Installing pgEdge AI DBA Workbench
The pgEdge AI DBA Workbench is an AI-powered environment for monitoring, managing, and troubleshooting PostgreSQL systems. The Workbench combines a Model Context Protocol (MCP) server with a web-based user interface, a data collector, and an alert monitoring service. The Workbench enables users to query, analyze, and manage distributed PostgreSQL clusters using natural language and intelligent automation. The Workbench exposes pgEdge tools and data sources to both cloud-connected and locally hosted language models; this design ensures full functionality in air-gapped or secure environments.
Supported Installation Methods
The Workbench supports three deployment methods.
- Building from binary files is the easiest method to use to deploy the Workbench.
- Building from source code ensures you have the latest Workbench features available.
- The Docker guide walks you through a Workbench deployment via Docker using RPM/DEB packages from pgEdge.
Each installation method places files in different locations. The following table summarizes the locations for each deployment method.
| Resource | GitHub Release | Docker | RPM/DEB Package |
|---|---|---|---|
| Binaries | /opt/ai-workbench/ |
/usr/local/bin/ |
/usr/bin/ |
| Config | /etc/pgedge/ |
/etc/pgedge/ (mounted) |
/etc/pgedge/ |
| Data | user-chosen | /data/ |
/var/lib/pgedge/<service>/ |
| Logs | stderr |
stderr |
/var/log/pgedge/<service>/ |
| Client files | /opt/ai-workbench/client/ |
container-served | /usr/share/pgedge/ai-dba-client/ |
| systemd units | pgedge-ai-dba-*.service |
N/A | pgedge-ai-dba-*.service |
| Run-as user | user-chosen | container user | pgedge |
Note
RPM and DEB packages are available from the pgEdge Enterprise Repository, and are used in the Docker deployment method documented here. If you're using pgEdge packages for deployment, note that the packages create and use the pgedge user automatically, and you do not need to manually adjust your systemd files to manage the service.
Contact pgEdge for information about accessing the enterprise packages.
System Requirements
The following minimum requirements apply to all deployment environments. The collector, server, and alerter components share the following hardware requirements:
- A minimum of 4 CPU cores is required.
- The system requires at least 16 GB of RAM.
- The installation requires 120 GB of disk space for binaries and the datastore.
Before installing the Workbench with binary files or building the project from source, install the following software:
- Go 1.24 or later is required for building server-side components.
- Node.js 18 or later is required for building the web client.
- PostgreSQL 14 or later is required for the datastore.
- Make is required for build automation.
- nginx is required to serve the client.
Each component requires specific network access to operate correctly:
- The collector requires network access to each monitored PostgreSQL server.
- The alerter requires network access to the datastore.
- The server requires network access to the datastore and must be reachable by web client users.
- Database credentials for the datastore and each monitored PostgreSQL server are required.
Customizing Configuration Files
The installation guides linked above share the details required to get a minimal deployment of the Workbench installed and serving content. Additional configuration options are extensive; for details about options available in each configuration file, see:
- The collector guide covers tuned connection pools and SSL.
- The server guide covers TLS, authentication, and LLM integration.
- The alerter guide covers anomaly detection and notification channels.
- The web client guide covers proxy settings and build options.