PostgresAI – enterprise-grade Postgres observability tool

Expert-level Postgres monitoring tool designed for humans and AI systems

Built for senior DBAs, SREs, and AI systems who need rapid root cause analysis and deep performance insights. This isn't a tool for beginners — it's designed for Postgres experts who need to understand complex performance issues in minutes, not hours.

Part of Self-Driving Postgres - PostgresAI monitoring is a foundational component of PostgresAI's open-source Self-Driving Postgres (SDP) initiative, providing the advanced monitoring and intelligent root cause analysis capabilities essential for achieving higher levels of database automation.

Live demo

Experience the full monitoring solution: https://demo.postgres.ai (login: demo / password: demo)

Console.Postgres.ai integration

PostgresAI monitoring integrates with Console.Postgres.ai, enabling:

• Automated health checks (checkups) — Comprehensive database health assessments with actionable recommendations, running automatically on schedule
• PostgresAI consulting support — Consulting customers benefit from shared monitoring access, allowing the PostgresAI team to work more efficiently on performance optimization and troubleshooting

Key features

• Open source foundation – PostgresAI core components are Apache 2.0 licensed, ensuring transparency and community-driven development

• Metadata only — Only database metadata is collected (statistics, query patterns, wait events). No actual data or query parameters are accessed. See data privacy details

• Expert-focused design: Assumes deep Postgres knowledge and performance troubleshooting experience

• Universal integration – Works with any type of Postgres, including:

  • All popular cloud platforms (RDS, CloudSQL, Azure Database, Supabase, TigerData, and more)
  • Self-managed Postgres installations
  • Kubernetes deployments

• Top-down troubleshooting methodology: Follows the Four Golden Signals approach (Latency, Traffic, Errors, Saturation)

• Powerful dashboards featuring:

  • Emergency dashboard – "Shallow but wide" analysis of all database components and key metrics to identify problematic areas within 1 minute (ideal for incident troubleshooting)
  • Query analysis – Top-to-bottom examination with comprehensive metrics for complete visibility into performance patterns and bottlenecks
  • Wait event analysis – Similar to AWS RDS Performance Insights and CloudSQL Query Insights, providing deep visibility into database wait events

• Renowned PostgresAI health check reports – Comprehensive health assessments with actionable recommendations based on industry best practices and real-world experience

• AI-powered insights backed by human expertise – From diagnostics to mitigation strategies, combining artificial intelligence with seasoned Postgres expert knowledge for actionable recommendations

Documentation

• Getting started — Installation guides for CLI, Docker, Helm, and cloud platforms
• Dashboards — Complete reference for all 14 Grafana dashboards
• Metrics reference — Detailed metrics documentation
• Configuration — Customization and alerting setup
• Troubleshooting — Common issues and solutions
• Advanced topics — Multi-cluster, custom metrics, API integration

Data privacy: metadata only

PostgresAI monitoring collects only database metadata — no actual data or query parameters are ever accessed or stored.

What is collected

• Database statistics from system views (pg_stat_*)
• Normalized query texts from pg_stat_statements (with parameter values replaced by $1, $2, etc.)
• Wait event information from pg_stat_activity
• Table and index statistics (sizes, access patterns, bloat estimates)

What is NOT collected

• Actual table data
• Query parameter values
• Connection credentials
• Application data

Verify collected metrics

Review exactly what metrics are collected by examining the metric definitions:

• Prometheus sink metrics: metrics.yml (pgwatch-prometheus)
• PostgreSQL sink metrics (including normalized queries): metrics.yml (pgwatch-postgres)

Verify database permissions

The monitoring user has read-only access to metadata only. To review the exact SQL statements used to create the monitoring role:

npx postgresai@latest prepare-db --print-sql

This shows all GRANT statements and confirms the minimal, read-only nature of the permissions.

Get started with Console.Postgres.ai

The easiest way to set up PostgresAI monitoring is through Console.Postgres.ai:

1. Navigate to Checkup → Monitoring instances in the left menu
2. Click Choose plan
3. Select Starter or Scale plan

See pricing for plan details and features.