM roles as required.
Additionally, the s3ImportRole
and s3ExportRole
properties can be used to set this role directly.
You can read more about loading data to (or from) S3 here:
The following snippet sets up a database cluster with different S3 buckets where the data is imported and exported -
import * as s3 from '@aws-cdk/aws-s3';
declare const vpc: ec2.Vpc;
const importBucket = new s3.Bucket(this, 'importbucket');
const exportBucket = new s3.Bucket(this, 'exportbucket');
new rds.DatabaseCluster(this, 'dbcluster', {
engine: rds.DatabaseClusterEngine.AURORA,
instanceProps: {
vpc,
},
s3ImportBuckets: [importBucket],
s3ExportBuckets: [exportBucket],
});
Creating a Database Proxy
Amazon RDS Proxy sits between your application and your relational database to efficiently manage
connections to the database and improve scalability of the application. Learn more about at Amazon RDS Proxy
The following code configures an RDS Proxy for a DatabaseInstance
.
declare const vpc: ec2.Vpc;
declare const securityGroup: ec2.SecurityGroup;
declare const secrets: secretsmanager.Secret[];
declare const dbInstance: rds.DatabaseInstance;
const proxy = dbInstance.addProxy('proxy', {
borrowTimeout: Duration.seconds(30),
maxConnectionsPercent: 50,
secrets,
vpc,
});
Exporting Logs
You can publish database logs to Amazon CloudWatch Logs. With CloudWatch Logs, you can perform real-time analysis of the log data,
store the data in highly durable storage, and manage the data with the CloudWatch Logs Agent. This is available for both database
instances and clusters; the types of logs available depend on the database type and engine being used.
import * as logs from '@aws-cdk/aws-logs';
declare const myLogsPublishingRole: iam.Role;
declare const vpc: ec2.Vpc;
const cluster = new rds.DatabaseCluster(this, 'Database', {
engine: rds.DatabaseClusterEngine.aurora({
version: rds.AuroraEngineVersion.VER_1_17_9,
}),
instanceProps: {
vpc,
},
cloudwatchLogsExports: ['error', 'general', 'slowquery', 'audit'],
cloudwatchLogsRetention: logs.RetentionDays.THREE_MONTHS,
cloudwatchLogsRetentionRole: myLogsPublishingRole,
});
const instance = new rds.DatabaseInstance(this, 'Instance', {
engine: rds.DatabaseInstanceEngine.postgres({
version: rds.PostgresEngineVersion.VER_12_3,
}),
vpc,
cloudwatchLogsExports: ['postgresql'],
});
Option Groups
Some DB engines offer additional features that make it easier to manage data and databases, and to provide additional security for your database.
Amazon RDS uses option groups to enable and configure these features. An option group can specify features, called options,
that are available for a particular Amazon RDS DB instance.
declare const vpc: ec2.Vpc;
declare const securityGroup: ec2.SecurityGroup;
new rds.OptionGroup(this, 'Options', {
engine: rds.DatabaseInstanceEngine.oracleSe2({
version: rds.OracleEngineVersion.VER_19,
}),
configurations: [
{
name: 'OEM',
port: 5500,
vpc,
securityGroups: [securityGroup],
},
],
});
Parameter Groups
Database parameters specify how the database is configured.
For example, database parameters can specify the amount of resources, such as memory, to allocate to a database.
You manage your database configuration by associating your DB instances with parameter groups.
Amazon RDS defines parameter groups with default settings.
You can create your own parameter group for your cluster or instance and associate it with your database:
declare const vpc: ec2.Vpc;
const parameterGroup = new rds.ParameterGroup(this, 'ParameterGroup', {
engine: rds.DatabaseInstanceEngine.sqlServerEe({
version: rds.SqlServerEngineVersion.VER_11,
}),
parameters: {
locks: '100',
},
});
new rds.DatabaseInstance(this, 'Database', {
engine: rds.DatabaseInstanceEngine.SQL_SERVER_EE,
vpc,
parameterGroup,
});
Another way to specify parameters is to use the inline field parameters
that creates an RDS parameter group for you.
You can use this if you do not want to reuse the parameter group instance for different instances:
declare const vpc: ec2.Vpc;
new rds.DatabaseInstance(this, 'Database', {
engine: rds.DatabaseInstanceEngine.sqlServerEe({ version: rds.SqlServerEngineVersion.VER_11 }),
vpc,
parameters: {
locks: '100',
},
});
You cannot specify a parameter map and a parameter group at the same time.
Serverless
Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon
Aurora. The database will automatically start up, shut down, and scale capacity
up or down based on your application's needs. It enables you to run your database
in the cloud without managing any database instances.
The following example initializes an Aurora Serverless PostgreSql cluster.
Aurora Serverless clusters can specify scaling properties which will be used to
automatically scale the database cluster seamlessly based on the workload.
declare const vpc: ec2.Vpc;
const cluster = new rds.ServerlessCluster(this, 'AnotherCluster', {
engine: rds.DatabaseClusterEngine.AURORA_POSTGRESQL,
parameterGroup: rds.ParameterGroup.fromParameterGroupName(this, 'ParameterGroup', 'default.aurora-postgresql10'),
vpc,
scaling: {
autoPause: Duration.minutes(10),
minCapacity: rds.AuroraCapacityUnit.ACU_8,
maxCapacity: rds.AuroraCapacityUnit.ACU_32,
}
});
Aurora Serverless Clusters do not support the following features:
- Loading data from an Amazon S3 bucket
- Saving data to an Amazon S3 bucket
- Invoking an AWS Lambda function with an Aurora MySQL native function
- Aurora replicas
- Backtracking
- Multi-master clusters
- Database cloning
- IAM database cloning
- IAM database authentication
- Restoring a snapshot from MySQL DB instance
- Performance Insights
- RDS Proxy
Read more about the limitations of Aurora Serverless
Learn more about using Amazon Aurora Serverless by reading the documentation
Use ServerlessClusterFromSnapshot
to create a serverless cluster from a snapshot:
declare const vpc: ec2.Vpc;
new rds.ServerlessClusterFromSnapshot(this, 'Cluster', {
engine: rds.DatabaseClusterEngine.AURORA_MYSQL,
vpc,
snapshotIdentifier: 'mySnapshot',
});
Data API
You can access your Aurora Serverless DB cluster using the built-in Data API. The Data API doesn't require a persistent connection to the DB cluster. Instead, it provides a secure HTTP endpoint and integration with AWS SDKs.
The following example shows granting Data API access to a Lamba function.
declare const vpc: ec2.Vpc;
const cluster = new rds.ServerlessCluster(this, 'AnotherCluster', {
engine: rds.DatabaseClusterEngine.AURORA_MYSQL,
vpc,
enableDataApi: true,
});
declare const code: lambda.Code;
const fn = new lambda.Function(this, 'MyFunction', {
runtime: lambda.Runtime.NODEJS_14_X,
handler: 'index.handler',
code,
environment: {
CLUSTER_ARN: cluster.clusterArn,
SECRET_ARN: cluster.secret!.secretArn,
},
});
cluster.grantDataApiAccess(fn);
Note: To invoke the Data API, the resource will need to read the secret associated with the cluster.
To learn more about using the Data API, see the documentation.
Default VPC
The vpc
parameter is optional.
If not provided, the cluster will be created in the default VPC of the account and region.
As this VPC is not deployed with AWS CDK, you can't configure the vpcSubnets
, subnetGroup
or securityGroups
of the Aurora Serverless Cluster.
If you want to provide one of vpcSubnets
, subnetGroup
or securityGroups
parameter, please provide a vpc
.