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Aws Rds

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BagelHole
aws-rds

Provision and manage RDS databases. Configure backups, replication, and security. Use when deploying managed relational databases on AWS.

Overview

PublisherBagelHole
RepositoryDevOps-Security-Agent-Skills
Skill nameaws-rds
Stars
1.1K
Forks
161
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by BagelHole on GitHub. Read the source before you install it.

Installation

Install the Aws 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.
    https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/cloud-aws/aws-rds
  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/BagelHole/DevOps-Security-Agent-Skills.git /tmp/DevOps-Security-Agent-Skills
mkdir -p .claude/skills
cp -r /tmp/DevOps-Security-Agent-Skills/infrastructure/cloud-aws/aws-rds .claude/skills/aws-rds
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws 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 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 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 RDS

Deploy and manage Amazon RDS relational databases with production-grade backups, replication, monitoring, and security.

When to Use This Skill

  • Provisioning a managed PostgreSQL, MySQL, MariaDB, Oracle, or SQL Server database
  • Setting up Multi-AZ deployments for high availability
  • Creating read replicas for horizontal read scaling
  • Configuring automated backups, snapshots, and point-in-time recovery
  • Tuning database parameters for performance
  • Migrating from self-managed databases to RDS
  • Monitoring database performance and setting up alarms

Prerequisites

  • AWS CLI v2 installed and configured
  • IAM permissions: rds:*, ec2:DescribeSecurityGroups, ec2:DescribeSubnets, kms:*, cloudwatch:*
  • A VPC with at least two subnets in different AZs (for subnet group)
  • Security group allowing database port access from application subnets only

Create a DB Subnet Group

bash
# Create a subnet group spanning two AZs
aws rds create-db-subnet-group \
  --db-subnet-group-name production-db-subnets \
  --db-subnet-group-description "Production database subnets" \
  --subnet-ids subnet-private-a subnet-private-b

# List subnet groups
aws rds describe-db-subnet-groups \
  --query "DBSubnetGroups[].{Name:DBSubnetGroupName,VPC:VpcId,Status:SubnetGroupStatus}" \
  --output table

Create a Production Database

bash
# Create a PostgreSQL 16 Multi-AZ instance
aws rds create-db-instance \
  --db-instance-identifier production-api-db \
  --db-instance-class db.r6g.large \
  --engine postgres \
  --engine-version 16.4 \
  --master-username appadmin \
  --manage-master-user-password \
  --allocated-storage 100 \
  --max-allocated-storage 500 \
  --storage-type gp3 \
  --storage-encrypted \
  --kms-key-id alias/rds-key \
  --vpc-security-group-ids sg-db-access \
  --db-subnet-group-name production-db-subnets \
  --db-name appdb \
  --backup-retention-period 14 \
  --preferred-backup-window "03:00-04:00" \
  --preferred-maintenance-window "sun:05:00-sun:06:00" \
  --multi-az \
  --auto-minor-version-upgrade \
  --deletion-protection \
  --copy-tags-to-snapshot \
  --monitoring-interval 60 \
  --monitoring-role-arn arn:aws:iam::123456789012:role/rds-monitoring-role \
  --enable-performance-insights \
  --performance-insights-retention-period 7 \
  --enable-cloudwatch-logs-exports '["postgresql","upgrade"]' \
  --tags '[
    {"Key":"Environment","Value":"production"},
    {"Key":"Team","Value":"backend"},
    {"Key":"Backup","Value":"daily"}
  ]'

# Wait for instance to become available
aws rds wait db-instance-available --db-instance-identifier production-api-db

# Get connection endpoint
aws rds describe-db-instances \
  --db-instance-identifier production-api-db \
  --query "DBInstances[0].Endpoint.{Address:Address,Port:Port}" \
  --output table

Retrieve Master Password from Secrets Manager

bash
# When using --manage-master-user-password, RDS stores the password in Secrets Manager
aws rds describe-db-instances \
  --db-instance-identifier production-api-db \
  --query "DBInstances[0].MasterUserSecret.SecretArn" \
  --output text

# Retrieve the secret value
aws secretsmanager get-secret-value \
  --secret-id arn:aws:secretsmanager:us-east-1:123456789012:secret:rds-db-secret-abc123 \
  --query SecretString --output text

Parameter Groups

bash
# Create a custom parameter group
aws rds create-db-parameter-group \
  --db-parameter-group-name production-pg16 \
  --db-parameter-group-family postgres16 \
  --description "Production PostgreSQL 16 parameters"

# Set performance parameters
aws rds modify-db-parameter-group \
  --db-parameter-group-name production-pg16 \
  --parameters \
    "ParameterName=max_connections,ParameterValue=200,ApplyMethod=pending-reboot" \
    "ParameterName=shared_buffers,ParameterValue={DBInstanceClassMemory/4},ApplyMethod=pending-reboot" \
    "ParameterName=effective_cache_size,ParameterValue={DBInstanceClassMemory*3/4},ApplyMethod=pending-reboot" \
    "ParameterName=work_mem,ParameterValue=65536,ApplyMethod=immediate" \
    "ParameterName=maintenance_work_mem,ParameterValue=524288,ApplyMethod=immediate" \
    "ParameterName=random_page_cost,ParameterValue=1.1,ApplyMethod=immediate" \
    "ParameterName=log_min_duration_statement,ParameterValue=1000,ApplyMethod=immediate" \
    "ParameterName=log_statement,ParameterValue=ddl,ApplyMethod=immediate" \
    "ParameterName=idle_in_transaction_session_timeout,ParameterValue=60000,ApplyMethod=immediate"

# Apply parameter group to the instance
aws rds modify-db-instance \
  --db-instance-identifier production-api-db \
  --db-parameter-group-name production-pg16 \
  --apply-immediately

Read Replicas

bash
# Create a read replica in the same region
aws rds create-db-instance-read-replica \
  --db-instance-identifier production-api-db-read1 \
  --source-db-instance-identifier production-api-db \
  --db-instance-class db.r6g.large \
  --availability-zone us-east-1b \
  --enable-performance-insights \
  --monitoring-interval 60 \
  --monitoring-role-arn arn:aws:iam::123456789012:role/rds-monitoring-role

# Create a cross-region read replica for DR
aws rds create-db-instance-read-replica \
  --db-instance-identifier dr-api-db-read \
  --source-db-instance-identifier arn:aws:rds:us-east-1:123456789012:db:production-api-db \
  --db-instance-class db.r6g.large \
  --region us-west-2 \
  --storage-encrypted \
  --kms-key-id alias/rds-dr-key

# Promote a read replica to standalone (for DR failover)
aws rds promote-read-replica \
  --db-instance-identifier dr-api-db-read

# Check replication lag
aws cloudwatch get-metric-statistics \
  --namespace AWS/RDS \
  --metric-name ReplicaLag \
  --dimensions Name=DBInstanceIdentifier,Value=production-api-db-read1 \
  --start-time "$(date -u -d '1 hour ago' +%Y-%m-%dT%H:%M:%SZ)" \
  --end-time "$(date -u +%Y-%m-%dT%H:%M:%SZ)" \
  --period 300 \
  --statistics Average \
  --output table

Snapshots and Point-in-Time Recovery

bash
# Create a manual snapshot
aws rds create-db-snapshot \
  --db-instance-identifier production-api-db \
  --db-snapshot-identifier production-api-db-pre-migration-$(date +%Y%m%d)

# Wait for snapshot to complete
aws rds wait db-snapshot-available \
  --db-snapshot-identifier production-api-db-pre-migration-20260324

# Restore from snapshot (creates a new instance)
aws rds restore-db-instance-from-db-snapshot \
  --db-instance-identifier production-api-db-restored \
  --db-snapshot-identifier production-api-db-pre-migration-20260324 \
  --db-instance-class db.r6g.large \
  --db-subnet-group-name production-db-subnets \
  --vpc-security-group-ids sg-db-access

# Point-in-time recovery (restore to a specific second)
aws rds restore-db-instance-to-point-in-time \
  --source-db-instance-identifier production-api-db \
  --target-db-instance-identifier production-api-db-pitr \
  --restore-time "2026-03-24T10:30:00Z" \
  --db-instance-class db.r6g.large \
  --db-subnet-group-name production-db-subnets

# Copy snapshot to another region
aws rds copy-db-snapshot \
  --source-db-snapshot-identifier arn:aws:rds:us-east-1:123456789012:snapshot:production-api-db-pre-migration-20260324 \
  --target-db-snapshot-identifier production-api-db-dr-copy \
  --region us-west-2 \
  --kms-key-id alias/rds-dr-key

# Delete old snapshots
aws rds delete-db-snapshot --db-snapshot-identifier old-snapshot-name

Monitoring and Alarms

bash
# Set CPU utilization alarm
aws cloudwatch put-metric-alarm \
  --alarm-name rds-production-cpu-high \
  --alarm-description "RDS CPU > 80% for 5 minutes" \
  --metric-name CPUUtilization \
  --namespace AWS/RDS \
  --dimensions Name=DBInstanceIdentifier,Value=production-api-db \
  --statistic Average \
  --period 300 \
  --threshold 80 \
  --comparison-operator GreaterThanThreshold \
  --evaluation-periods 1 \
  --alarm-actions arn:aws:sns:us-east-1:123456789012:db-alerts

# Set free storage space alarm (alert below 10 GB)
aws cloudwatch put-metric-alarm \
  --alarm-name rds-production-storage-low \
  --alarm-description "RDS free storage < 10GB" \
  --metric-name FreeStorageSpace \
  --namespace AWS/RDS \
  --dimensions Name=DBInstanceIdentifier,Value=production-api-db \
  --statistic Average \
  --period 300 \
  --threshold 10737418240 \
  --comparison-operator LessThanThreshold \
  --evaluation-periods 1 \
  --alarm-actions arn:aws:sns:us-east-1:123456789012:db-alerts

# Check current database connections
aws cloudwatch get-metric-statistics \
  --namespace AWS/RDS \
  --metric-name DatabaseConnections \
  --dimensions Name=DBInstanceIdentifier,Value=production-api-db \
  --start-time "$(date -u -d '1 hour ago' +%Y-%m-%dT%H:%M:%SZ)" \
  --end-time "$(date -u +%Y-%m-%dT%H:%M:%SZ)" \
  --period 300 \
  --statistics Average Maximum \
  --output table

Terraform RDS Example

hcl
resource "aws_db_subnet_group" "main" {
  name       = "production-db-subnets"
  subnet_ids = [aws_subnet.private_a.id, aws_subnet.private_b.id]

  tags = {
    Environment = "production"
  }
}

resource "aws_db_parameter_group" "postgres16" {
  name   = "production-pg16"
  family = "postgres16"

  parameter {
    name  = "max_connections"
    value = "200"
  }

  parameter {
    name         = "shared_buffers"
    value        = "{DBInstanceClassMemory/4}"
    apply_method = "pending-reboot"
  }

  parameter {
    name  = "log_min_duration_statement"
    value = "1000"
  }
}

resource "aws_db_instance" "main" {
  identifier     = "production-api-db"
  engine         = "postgres"
  engine_version = "16.4"
  instance_class = "db.r6g.large"

  allocated_storage     = 100
  max_allocated_storage = 500
  storage_type          = "gp3"
  storage_encrypted     = true
  kms_key_id            = aws_kms_key.rds.arn

  db_name  = "appdb"
  username = "appadmin"
  manage_master_user_password = true

  multi_az               = true
  db_subnet_group_name   = aws_db_subnet_group.main.name
  vpc_security_group_ids = [aws_security_group.db.id]
  parameter_group_name   = aws_db_parameter_group.postgres16.name

  backup_retention_period   = 14
  backup_window             = "03:00-04:00"
  maintenance_window        = "sun:05:00-sun:06:00"
  copy_tags_to_snapshot     = true
  deletion_protection       = true
  skip_final_snapshot       = false
  final_snapshot_identifier = "production-api-db-final"

  performance_insights_enabled          = true
  performance_insights_retention_period = 7
  monitoring_interval                   = 60
  monitoring_role_arn                   = aws_iam_role.rds_monitoring.arn

  enabled_cloudwatch_logs_exports = ["postgresql", "upgrade"]

  tags = {
    Environment = "production"
    Team        = "backend"
  }
}

resource "aws_db_instance" "read_replica" {
  identifier          = "production-api-db-read1"
  replicate_source_db = aws_db_instance.main.identifier
  instance_class      = "db.r6g.large"

  performance_insights_enabled = true
  monitoring_interval          = 60
  monitoring_role_arn          = aws_iam_role.rds_monitoring.arn
}

Troubleshooting

ProblemCauseFix
Cannot connect to RDSSecurity group blocks trafficVerify SG allows app subnet CIDR on DB port
Storage fullAuto-scaling not enabled or limit reachedSet --max-allocated-storage; increase manually
High replication lagWrite-heavy workload or replica undersizedUpgrade replica instance class; reduce write volume
Parameter change not appliedRequires reboot for static paramsReboot with --force-failover during maintenance window
Snapshot restore slowLarge database sizeUse larger instance class for restore; consider PITR
Performance Insights emptyNot enabled or instance type unsupportedEnable PI; check instance class supports it
Multi-AZ failover happenedHardware or AZ failureCheck RDS events; review failover logs
Connection count maxed outApplication connection leakImplement connection pooling (PgBouncer/RDS Proxy)
Master password unknownUsing managed secretRetrieve from Secrets Manager ARN in instance details

Related Skills

Frequently asked questions

What does the Aws Rds AI skill do?

Provision and manage RDS databases. Configure backups, replication, and security. Use when deploying managed relational databases on AWS.

Why use Aws Rds on TypingMind?

Because you install it once and use it with any model. Aws 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 Rds in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/cloud-aws/aws-rds. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Aws 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 Rds?

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

Is the Aws Rds AI skill free?

Yes. It is published on GitHub by BagelHole 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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