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Aws Cloudformation Rds

Community
giuseppe-trisciuoglio
aws-cloudformation-rds

Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Overview

Publishergiuseppe-trisciuoglio
Repositorydeveloper-kit
Skill nameaws-cloudformation-rds
Stars
345
Forks
41
Bundled files
8
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by giuseppe-trisciuoglio on GitHub. Read the source before you install it.

Installation

Install the Aws Cloudformation Rds AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git /tmp/developer-kit
mkdir -p .claude/skills
cp -r /tmp/developer-kit/plugins/developer-kit-aws/skills/aws-cloudformation/aws-cloudformation-rds .claude/skills/aws-cloudformation-rds
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws Cloudformation Rds in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aws Cloudformation Rds on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aws Cloudformation Rds is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AWS CloudFormation RDS Database

Overview

Create production-ready Amazon RDS infrastructure using AWS CloudFormation templates. Covers RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, security groups, and cross-stack references.

When to Use

  • Creating RDS instances (MySQL, PostgreSQL, Aurora) or DB clusters with read replicas
  • Setting up multi-AZ deployments or configuring parameter/subnet groups
  • Integrating with Secrets Manager or implementing cross-stack references

Quick Reference

ComponentCloudFormation TypeUse Case
DB InstanceAWS::RDS::DBInstanceSingle database instance
DB ClusterAWS::RDS::DBClusterAurora cluster
DB Subnet GroupAWS::RDS::DBSubnetGroupVPC deployment
Parameter GroupAWS::RDS::DBParameterGroupDatabase configuration
Security GroupAWS::EC2::SecurityGroupNetwork access control
Secrets ManagerAWS::SecretsManager::SecretCredential storage

Instructions

Step 1 — Define Database Parameters

Use AWS-specific parameter types for validation.

yaml
Parameters:
  DBInstanceClass:
    Type: AWS::RDS::DBInstance::InstanceType
    Default: db.t3.micro
    AllowedValues: [db.t3.micro, db.t3.small, db.t3.medium]

  Engine:
    Type: String
    Default: mysql
    AllowedValues: [mysql, postgres, aurora-mysql, aurora-postgresql]

  MasterUsername:
    Type: String
    Default: admin
    AllowedPattern: "^[a-zA-Z][a-zA-Z0-9]*$"
    MinLength: 1
    MaxLength: 16

  MasterUserPassword:
    Type: String
    NoEcho: true
    MinLength: 8
    MaxLength: 41

See template-structure.md for advanced parameter patterns, mappings, conditions, and cross-stack references.

Step 2 — Create DB Subnet Group

Required for VPC deployment with subnets in different AZs.

yaml
DBSubnetGroup:
  Type: AWS::RDS::DBSubnetGroup
  Properties:
    DBSubnetGroupDescription: Subnet group for RDS
    SubnetIds:
      - !Ref PrivateSubnet1
      - !Ref PrivateSubnet2

See database-components.md for parameter groups, option groups, and engine-specific configurations.

Step 3 — Configure Security Group

Restrict access to application tier only.

yaml
DBSecurityGroup:
  Type: AWS::EC2::SecurityGroup
  Properties:
    GroupDescription: Security group for RDS
    VpcId: !Ref VpcId
    SecurityGroupIngress:
      - IpProtocol: tcp
        FromPort: 3306
        ToPort: 3306
        SourceSecurityGroupId: !Ref AppSecurityGroup

See security-secrets.md for VPC security groups, encryption, Secrets Manager integration, and IAM authentication.

Step 4 — Launch RDS Instance

Configure instance with subnet group, security group, and settings.

yaml
DBInstance:
  Type: AWS::RDS::DBInstance
  Properties:
    DBInstanceIdentifier: !Sub "${AWS::StackName}-mysql"
    DBInstanceClass: !Ref DBInstanceClass
    Engine: !Ref Engine
    MasterUsername: !Ref MasterUsername
    MasterUserPassword: !Ref MasterUserPassword
    AllocatedStorage: 20
    StorageType: gp3
    DBSubnetGroupName: !Ref DBSubnetGroup
    VPCSecurityGroups: [!Ref DBSecurityGroup]
    StorageEncrypted: true
    MultiAZ: true
    BackupRetentionPeriod: 7
    DeletionProtection: false

See database-components.md for MySQL, PostgreSQL, Aurora cluster configurations, and parameter groups.

Step 5 — Enable High Availability

Configure multi-AZ deployment for production.

yaml
Conditions:
  IsProduction: !Equals [!Ref Environment, production]

Resources:
  DBInstance:
    Type: AWS::RDS::DBInstance
    Properties:
      MultiAZ: !If [IsProduction, true, false]
      BackupRetentionPeriod: !If [IsProduction, 35, 7]
      DeletionProtection: !If [IsProduction, true, false]
      EnablePerformanceInsights: !If [IsProduction, true, false]

See high-availability.md for multi-AZ deployments, read replicas, Aurora auto-scaling, enhanced monitoring, and disaster recovery.

Step 6 — Define Outputs

Export connection details for application stacks.

yaml
Outputs:
  DBInstanceEndpoint:
    Description: Database endpoint address
    Value: !GetAtt DBInstance.Endpoint.Address
    Export:
      Name: !Sub ${AWS::StackName}-DBEndpoint

  DBInstancePort:
    Description: Database port
    Value: !GetAtt DBInstance.Endpoint.Port
    Export:
      Name: !Sub ${AWS::StackName}-DBPort

  DBConnectionString:
    Description: Connection string
    Value: !Sub jdbc:mysql://${DBInstance.Endpoint.Address}:${DBInstance.Endpoint.Port}/${DBName}

See template-structure.md for cross-stack reference patterns and import/export strategies.

Validation Steps

Always validate before deploying, especially to production.

bash
# Validate the template syntax
aws cloudformation validate-template --template-body file://template.yaml

# Review the change set before applying updates
aws cloudformation create-change-set \
  --stack-name my-rds-stack \
  --template-body file://template.yaml \
  --change-set-type UPDATE

aws cloudformation describe-change-set --change-set-name <arn>

# Execute the change set if the preview looks correct
aws cloudformation execute-change-set --change-set-name <arn>

Best Practices

CategoryPracticeImplementation
SecurityEncryption at restStorageEncrypted: true with KMS key
SecurityCredential managementUse Secrets Manager integration
SecurityNetwork isolationPrivate subnets, restrictive SG rules
SecurityIAM authenticationEnable IAMDatabaseAuthentication
HAMulti-AZ deploymentMultiAZ: true for production
HADeletion protectionDeletionProtection: true for production
HABackup retention35 days for production, 7 for dev
HARead replicasUse for read-heavy workloads
CostStorage typeUse gp3 for cost efficiency
CostInstance sizingRight-size based on workload
CostServerlessConsider Aurora Serverless for variable loads
OperationsChange setsAlways review before applying updates
OperationsDrift detectionEnable for template compliance
OperationsMonitoringConfigure CloudWatch alarms

See operational-practices.md for detailed guidance on stack policies, termination protection, and backup strategies.

Examples

Complete production-ready RDS instance with MultiAZ, encryption, and Secrets Manager integration:

yaml
AWSTemplateFormatVersion: '2010-09-09'
Description: Production RDS Instance

Parameters:
  VpcId:
    Type: AWS::EC2::VPC::Identifier
  SubnetIds:
    Type: List<AWS::EC2::Subnet::Identifier>
  AppSecurityGroupId:
    Type: AWS::EC2::SecurityGroup::Id
  Environment:
    Type: String
    AllowedValues: [dev, staging, production]
  MasterUsername:
    Type: String
    Default: dbadmin

Conditions:
  IsProduction: !Equals [!Ref Environment, production]

Resources:
  DBSubnetGroup:
    Type: AWS::RDS::DBSubnetGroup
    Properties:
      DBSubnetGroupDescription: !Sub "${AWS::StackName} subnet group"
      SubnetIds: !Ref SubnetIds

  DBSecurityGroup:
    Type: AWS::EC2::SecurityGroup
    Properties:
      GroupDescription: !Sub "${AWS::StackName} RDS security group"
      VpcId: !Ref VpcId
      SecurityGroupIngress:
        - IpProtocol: tcp
          FromPort: 3306
          ToPort: 3306
          SourceSecurityGroupId: !Ref AppSecurityGroupId

  DBInstance:
    Type: AWS::RDS::DBInstance
    DeletionPolicy: Snapshot
    UpdateReplacePolicy: Snapshot
    Properties:
      DBInstanceIdentifier: !Sub "${AWS::StackName}-mysql"
      DBInstanceClass: db.t3.medium
      Engine: mysql
      EngineVersion: '8.0'
      MasterUsername: !Ref MasterUsername
      MasterUserPassword: !Ref MasterUserPassword
      AllocatedStorage: 50
      StorageType: gp3
      StorageEncrypted: true
      KmsKeyId: !Ref KmsKeyId
      DBSubnetGroupName: !Ref DBSubnetGroup
      VPCSecurityGroups: [!Ref DBSecurityGroup]
      MultiAZ: !If [IsProduction, true, false]
      BackupRetentionPeriod: !If [IsProduction, 35, 7]
      DeletionProtection: !If [IsProduction, true, false]
      EnablePerformanceInsights: !If [IsProduction, true, false]
      PerformanceInsightsRetentionPeriod: !If [IsProduction, 731, 7]

  KmsKeyId:
    Type: AWS::KMS::Key
    Condition: IsProduction
    Properties:
      Description: KMS key for RDS encryption
      EnableKeyRotation: true
      KeyPolicy:
        Version: '2012-10-17'
        Statement:
          - Sid: Enable IAM User Permissions
            Effect: Allow
            Principal:
              AWS: !Sub arn:aws:iam::${AWS::AccountId}:root
            Action: kms:*
            Resource: '*'

Outputs:
  DBEndpoint:
    Description: Database endpoint
    Value: !GetAtt DBInstance.Endpoint.Address
    Export:
      Name: !Sub ${AWS::StackName}-DBEndpoint
  DBPort:
    Description: Database port
    Value: !GetAtt DBInstance.Endpoint.Port
    Export:
      Name: !Sub ${AWS::StackName}-DBPort

See examples.md for additional examples including Aurora clusters, read replicas, and multi-region setups.

References

Core Configuration

Operational Guides

  • operational-practices.md — Stack policies, termination protection, drift detection, change sets, monitoring
  • constraints.md — Resource limits, operational constraints, security constraints, cost considerations

Additional Resources

Constraints and Warnings

Resource Limits

  • Maximum storage size varies by engine (up to 64 TB for MySQL/PostgreSQL)
  • Maximum 500 resources per CloudFormation stack
  • Parameter group limits vary by account/region

Cost Considerations

  • Multi-AZ deployments cost approximately double single-AZ
  • Provisioned IOPS (io1) significantly increases costs
  • Backup storage beyond free tier incurs monthly costs
  • Manual snapshots incur storage costs even after instance deletion

Security Constraints

  • Master password cannot be retrieved after creation
  • Encryption at rest cannot be disabled once enabled
  • RDS instances must be in VPC (public access not recommended)
  • Security group rules must restrict access to application tier

Operational Constraints

  • Certain modifications (engine version, storage type) require instance replacement with downtime
  • Maintenance windows may cause brief service interruptions
  • Read replicas may lag behind primary by seconds to minutes
  • Not all database engines available in all regions

See constraints.md for complete constraints, troubleshooting guides, and performance considerations.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aws Cloudformation Rds AI skill do?

Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Why use Aws Cloudformation Rds on TypingMind?

Because you install it once and use it with any model. Aws Cloudformation Rds is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aws Cloudformation Rds in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-aws/skills/aws-cloudformation/aws-cloudformation-rds. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aws Cloudformation Rds?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aws Cloudformation Rds?

As many as you like. As long as a model supports skills, you can use Aws Cloudformation Rds with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aws Cloudformation Rds AI skill free?

Yes. It is published on GitHub by giuseppe-trisciuoglio under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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