Grafana Cloud Database Observability

SkillDatabases & data

Grafana Cloud Database Observability — query-level performance insights for MySQL and PostgreSQL. Covers setup with Grafana Alloy, query samples, visual explain plans, RED metrics, pg_stat_statements and Performance Schema integration, and correlation with application traces. Use when monitoring database performance, diagnosing slow queries, setting up database observability for MySQL or PostgreSQL (self-managed, RDS, Aurora, Azure, Cloud SQL), or correlating DB metrics with APM data.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Grafana Cloud Database Observability skill

What this skill tells your AI

The instructions your AI receives, as published by kilo-org/kilo-marketplace in skills/database-observability/SKILL.md and read by ahel’s review.

Docs: https://grafana.com/docs/grafana-cloud/monitor-applications/database-observability/

Provides query-level insights (RED metrics, query samples, explain plans) for MySQL and PostgreSQL without application code changes. Generally Available as of April 2026.

Supported Databases

DatabaseVariants
MySQLSelf-managed, RDS MySQL, Aurora MySQL, Cloud SQL MySQL, Azure Database for MySQL
PostgreSQLSelf-managed, RDS PostgreSQL, Aurora PostgreSQL, Cloud SQL PostgreSQL, Azure Database for PostgreSQL

Prerequisites

PostgreSQL

-- 1. Enable pg_stat_statements in postgresql.conf
-- shared_preload_libraries = 'pg_stat_statements'
-- Then restart PostgreSQL

-- 2. Create monitoring user
CREATE USER grafana_monitoring WITH PASSWORD 'secret';
GRANT pg_monitor TO grafana_monitoring;
GRANT CONNECT ON DATABASE mydb TO grafana_monitoring;

-- 3. Enable the extension
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

MySQL

-- Create monitoring user with least-privilege permissions
CREATE USER 'grafana_monitoring'@'%' IDENTIFIED BY 'secret';
GRANT SELECT, PROCESS, REPLICATION CLIENT ON *.* TO 'grafana_monitoring'@'%';
GRANT SELECT ON performance_schema.* TO 'grafana_monitoring'@'%';
FLUSH PRIVILEGES;

Alloy Configuration

PostgreSQL

database_observability.postgres "mydb" {
  data_source_name = "postgresql://grafana_monitoring:secret@localhost:5432/mydb?sslmode=disable"

  enable_collectors = ["pg_stat_statements", "query_samples", "schema_details"]

  forward_metrics_to = [prometheus.remote_write.cloud.receiver]
  forward_logs_to    = [loki.write.cloud.receiver]
}

prometheus.remote_write "cloud" {
  endpoint {
    url = sys.env("PROMETHEUS_URL")
    basic_auth {
      username = sys.env("PROMETHEUS_USER")
      password = sys.env("GRAFANA_CLOUD_API_KEY")
    }
  }
}

loki.write "cloud" {
  endpoint {
    url = sys.env("LOKI_URL")
    basic_auth {
      username = sys.env("LOKI_USER")
      password = sys.env("GRAFANA_CLOUD_API_KEY")
    }
  }
}

MySQL

database_observability.mysql "mydb" {
  data_source_name = "grafana_monitoring:secret@tcp(localhost:3306)/mydb"

  enable_collectors = ["query_samples", "explain_plans", "schema_details"]

  forward_metrics_to = [prometheus.remote_write.cloud.receiver]
  forward_logs_to    = [loki.write.cloud.receiver]
}

Key Metrics

# Query rate by database
rate(db_query_total{db_instance="mydb"}[5m])

# P95 query latency
histogram_quantile(0.95, rate(db_query_duration_seconds_bucket[5m]))

# Error rate
rate(db_query_errors_total[5m]) / rate(db_query_total[5m])

# Slow queries (over 1 second)
count(db_query_duration_seconds > 1) by (db_query_digest)

# Active connections
db_connections_active{db_instance="mydb"}

What You Get

Query Performance Dashboard (auto-provisioned):

  • Top queries by total time, call count, mean latency
  • Query samples with actual parameters and timing
  • Visual explain plans showing index usage, scan types, costs
  • RED metrics per query digest

Correlation with APM:

  • Link slow DB queries to the application traces that triggered them
  • db.statement, db.system, db.name OTel attributes connect DB spans to query samples
  • Drill from service latency spike → specific slow SQL query → explain plan

Alert Rules

groups:
  - name: database-observability
    rules:
      - alert: SlowQueryDetected
        expr: histogram_quantile(0.95, rate(db_query_duration_seconds_bucket[5m])) > 1
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "P95 query latency > 1s on {{ $labels.db_instance }}"

      - alert: HighDBErrorRate
        expr: rate(db_query_errors_total[5m]) / rate(db_query_total[5m]) > 0.05
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "DB error rate > 5% on {{ $labels.db_instance }}"

      - alert: TooManyConnections
        expr: db_connections_active / db_connections_max > 0.8
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "DB connection pool >80% on {{ $labels.db_instance }}"

Setup Checklist

  1. Enable pg_stat_statements (PostgreSQL) or Performance Schema (MySQL)
  2. Create least-privilege monitoring user
  3. Add database_observability.* block to Alloy config
  4. Verify metrics appear in Grafana Cloud → Database Observability
  5. Set up alerting on slow queries and error rates
  6. Enable trace correlation by ensuring app uses db.statement span attributes

Signals

GitHub stars
175
Forks
162
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
database-observability
Source
github.com/kilo-org/kilo-marketplace