renovosolutions.aws-cdk-aurora-native-backup 0.1.1

AWS CDK construct library for Aurora backup and restore using ECS on a schedule, storing backups in S3.

cdk-library-aurora-native-backup

A CDK construct library that creates and manages Docker images for Aurora PostgreSQL native backups using pg_dump. The resulting images are designed for use with Amazon ECS Fargate for scalable, serverless backup operations.

Features

• Multi-Database Support: Back up multiple databases from the same Aurora cluster in a single service
• Pre-built Docker Image: Amazon Linux 2023 base with PostgreSQL 17 client tools and AWS CLI v2
• ECR Repository Management: Automatically creates and manages ECR repositories with security best practices
• Complete Backup Service: Ready-to-use ECS Fargate service for scheduled Aurora backups
• EFS and S3 Support: Built-in support for backing up to EFS with S3 sync
• Comprehensive Backup: Uses pg_dump directory format for efficient storage and simplified restore
• Production Ready: Includes proper error handling, logging, and cleanup mechanisms
• Secure Authentication: Uses AWS Secrets Manager for database password management

API Doc

See API

Interface Structure

The library provides two main constructs, each with its own configuration interface:

• AuroraBackupRepository (AuroraBackupRepositoryProps): Manages the ECR repository and Docker image for backups.

• AuroraNativeBackupService (AuroraNativeBackupServiceProps): Manages the backup service infrastructure (VPC, Aurora cluster, S3 bucket, compute resources, etc.), and uses:

  • AuroraBackupConnectionProps: For database connection settings (username, database names array, password secret).

This separation allows for cleaner organization of image/repository management, connection credentials, and infrastructure settings.

Multi-Database Support

The library supports backing up multiple databases from the same Aurora PostgreSQL cluster in a single backup service. Simply provide an array of database names in the databaseNames property (defaults to ['postgres'] if not specified). Each database will be backed up separately and stored in its own S3 folder structure.

Database User Setup

Create a dedicated database user with read-only backup permissions on ALL databases to be backed up.

For PostgreSQL 14+ (recommended), use the built-in pg_read_all_data role for comprehensive read access:

-- Connect to each database and grant permissions
\c your_database_1;
GRANT CONNECT ON DATABASE your_database_1 TO backup_user;
GRANT pg_read_all_data TO backup_user;

-- Repeat for each additional database
\c your_database_2;
GRANT CONNECT ON DATABASE your_database_2 TO backup_user;
GRANT pg_read_all_data TO backup_user;

The pg_read_all_data role automatically provides:

• SELECT on all tables and views
• USAGE on all schemas
• SELECT and USAGE on all sequences
• Access to future objects without requiring additional grants

Note: This library requires PostgreSQL 14 or newer for the pg_read_all_data role.

Shortcomings

• The backup service requires password-based authentication (no IAM database authentication for now)
• The backup container runs as a scheduled task, not continuously, so it cannot capture incremental changes
• Custom backup scripts are not currently supported, only the built-in pg_dump functionality
• When backing up multiple databases, if one database backup fails, the task continues with the remaining databases but the overall task does not fail - individual database backup failures must be monitored through CloudWatch logs

Examples

Prerequisites

To use this construct, you must have:

• An AWS CDK stack with a defined environment (account and region)
• An existing VPC for the backup service
• An existing Aurora PostgreSQL database cluster
• An AWS Secrets Manager secret containing database credentials (recommended)
• A database user with the required backup permissions (see above)

Complete Backup Service (Recommended)

For most use cases, use the AuroraNativeBackupService which provides a complete, ready-to-use backup solution:

TypeScript

import { Stack, StackProps, Duration, aws_ec2 as ec2, aws_rds as rds, aws_scheduler as scheduler, aws_secretsmanager as secretsmanager } from 'aws-cdk-lib';
import { Construct } from 'constructs';
import { AuroraNativeBackupService, AuroraBackupRepository } from '@renovosolutions/cdk-library-aurora-native-backup';

export class BackupServiceStack extends Stack {
  constructor(scope: Construct, id: string, props: StackProps) {
    super(scope, id, props);

    // Your existing Aurora PostgreSQL database cluster and VPC
    const vpc = ec2.Vpc.fromLookup(this, 'Vpc', { isDefault: true });
    const dbCluster = rds.DatabaseCluster.fromDatabaseClusterAttributes(this, 'DbCluster', {
      clusterIdentifier: 'my-production-cluster',
      clusterEndpointAddress: 'cluster.xyz.region.rds.amazonaws.com',
      port: 5432,
    });

    // First create the backup repository
    const backupRepository = new AuroraBackupRepository(this, 'BackupRepository', {
      repositoryName: 'aurora-postgres-backup',
    });

    // Secret containing the backup user's password
    const backupUserSecret = secretsmanager.Secret.fromSecretAttributes(this, 'BackupUserSecret', {
      secretArn: 'arn:aws:secretsmanager:region:account:secret:backup-user-password-abc123',
    });

    // Create the complete backup service
    const backupService = new AuroraNativeBackupService(this, 'BackupService', {
      cluster: dbCluster,
      vpc,
      backupBucketName: 'my-aurora-production-backups',
      ecrRepository: backupRepository.repository,
      connection: {
        username: 'backup_user',
        databaseNames: ['production', 'analytics', 'reporting'],
        passwordSecret: backupUserSecret,
      },
      retentionDays: 30,
      backupSchedule: scheduler.ScheduleExpression.cron({ minute: '0', hour: '2' }), // Daily at 2 AM UTC
      cpu: 1024, // Override default of 256
      memoryLimitMiB: 2048, // Override default of 512
    });
  }
}

Python

from aws_cdk import (
  Stack,
  Duration,
  aws_ec2 as ec2,
  aws_rds as rds,
  aws_scheduler as scheduler,
  aws_secretsmanager as secretsmanager
)
from constructs import Construct
from cdk_library_aurora_native_backup import AuroraNativeBackupService, AuroraBackupRepository

class BackupServiceStack(Stack):
  def __init__(self, scope: Construct, id: str, **kwargs):
    super().__init__(scope, id, **kwargs)

    # Your existing Aurora PostgreSQL database cluster and VPC
    vpc = ec2.Vpc.from_lookup(self, "Vpc", is_default=True)
    db_cluster = rds.DatabaseCluster.from_database_cluster_attributes(self, "DbCluster",
      cluster_identifier="my-production-cluster",
      cluster_endpoint_address="cluster.xyz.region.rds.amazonaws.com",
      port=5432
    )

    # First create the backup repository
    backup_repository = AuroraBackupRepository(self, "BackupRepository",
      repository_name="aurora-postgres-backup"
    )

    # Secret containing the backup user's password
    backup_user_secret = secretsmanager.Secret.from_secret_attributes(self, "BackupUserSecret",
      secret_arn="arn:aws:secretsmanager:region:account:secret:backup-user-password-abc123"
    )

    # Create the complete backup service
    backup_service = AuroraNativeBackupService(self, "BackupService",
      cluster=db_cluster,
      vpc=vpc,
      backup_bucket_name="my-aurora-production-backups",
      ecr_repository=backup_repository.repository,
      connection={
        "username": "backup_user",
        "database_names": ["production", "analytics", "reporting"],
        "password_secret": backup_user_secret
      },
      retention_days=30,
      backup_schedule=scheduler.ScheduleExpression.cron(minute='0', hour='2'),  # Daily at 2 AM UTC
      cpu=1024,  # Override default of 256
      memory_limit_mi_b=2048  # Override default of 512
    )

Environment Variables

All environment variables used by the backup container are set automatically by the constructs. You do not need to set them manually.

Environment Variable	Description	CDK Prop / Source
DB_HOST	Aurora PostgreSQL database cluster endpoint	cluster.clusterEndpoint.hostname
DB_NAMES	Array of database names to backup	connection.databaseNames
DB_USER	Database username	connection.username
DB_PASSWORD	Database password	connection.passwordSecret
AWS_REGION	AWS region	Stack.region
CLUSTER_IDENTIFIER	Cluster ID used as S3 path prefix (backups/{CLUSTER_IDENTIFIER}/)	cluster.clusterIdentifier
DB_PORT	Database port (default: 5432)	cluster.clusterEndpoint.port
BACKUP_ROOT	Backup directory (default: /mnt/aurora-backups)	(internal default)
S3_BUCKET	S3 bucket for backup sync	backupBucketName
S3_PREFIX	S3 prefix (default: backups)	(internal default)

Backup Process

1. Validation: Checks AWS credentials and creates backup directories

2. Database Backup: For each database in the DB_NAMES array:

   • Uses pg_dump --format=directory with gzip compression (level 9) for each data file
   • Creates separate backup directory per database with date stamp
   • If one database backup fails, continues with remaining databases

3. Verification: Validates each backup contains toc.dat file

4. S3 Sync: Syncs each database backup to S3 bucket under separate database folders

5. Cleanup: Removes local backups after successful S3 sync

Security Considerations

• ECR repositories created with image scanning enabled
• EFS encryption in transit supported
• IAM permissions follow principle of least privilege
• Use AWS Secrets Manager for database passwords in production
• Consider VPC endpoints for S3 to avoid internet traffic

Backup Storage Structure

Local EFS structure (per database):

/mnt/aurora-backups/
├── production/
│   └── YYYY-MM-DD/
│       ├── toc.dat                # PostgreSQL table of contents
│       ├── ####.dat.gz            # Compressed table data files
│       └── ####.dat.gz            # Additional data files
├── analytics/
│   └── YYYY-MM-DD/
│       ├── toc.dat
│       └── ####.dat.gz
└── reporting/
    └── YYYY-MM-DD/
        ├── toc.dat
        └── ####.dat.gz

S3 structure:

s3://my-backup-bucket/
└── backups/
    └── {CLUSTER_IDENTIFIER}/
        ├── production/
        │   └── YYYY-MM-DD/
        │       ├── toc.dat
        │       └── ####.dat.gz
        ├── analytics/
        │   └── YYYY-MM-DD/
        │       ├── toc.dat
        │       └── ####.dat.gz
        └── reporting/
            └── YYYY-MM-DD/
                ├── toc.dat
                └── ####.dat.gz

Restoration

Interactive Restore CLI (Recommended)

This library includes an interactive TypeScript CLI that simplifies the restore process with auto-discovery and guided prompts:

npx ts-node restore_script/aurora-restore-cli.ts

Features:

• Auto-discovery: Automatically finds S3 backup buckets using the aurora_native_backup_bucket=true tag
• Interactive selection: Guided prompts for cluster, database, backup date, and tables
• Table-level restore: Select specific tables or restore entire database
• Optimized downloads: Only downloads required backup files
• Ready-to-run commands: Generates and optionally executes pg_restore commands

Prerequisites:

• Node.js and TypeScript installed

• AWS credentials configured (via AWS CLI, environment variables, or IAM role)

• pg_restore command available in your PATH

• Network access to target PostgreSQL database

• Database user with restore permissions on target database:

  • CREATE privilege (for creating tables, indexes, constraints)
  • INSERT privilege (for loading data)
  • USAGE and CREATE on schemas
  • For full database restore: CREATEDB privilege or superuser role

Setup and Execution:

First, install dependencies:

cd restore_script
yarn install

Then run the interactive CLI:

npx ts-node aurora-restore-cli.ts

The CLI will guide you through selecting your backup source, target database, and specific tables to restore.

Workflow:

1. S3 Configuration: Auto-discovers backup bucket or prompts for manual entry
2. Source Selection: Choose cluster, database, and backup date
3. Table Selection: Select specific tables or full database restore
4. Target Configuration: Enter target database connection details
5. Execution: Downloads backup files and generates restore command

Manual Restoration

For advanced users or automation, backups are stored in S3 under organized paths:

s3://my-backup-bucket/backups/{CLUSTER_IDENTIFIER}/{DATABASE_NAME}/YYYY-MM-DD/

Download backup files:

aws s3 cp --recursive s3://my-backup-bucket/backups/{CLUSTER_IDENTIFIER}/production/YYYY-MM-DD/ /path/to/backup/directory/

Restore commands:

Full database restore:

pg_restore -h target-host -U username -d target_db -v -C /path/to/backup/directory/

List backup contents:

pg_restore --list /path/to/backup/directory/

Selective table restore:

pg_restore -h target-host -U username -d target_db -v -t table_name /path/to/backup/directory/

Contributing

Contributions are welcome! Please follow these guidelines to help us maintain and improve the project:

Code Structure and Interfaces

• The main user-facing interfaces are:

  • AuroraBackupRepositoryProps in src/aurora-backup-repository.ts
  • AuroraNativeBackupServiceProps and AuroraBackupConnectionProps in src/aurora-native-backup-service.ts

• All constructs and their configuration interfaces are defined in the src/ directory.

Code Generation and Project Tasks

• This project uses projen for project management and code generation.

• If you make changes to the project configuration (.projenrc.ts), run:

  npx projen
  

  This will regenerate all managed files, including package.json and other configuration files.

Building and Testing

• To build the project and run all tests, use:

  yarn build
  

  This will compile the code, run unit tests, and ensure everything is up to date.

License

This project is licensed under the Apache License, Version 2.0 - see the LICENSE file for details.