Intelligent RDS Monitoring: Connecting AWS RDS to pgEdge AI DBA Workbench

AWS RDS handles operations like provisioning, patching, and backups. What it doesn’t do is tell you why your query latency spiked at 2am, whether that replication lag is trending up, or what to do about it.

The pgEdge AI DBA Workbench connects to any PostgreSQL 14+ instance — including RDS — over the standard wire protocol. No agent on the host, no migration required. Once connected, it collects metrics across 34 probes, runs three-tier anomaly detection, and gives Ellie (an optional AI assistant) the context she needs to walk you through diagnosis and suggest fixes.

This guide covers the full setup: connecting your RDS instance to the Workbench, the SSL/TLS configuration AWS requires, and what you’ll see once it’s running.

Prerequisites

Before diving into the integration, ensure your environment meets the following requirements:

1. AI DBA Workbench Core Services

Your Workbench environment must be installed and active. This guide assumes you are running on a Linux-based server (e.g., RHEL/CentOS or Ubuntu).

Verify that the core services are running:

# Start AI DBA Workbench core components
systemctl start pgedge-ai-dba-collector.service
systemctl start pgedge-ai-dba-server.service
systemctl start pgedge-ai-dba-alerter.service

# Update SELinux policy to allow Nginx to bind to port 8444
semanage port -a -t http_port_t -p tcp 8444

#Start the nginx Service
systemctl start nginx.service

Note: This guide assumes installation via the (open source, and free to download) pgEdge Enterprise repository. Alternative setups, such as Docker-based deployments, follow a different configuration process and are not covered in this guide.

2. Create a Workbench Superuser

You need administrative access within the Workbench to add new servers and clusters.

# Add the admin user
/usr/bin/ai-dba-server -add-user -username admin -data-dir /var/lib/pgedge/ai-dba-server/

# Grant superuser privileges
./ai-dba-server -set-superuser -username admin -data-dir /var/lib/pgedge/ai-dba-server/
# Expected Output: User 'admin' is now a superuser

3. Prepare Your RDS Instance

• Log in to the AWS RDS Console.

• Ensure your instance is configured for Public Access (if connecting from outside the VPC) and uses the Free Tier or higher.

• Note your Endpoint (Host) and Port (default: 5432).

• Ensure you have the postgres user password.

Step-by-Step Guide: Securely Connecting RDS

Step 1: Secure Your Connection with the RDS Global Bundle

AWS RDS uses specific CA certificates for SSL/TLS. To use verify-full security (the gold standard for production), the Workbench needs to trust the AWS Root CA.

Download the global bundle certificate:

curl -o global-bundle.pem https://truststore.pki.rds.amazonaws.com/global/global-bundle.pem

Step 2: Configure Permissions and Certificate Path

The AI DBA Workbench runs under the pgedge user. You must move the certificate to a directory the service can access and set the correct ownership.

# Copy to the AI DBA server directory
cp global-bundle.pem /var/lib/pgedge/ai-dba-server/rds-global-bundle.pem

# Set appropriate ownership and permissions
chown pgedge:pgedge /var/lib/pgedge/ai-dba-server/rds-global-bundle.pem
chmod 644 /var/lib/pgedge/ai-dba-server/rds-global-bundle.pem

# Restart the service to apply changes
systemctl restart pgedge-ai-dba-server.service

Integrating RDS via the Workbench UI

Step 3: Log In to the Workbench

Launch your browser and navigate to the Workbench GUI (typically http://localhost:8444/). Log in with the admin credentials you created earlier.

Step 4: Organize with Server Groups

Grouping your resources keeps your dashboard clean, especially as you add more environments.

• Navigate to Clusters in the sidebar.

• Click New Group.

• Name it RDS.

• Click Save.

RDS group successfully created in the cluster navigator

Step 5: Define the RDS Cluster

• Inside the RDS group, click New Cluster.

• Name: rds-cluster

• Replication Type: Select Other.

  Why? Since RDS manages its own replication (Multi-AZ/Read Replicas), the Workbench treats it as an external cluster.

• Click Save.

The Cluster Navigator panel showing the RDS group structure.

Drag the newly created cluster and drop it into the RDS group to organize your workspace.

Step 6: Add your RDS Instance as a Server

This is where we link the specific database node. Click Add-server.

• Click Add-server.

• Enter the details from your AWS Console:

  Host: your-db-instance.xxxx.rds.amazonaws.com

  Port: 5432

  User: postgres

  SSL: verify-full

  SSL Root Certificate Path: /var/lib/pgedge/ai-dba-server/rds-global-bundle.pem

• Select the rds-cluster and set the Role to Node.

• Click Save.

A composite view of the RDS server registration process, including connection details, SSL settings, and cluster selection.

Exploring the AI-Driven Insights

Once connected, your RDS instance becomes part of the pgEdge ecosystem. Here’s what you should explore first:

The AI Overview

The AI Overview doesn’t just show you data; it interprets it. It provides a narrative summary of your database health, highlighting potential bottlenecks and offering performance suggestions.

The AI Overview dashboard provides high-level health and performance insights.

The Workbench main interface shows the successfully integrated RDS server.

Real-Time Metrics & Visualizations

Get granular with dashboards covering everything from connection counts to query latency. These visual cues help you spot trends before they become issues.

Real-time metrics dashboard with graphs for CPU, memory, and query latency.

Detailed query performance analytics and execution trends.

System resource utilization and throughput monitoring.

Database activity tracking and active connection counts over time.

I/O performance statistics and storage utilization metrics.

Administration & Alerting

Set up custom alert rules and notification channels (like Slack or PagerDuty) via the Administration Settings to ensure you’re always informed about the state of your RDS instance.

The Administration Settings interface for managing users, permissions, and automated alerts.