Set up Database Observability on Grafana Labs

What Database Observability provides

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Beyond basic metrics

Traditional database monitoring tells you something is wrong. Database Observability tells you why. It surfaces query-level performance data (RED metrics, explain plans, query samples, wait events, and schema details) all inside Grafana Cloud.

Basic monitoring	Database Observability
Queries per second (aggregate)	Which specific queries are slow and why
CPU and memory usage	Explain plans and wait events at the query level

What you can see

Database Observability gives you query-level visibility. It captures RED metrics (rate, errors, and duration) for tracked queries, so you can tell which ones are slow. Explain plans are available for SELECT queries. Write statements such as INSERT, UPDATE, and DELETE cannot be explained.

You can open a query to investigate it, and also get the signals that explain its performance:

Query samples: individual executions with timing. Parameters are redacted by default.
Explain plans: how the database executes a query, with cost-coded nodes highlighting expensive operations
Wait events: where a query spends time waiting for locks, I/O, or other resources instead of executing
Table schemas: table structures, indexes, and constraints that may reveal missing indexes

Managed database support

Database Observability works with the following self-managed databases and managed cloud services:

Self-managed MySQL and PostgreSQL
Amazon RDS (MySQL and PostgreSQL)
Amazon Aurora (MySQL and PostgreSQL)
Google Cloud SQL (MySQL and PostgreSQL)
Azure Database for MySQL and PostgreSQL

How Database Observability works

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How the data flows

Grafana Alloy runs alongside your database and reads its built-in statistics. Where those statistics come from depends on the database:

PostgreSQL: pg_stat_statements for aggregate query statistics and pg_stat_activity for active sessions. The pg_stat_statements extension must be installed and enabled.
MySQL: Performance Schema, which is enabled by default in MySQL 8.0 and later

Alloy splits that data into two streams and forwards each to a different Grafana Cloud backend:

Metrics (query counts, latency, errors, and resource usage) are scraped by database exporters and sent to Grafana Cloud Metrics.
Logs (query samples, explain plans, schema details, and wait events) are collected by the Database Observability components and sent to Grafana Cloud Logs.

Grafana Cloud provides Database Observability dashboards that bring the metrics and logs together into a single view of query performance, starting with the Queries Overview dashboard.

Database Observability is designed to minimize impact on your production databases. To capture an explain plan, it runs EXPLAIN, not EXPLAIN ANALYZE, so the query itself does not run. That has minimal overhead for most queries.

When you collect more than you need

Query samples, schema details, and wait events are sent to Grafana Cloud Logs along with the metrics. If that is more than you need, Requirements and overhead lists three changes:

Raise collect_interval, for example from 1 minute to 5 minutes.
Lower explain_plans.per_collect_ratio, for example to 0.5 or lower.
Exclude schemas you don’t need (exclude_schemas on MySQL) or databases you don’t need (exclude_databases on PostgreSQL).

Tune Alloy collection has a high-volume example of those same settings.

Common setup pitfalls

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Before you try the hands-on path

If you decide to install and explore Database Observability, it’s important to keep in mind to start from the Configuration page.

The setup guides recommend generating your Alloy configuration from the Database Observability Configuration page. That page builds the config for your database and deployment, so you don’t have to assemble the components by hand.

If you hand-write or edit the config, these mistakes stop data from arriving.

Where setup goes wrong

Pitfall	What happens	What to check
Incomplete Alloy config	The `database_observability.mysql` or `database_observability.postgres` component is missing its required `data_source_name` (the database connection) or its `forward_to` destination, so nothing is collected.	Both `data_source_name` and `forward_to` are set on the component.
Missing endpoints	The config has no `prometheus.remote_write` for metrics or `loki.write` for logs, so telemetry is collected but never reaches Grafana Cloud.	Both write blocks point at your Grafana Cloud Metrics and Grafana Cloud Logs endpoints with valid credentials.
Inconsistent job label	The `job` label doesn’t use the value from the generated config (`integrations/db-o11y`), or the metrics and logs relabel rules don’t match, so your data isn’t labeled the way Database Observability expects.	Your `discovery.relabel` and `loki.relabel` blocks both set `job` to `integrations/db-o11y`, and their rules stay consistent with each other.
Database side not prepared	Performance Schema (MySQL) isn’t enabled, or the `pg_stat_statements` extension (PostgreSQL) isn’t enabled in each database you want to monitor, so the built-in statistics Alloy reads don’t exist.	The prerequisites for your database are in place before Alloy starts. For PostgreSQL, confirm the extension exists in each database, not only on the server.

Confirm it’s working before you troubleshoot

After Alloy is running, the Configuration page runs status checks for your instance. If data isn’t showing up, start there. A failing check points at one of the gaps above, which is faster than searching the dashboards for data that never arrived.

Set up a managed database

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Set up a managed database

The hands-on paths on the MySQL and PostgreSQL slides are for a database you run yourself. Amazon RDS, Amazon Aurora, Google Cloud SQL, and Azure Database use the same Database Observability features, and each has its own setup guide.

Each of those guides follows the same three steps:

Prepare the database. Set the parameters or flags the guide lists, restart the instance when a change requires it, and create the monitoring user. For PostgreSQL, enable the pg_stat_statements extension in each database you want to monitor.
Configure Grafana Alloy so it can reach that instance.
Verify that query metrics appear in Database Observability.

Reach a Cloud SQL instance

Google Cloud SQL can be reached by private IP, by public IP with authorized networks, or by the Cloud SQL Auth Proxy. When you use the proxy, point Alloy at the proxy address. Avoid sending Alloy through a load balancer or a connection pooler.

Skip the provider’s system database

Grafana Alloy 1.17 and later excludes these provider system databases by default. If you run an older Alloy, exclude the database for your service yourself. The setup guide for your service shows where to set that exclusion.

Service	Database to exclude
Amazon RDS and Amazon Aurora	`rdsadmin`
Google Cloud SQL	`cloudsqladmin`
Azure Database (MySQL and PostgreSQL)	`azure_sys` and `azure_maintenance`

Setup guides

Choose the guide that matches your engine and your service:

MySQL with Database Observability

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MySQL with Database Observability

Database Observability gives you deep visibility into MySQL query performance. This slide’s path is for a database you run yourself.


What it monitors	Query performance, explain plans, wait events, query samples, table schemas
How it works	Grafana Alloy reads from MySQL Performance Schema (enabled by default in 8.0+)
What you see	Top queries by duration, explain plans with cost highlighting, wait events, query samples
This path	Self-managed MySQL 8.0 or later
Managed services	Amazon RDS, Amazon Aurora, Google Cloud SQL, and Azure Database each have a setup guide

What you’ll get

Queries Overview dashboard showing RED metrics for tracked queries
Explain plans revealing full table scans, missing indexes, and expensive joins
Wait events showing lock contention, I/O bottlenecks, and resource waits
Query samples with individual execution timing
Table schemas highlighting index coverage and constraints

Before you start

A few things to keep in mind:

MySQL 8.0 or later is required. MariaDB isn’t supported.
Query statistics need PROCESS, REPLICATION CLIENT, and SELECT on performance_schema.
Schema details and explain plans also need SELECT and SHOW VIEW on each schema you monitor, or on all schemas if you want every schema. The path below grants all schemas.
Amazon RDS, Amazon Aurora, Google Cloud SQL, and Azure Database use a separate setup guide, not this path.

The path below walks you through each step.

Learning path

MySQL Database Observability

Set up Grafana Cloud Database Observability for MySQL to monitor query performance, explain plans, wait events, and query samples.

16 min

Intermediate

Docs & blog posts

Open in Grafana Cloud

Complete this learning path directly in your Grafana Cloud stack with an interactive learning experience.

Open in Grafana Cloud

View on website

Path completed

PostgreSQL with Database Observability

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PostgreSQL with Database Observability

Database Observability gives you deep visibility into PostgreSQL query performance. This slide’s path is for a database you run yourself.


What it monitors	Query performance, explain plans, wait events, query samples, table schemas
How it works	Grafana Alloy reads from `pg_stat_statements` and `pg_stat_activity`
What you see	Top queries by duration, explain plans with cost highlighting, wait events, query samples
This path	Self-managed PostgreSQL 14 or later
Managed services	Amazon RDS, Amazon Aurora, Google Cloud SQL, and Azure Database each have a setup guide

What you’ll get

Queries Overview dashboard showing RED metrics for tracked queries
Explain plans with visual graphs showing scan types, join strategies, and cost distribution
Wait events categorized by I/O, lock, and network waits from pg_stat_activity
Query samples with individual execution timing. Parameters are redacted by default.
Table schemas showing structures, indexes, and constraints

Before you start

A few things to keep in mind:

PostgreSQL 14 or later is required.
Load pg_stat_statements in shared_preload_libraries. Changing that setting requires a restart. Then create the extension in each database you want to monitor.
Query statistics need the pg_monitor and pg_read_all_stats roles.
Schema details and explain plans also need USAGE on each schema and SELECT on all tables in that schema, or the pg_read_all_data role if you want every object.
Amazon RDS, Amazon Aurora, Google Cloud SQL, and Azure Database use a separate setup guide, not this path.

The path below walks you through each step.

Learning path

PostgreSQL Database Observability

Set up Grafana Cloud Database Observability for PostgreSQL to monitor query performance, explain plans, wait events, and query samples.

15 min

Intermediate

Docs & blog posts

Open in Grafana Cloud

Complete this learning path directly in your Grafana Cloud stack with an interactive learning experience.

Open in Grafana Cloud

View on website

Path completed

Resources

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Resources for Database Observability

Use these resources to learn more.

Documentation and blogs

Database Observability documentation
Requirements and overhead
Tune Alloy collection
Set up MySQL, including Amazon RDS, Aurora, Google Cloud SQL, and Azure Database
Set up PostgreSQL, including Amazon RDS, Aurora, Google Cloud SQL, and Azure Database
Understand, diagnose, and optimize SQL queries: introducing Grafana Cloud Database Observability blog
Database Observability: how OpenTelemetry semantic conventions improve consistency across signals blog
Grafana Alloy documentation

Set up Database Observability on Grafana Labs

What Database Observability provides

Beyond basic metrics

What you can see

Managed database support

How Database Observability works

How the data flows

When you collect more than you need

Common setup pitfalls

Before you try the hands-on path

Where setup goes wrong

Confirm it’s working before you troubleshoot

Set up a managed database

Set up a managed database

Reach a Cloud SQL instance

Skip the provider’s system database

Setup guides

MySQL with Database Observability

MySQL with Database Observability

What you’ll get

Before you start

MySQL Database Observability

Open in Grafana Cloud

PostgreSQL with Database Observability

PostgreSQL with Database Observability

What you’ll get

Before you start

PostgreSQL Database Observability

Open in Grafana Cloud

Resources

Resources for Database Observability

Documentation and blogs

Community