AWS Architecture Blog

Field Notes: How to Set Up Your Cross-Account and Cross-Region Database for Amazon Aurora

This post was co-written by Ashutosh Pateriya, Solution Architect at AWS and Nirmal Tomar, Principal Consultant at Infosys Technologies Ltd. 

Various organizations have stringent regulatory compliance obligations or business requirements that require an effective cross-account and cross-region database setup. We recommend to establish a Disaster Recovery (DR) environment in different AWS accounts and Regions for a system design that can handle AWS Region failures.

Account-level separation is important for isolating production environments from other environments, that is, development, test, UAT and DR environments. These are defined by external compliance requirements, such as PCI-DSS or HIPAA. Cross-account replication helps an organization recover data from a replicated account, when the primary AWS account is compromised, and access to the account is lost. Using multiple Regions gives you greater control over the recovery time, if there is a hard dependency failure on a Regional AWS service.

You can use Amazon Aurora Global Database to replicate your RDS database across Regions, within the same AWS Account. In this blog, we show how to build a custom solution for Cross-Account, Cross-Region database replication with configurable Recovery Time Objective (RTO)/ Recovery Point Objective (RPO).

Solution Overview

a custom solution for Cross-Account, Cross-Region database replication with configurable Recovery Time

Figure 1 – Architecture of a Cross-Account, Cross-Region database replication with configurable Recovery Time Objective (RTO)/ Recovery Point Objective (RPO)

Step 1: Automated Amazon Aurora snapshots cannot be shared with other AWS accounts. Hence, create a manual version of the snapshot for the same.

Step 2: Amazon Aurora cannot be restored from the snapshot created in different AWS Regions. To overcome this, you must copy the snapshot in the target AWS Region after AWS KMS encryption.

Step 3: Share the DB cluster snapshot with the target account, in order to restore the cluster.

Step 4: Restore Aurora Cluster from the shared snapshot.

Step 5: Restore the required Aurora Instances.

Step 6: Swap the cluster and instance names, to make it accessible from the previous Reader/Writer endpoint.

Step 7: Perform a sanity test and shut down the old cluster.

Prerequisites

  • Two AWS accounts with permission to spin up required resources.
  • A running Aurora instance in the source AWS account.

Walkthrough

The solution outlined is custom built, and automated using AWS Step functions, AWS Lambda, Amazon Simple Notification Service (SNS), AWS Key Management Service (KMS), AWS Cloud​Formation Templates, Amazon Aurora and AWS Identity and Access Management IAM by following these four steps:

  1. Launch a one-time set up of the AWS KMS in the AWS source account to share the key with destination account. This key will be used by the destination account to restore the Aurora cluster from a KMS encrypted snapshot.
  2. Set up the step function workflow in the AWS source account and source Region. On a scheduled interval, this workflow creates a snapshot in the source account and source Region. Copy it to the target Region and push a notification to the SNS topic and setup a Lambda function as a target for the SNS topic. Refer to the documentation to learn more about Using Lambda with Amazon SNS.
  3. Set up the step function workflow in the AWS target account and in the target Region. This workflow is initiated from the previous workflow after sharing the snapshot. It restores the Aurora cluster from the shared snapshot in the target account and in the target Region.
  4. Provide access to the Lambda function in the target account and target Region. Set it up to listen to the SNS topic in the source account and source Region.
AWS Step Function in Source Account and Source Region

Figure 2 – Architecture showing AWS Step Function in Source Account and Source Region

We can implement a Lambda function with different supported programming languages. For this solution, we selected Python to implement various Lambda functions used in both step function workflows.

Note: We are using us-west-2 as the source Region and us-west-1 as the target Region for this demo. You can choose Regions as per your design need.

Part 1: One Time AWS KMS key setup in the Source Account and Target Region for cross-account access of the Encrypted Snapshot

We can share a Customer Master Key (CMK) across multiple AWS accounts using different ways, such as  using AWS CloudFormation templates, CLI, and AWS console.

Following are one-time steps that allow you to create an AWS KMS key in the source AWS account. You can then provide cross-account usage access of the same key to the destination account for restoring the Aurora cluster. You can achieve this with the AWS Console and AWS CloudFormation Template.

Note: Several AWS services being used do not fall under the AWS Free Tier. To avoid extra charges, make sure to delete resources once the demo is completed.

Using the AWS Console

You can set up cross-account AWS KMS keys using the AWS Console. For more information on the setup, refer to the guide: Allowing users in other accounts to use a CMK.

Using the AWS CloudFormation Template

You can set up cross account AWS KMS keys using CloudFormation templates by following these steps:

  • Launch the template:

Launch with CLoudFormatation Console button

  • Use the source account and destination AWS Region.
  • Type the appropriate stack name and destination account number and select Create stack.

Create Stack screenshot

  • Click on the Resources tab to confirm if the KMS key and its alias name have been created.

Resources screenshot

Part 2: Snapshot creation and sharing Target Account in Target Region using the Step Function workflow

Now, we schedule the AWS Step Function workflow with single/multiple times in a day/week/month using Amazon EventBridge or Amazon CloudWatch Events per Recovery Time Objective (RTO)/ Recovery Point Objective (RPO).

This workflow first creates a snapshot in the AWS source account and source Region> The snapshot copies it in target Region after KMS encryption, shares the snapshot with the target account and sends a notification to SNS Topic.  A Lambda function is subscribed to the topic in the target account.

 

Diagram showing AWS Step Function in Source Account and Source Region

Figure 3 – Architecture showing the AWS Step Functions Workflow

The Import Lambda functions involved in this workflow:

a.     CreateRDSSnapshotInSourceRegion:  This Lambda function creates a snapshot in the source Account and Region for an existing Aurora cluster.

b.     FetchSourceRDSSnapshotStatus: This Lambda function fetches the snapshot status and waits for its availability before moving to the next step.

c.     EncrytAndCopySnapshotInTargetRegion: This Lambda function copies the source snapshot in the target AWS Region after encryption with AWS KMS keys.

d.     FetchTargetRDSSnapshotStatus: This Lambda function fetch the snapshot status in the target Region and will wait to move to the next step once snapshot status changed to available.

e.     ShareSnapshotStateWithTargetAccount: This Lambda function shares the snapshot with the target account and target Region.

f.      SendSNSNotificationToTargetAccount:  This option sends the notification to the SNS topic. An AWS Lambda function is subscribed to this topic for the destination AWS Account.

Using the following AWS CloudFormation Template, we set up the required services/workflow in the source account and source Region:

a.     Launch the template in the source account and source Region:

Launch with CLoudFormatation Console button

Specify stack details screenshot

b.     Fill out the preceding form with the following details and select next.

Stack name:  Stack Name which you want to create.

DestinationAccountNumber: Destination AWS Account number where you want to restore the Aurora  cluster.

KMSKey: KMS key ARN number setup in previous steps.

ScheduleExpression: Schedule a cron expression when you want to run this workflow. Sample expressions are available in this guide, Schedule expressions using rate or cron.

SourceDBClusterIdentifier: The identifier of the DB cluster, for which a snapshot is created. It must match the identifier of an existing DBCluster. This parameter isn’t case-sensitive.

SourceDBSnapshotName: Snapshot name which we will use in this flow.

TargetAWSRegion: Destination AWS Account Region where you want to restore the Aurora cluster.

Permissions screenshot

c.     Select IAM role to launch this template per best practices.

Capabilities and transforms screenshot

d.     Acknowledge to create various resources including IAM roles/policies and select Create Stack.

Part 3: Workflow to Restore the Aurora Cluster in the AWS Target Account and Target Region

Once AWS Lambda receives a cross-account sns notification for the shared snapshot, this workflow begins:

  • The Lambda function starts the AWS Step Function workflow in an asynchronous mode.
  • The workflow checks for the snapshot availability and starts restoring the Aurora cluster based on the configured engine, version, and other parameters.
  • Depending on the availability of the cluster, it adds instances based on a predefined configuration.
  • Once the instances are available, it swaps cluster names so that the updated database is available at the same reader and writer endpoints.
  • Once the databases are restored, the old Aurora cluster is shut down.

Note:

a)       The database is restored in the default VPC, Availability Zone, and option group, with the default cluster version and option group. If you want to restore with the specific configurations, you can edit the restore cluster function with details available in the same section.

b)      Database credentials will be the same as source account. If you want to override credential or change the authentication mechanism, you can edit the restore cluster function with details available in the same section.

Trigger Step Function graphic

Figure 4 – Architecture showing the AWS Step Functions Workflow

Import Lambda functions involved in this workflow:

a)     FetchRDSSnapshotStatus: This Lambda function fetches the snapshot status and moves to RestoreCluster functionality once the snapshot is available.

b)    RestoreRDSCluster: This Lambda function restores the cluster from the shared snapshot with the mandatory attribute only.

–     You can edit the Lambda function as described following to add specific parameters like specific VPC, Subnets, AvailabilityZones, DBSubnetGroupName, Autoscaling for reader capacity, DBClusterParameterGroupName, BacktrackWindow and many more.

c)     RestoreInstance: This Lambda function creates an instance for the restored cluster.

d)    SwapClusterName: This Lambda function swaps the cluster name, so that the updated database is available at previous endpoints. Then the cluster url is swapped.

e)     TerminateOldCluster: This Lambda function will shut down the previous cluster.

Using the following AWS CloudFormation Template, we can set up the required services/workflow in the target account and target Region:

a)     Launch the template in target account and target Region:

Launch with CLoudFormatation Console button

Specify stack details screenshot

b)     Fill out the preceding form with the following details and click the next button.

Stack name: Stack name which you want to create.

Engine: The database engine to be used for the new DB cluster, such as aurora-mysql. It must be compatible with the engine of the source.

DBInstanceClass: The compute and memory capacity of the Amazon RDS DB instance, for example, db.t3.medium.

Not all DB instance classes are available in all AWS Regions, or for all database engines. For the full list of DB instance classes, and availability for your engine, see DB Instance Class in the Amazon RDS User Guide.

ExistingDBClusterIdentifier: Name of the existing DB cluster. In the final step, if the old cluster is available with this name, it will be deleted and a new cluster will be available with this name, so the reader/writer endpoint will not change. This parameter isn’t case-sensitive. It must contain from 1 to 63 letters, numbers, or hyphens. The first character must be a letter. DBClusterIdentifier can’t end with a hyphen or contain two consecutive hyphens.

TempDBClusterIdentifier: Temporary name of the DB cluster created from the DB snapshot or DB cluster snapshot. In the final step, this cluster name will be swapped with the original cluster and the previous cluster will be deleted. This parameter isn’t case-sensitive. Must contain from 1 to 63 letters, numbers, or hyphens. The first character must be a letter. DBClusterIdentifier can’t end with a hyphen or contain two consecutive hyphens.

ExistingDBInstanceIdentifier: Name of the existing DB instance identifier. In the final step, if an previous instance is available with this name, it will be deleted and a new instance will be available with this name. This parameter is stored as a lowercase string. Must contain from 1 to 63 letters, numbers, or hyphens. The first character must be a letter, can’t end with a hyphen or contain two consecutive hyphens.

TempDBInstanceIdentifier: Temporary name of the existing DB instance. In the final step, if a previous instance is available with this name, it will be deleted and a new instance will be available. This parameter is stored as a lowercase string. Must contain from 1 to 63 letters, numbers, or hyphens. The first character must be a letter, can’t end with a hyphen or contain two consecutive hyphens.

Permissions2 screenshot

 

c)     Select IAM role to launch this template as per best practices and select Next.

Capabilities and transforms screenshot 2

 

d)     Acknowledge to create various resources including IAM roles/policies and select Create Stack.

After launching the CloudFormation steps, all resources like IAM roles, step function workflow and Lambda functions will be set up in the target account.

Part 4: Cross Account Role for Lambda Invocation to restore the Aurora Cluster

In this step, we  provide access to Lambda function setup in the target account and target Region to listen to the SNS topic setup in the source account and source Region. An SNS notification is initiated by the first workflow after the snapshot sharing steps. The Lambda function initiates a workflow to restore the Aurora cluster in the target account and target Region.

Using the following code , we can configure a Lambda function in the target account to listen to the sns topic created in the source account and Region. More details are available in this Tutorial: Using AWS Lambda with Amazon Simple Notification Service.

a)     Configure the SNS topic in source account to allow Subscriptions for target account by using the following AWS CLI command in the source account.

aws sns add-permission \
  --label lambda-access --aws-account-id <<targetAccountID>> \
  --topic-arn <<snsTopicinSourceAccount>> \
  --action-name Subscribe ListSubscriptionsByTopic

Replace << targetAccountID >> with target AWS account number and <<snsTopicinSourceAccount>> with sns topic created as an output of part 2 CloudFormation template in the source account.

b)     Configure the InvokeStepFunction Lambda function in target account to allow invocation from the SNS topic in source account by using following AWS CLI command in the target account. This policy allows the specific SNS topic in the source account to invoke the Lambda function.

aws lambda add-permission \
  --function-name InvokeStepFunction \
  --source-arn <<snsTopicinSourceAccount>> \
  --statement-id sns-x-account \
  --action "lambda:InvokeFunction" \
   --principal sns.amazonaws.com

Replace <<snsTopicinSourceAccount>> with sns topic created as an output of part 2 CloudFormation template.

c)     Subscribe the Lambda function in the target account to the SNS topic in the source account by using the following AWS CLI command in the target account.

aws sns subscribe \
  --topic-arn <<snsTopicinSourceAccount>> \
   --protocol "lambda" \
  --notification-endpoint << InvokeStepFunctionArninTargetAccount>>

Initiate the CLI command in the source Region as sns topic is created there. Replace <<snsTopicinSourceAccount>> with sns topic created as an output of part 2 CloudFormation template execution and << InvokeStepFunctionArninTargetAccount >>with InvokeStepFunction Lambda in the target account created as an output of part 3 CloudFormation template launch.

Security Consideration:

1.     We can share the snapshots with different accounts using public and private mode.

  • Public mode permits all AWS accounts to restore a DB instance from the shared snapshot.
  • Private mode permits only AWS accounts that you specify to restore a DB instance from the shared snapshot. We recommend sharing the snapshot with the destination account in private mode, as we are using the same in our solution.

Snapshot permissions screenshot

2.     Sharing a manual DB cluster snapshot (whether encrypted or unencrypted) enables authorized AWS accounts to directly restore a DB cluster from the snapshot. This is instead of taking a copy and restoring from that. We recommend sharing an encrypted snapshot with the destination account, as we are using the same in our solution.

Cleaning up

Delete the resources to avoid future incurring charges.

Conclusion

In this blog, you learned how to replicate databases across the Region and across different accounts. This helps in designing your DR environment and fulfilling compliance requirements. This solution can be customized for any RDS-based databases or Aurora Serverless, and you can achieve the desired level of RTO and RPO.

Reference:

Field Notes provides hands-on technical guidance from AWS Solutions Architects, consultants, and technical account managers, based on their experiences in the field solving real-world business problems for customers.

 

Nirmal Tomar

Nirmal is a principal consultant with Infosys, assisting vertical industries on application migration and modernization to the public cloud. He is the part of the Infosys Cloud CoE team and leads various initiatives with AWS. Nirmal has a keen interest in industry and cloud trends, and in working with hyperscaler to build differentiated offerings. Nirmal also specializes in cloud native development, managed containerization solutions, data analytics, data lakes, IoT, AI, and machine learning solutions.

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Ashutosh Pateriya

Ashutosh Pateriya

Ashutosh Pateriya is a Solutions Architect with Amazon Web Services. He is passionate about Networking, Security and helping customers leverage the power of AWS cloud.