aws-cloudformation-rds_skill
- Python
99
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
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Installation
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npx veilstrat add skill giuseppe-trisciuoglio/developer-kit --skill aws-cloudformation-rds- SKILL.md47.9 KB
Overview
This skill provides battle-tested AWS CloudFormation patterns for provisioning Amazon RDS databases. It covers single-instance and cluster deployments (MySQL, PostgreSQL, Aurora, MariaDB), multi-AZ setups, parameter and subnet groups, security and backup configuration, and template structuring for reusable stacks. Use it to accelerate reliable, production-ready RDS infrastructure as code.
How this skill works
The skill supplies CloudFormation template patterns and examples that define Parameters, Mappings, Conditions, Resources, and Outputs for RDS workloads. It demonstrates DBInstance and DBCluster resources, DBSubnetGroup and DBParameterGroup configuration, VPC security group integration, Secrets Manager for credentials, and cross-stack outputs for modular stacks. Templates include validation rules, recommended defaults, and production settings like Multi-AZ, backups, and monitoring.
When to use it
- Provision a new RDS instance or Aurora cluster with a reusable CloudFormation template
- Build multi-AZ or read-replica architectures for availability and scale
- Create DB parameter groups, option groups, and subnet groups for VPC deployments
- Integrate Secrets Manager for credential rotation and secure parameters
- Organize templates with Parameters, Mappings, Conditions, and Outputs for modular stacks
Best practices
- Use AWS-specific parameter types and constraints for safer console input and validation
- Store credentials in AWS Secrets Manager and reference them from templates
- Define DBSubnetGroup with private subnets and attach least-privilege security groups
- Enable Multi-AZ, automated backups, and Performance Insights for production workloads
- Expose only necessary Outputs for cross-stack references and avoid leaking secrets
Example use cases
- Quickly generate a MySQL single-instance template for development or staging
- Deploy an Aurora MySQL cluster with a writer and reader for horizontally scaled reads
- Migrate a PostgreSQL deployment to Multi-AZ with automated backups and monitoring
- Build modular stacks: networking in one stack, DB in another, connecting via Outputs
- Create parameterized templates that select engine and version via SSM or allowed lists
FAQ
No. Use AWS Secrets Manager and reference secrets in CloudFormation to avoid exposing credentials.
When should I use DB clusters vs single instances?
Choose DB clusters (Aurora or read-replica setups) for high read throughput and automatic scaling; use single instances for small, cost-sensitive workloads.
