The reliable pattern is to run the official Prometheus mysqld_exporter beside your MySQL or MariaDB server, let it expose database metrics on an HTTP endpoint, and have Prometheus scrape that endpoint. Grafana then queries Prometheus for dashboards, recording rules, and alerts. Use a dedicated, least-privilege database account, restrict exporter access to your monitoring network, and tune scrape and query limits for the workload on your VPS.
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What the monitoring stack does
MySQL and MariaDB do not natively expose Prometheus-formatted metrics. The exporter acts as an adapter: it logs in to the database, reads status and performance information, and serves the results over HTTP. Prometheus periodically requests that endpoint and stores each value as a time series. Grafana reads those time series to draw panels and evaluate alerts.
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| Component | Responsibility | Typical location |
|---|---|---|
| MySQL or MariaDB | Runs the application data workload and provides status information to the exporter. | Your Linux VPS |
mysqld_exporter |
Uses a dedicated database login and exposes metrics over HTTP, commonly on port 9104. | The VPS or a monitoring host with database access |
| Prometheus | Scrapes the exporter endpoint, stores time-series samples, and evaluates recording and alerting rules. | The VPS, another server, or a managed Prometheus service |
| Grafana | Queries Prometheus for dashboards, visualizations, and notification rules. | Self-hosted or Grafana Cloud |
Keep the exporter close to the database when possible. A local process avoids exposing MySQL to a monitoring network, while Prometheus only needs access to the exporter’s HTTP port. Running the exporter elsewhere is also valid, but the monitoring host must be able to reach the database address and port, and both paths need firewall rules.
Check compatibility before installing
The current Prometheus exporter documentation lists support for MySQL 5.6 and newer and MariaDB 10.3 and newer. Older releases may still provide some metrics, but not every collection method is available on every older MySQL or MariaDB version. Confirm the server version and review collector compatibility before enabling a production dashboard.
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| Database | Documented supported versions | Important qualification |
|---|---|---|
| MySQL | 5.6 or newer | Collection support varies by server version. |
| MariaDB | 10.3 or newer | The maximum-connection account option is unavailable on some older releases, including MariaDB 10.1. |
Pin the exporter release you deploy rather than silently tracking a moving “latest” binary or container tag. Before upgrading either the database or exporter, verify that the release still supports the collectors your alerts use.
Create a dedicated database account
Do not give the exporter an application password. Create a separate account that can be revoked or rotated without affecting application traffic. The documented local IPv4 TCP pattern is:
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IDENTIFIED BY 'strong-secret'
WITH MAX_USER_CONNECTIONS 3;
GRANT PROCESS, REPLICATION CLIENT, SELECT
ON *.* TO 'exporter'@'127.0.0.1';PROCESS, REPLICATION CLIENT, and global SELECT are the grants used by the exporter’s documented setup. The MAX_USER_CONNECTIONS 3 clause limits simultaneous exporter sessions so an overloaded scrape schedule cannot consume an unbounded number of database connections. Some older MariaDB versions do not implement that account option; if your server rejects it, create the same user without the clause and enforce connection limits in the exporter and Prometheus configuration instead.
Make the account host match the connection method
MySQL and MariaDB authenticate a user together with its host pattern. A user created for 127.0.0.1 is not automatically the same user as exporter@localhost. Match the account to the address you put in the exporter configuration:
- TCP over IPv4: use
'exporter'@'127.0.0.1'and an address such as127.0.0.1:3306. - Unix socket: create a
'exporter'@'localhost'account and configure the socket path. Do not assume a socket connection will match the IPv4 account. - Remote exporter: replace the host part with the monitoring host’s permitted address, use firewall restrictions, and avoid a wildcard host unless you have a specific, controlled reason.
After creating the account, test the exact connection form that the exporter will use. This catches host-matching, password, socket-path, and TLS issues before Prometheus reports a failed scrape.
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Install and run mysqld_exporter
The exporter is available as a released binary or as a container. Choose one deployment method and keep its configuration under your normal service-management and secret-management controls.
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Download and pin a release appropriate for your VPS architecture, place the executable in a root-owned system path, and run it under a non-root service account. The exporter documentation supports command-line flags and a configuration file. Relevant settings include:
mysqld.address— the database host, port, or socket endpoint.mysqld.username— the dedicated exporter account.config.my-cnf— a client option file containing credentials and connection settings.exporter.query_timeout— the maximum time allowed for exporter queries.exporter.max_open_connections— the exporter-side cap on concurrent database connections.- Lock-wait timeout controls — limits how long a metrics query waits behind a database lock.
When both command-line options and a configuration file provide client-section values, the configuration-file values take precedence. Put the password in a protected file readable only by the exporter service account, not in a world-readable shell history or process listing.
Container deployment
Grafana’s documented container pattern uses the prom/mysqld-exporter image, publishes port 9104, and passes a DATA_SOURCE_NAME environment variable. A minimal template is:
docker network create monitoring
export DATA_SOURCE_NAME='user:password@(hostname:3306)/'
docker run -d
--name mysqld-exporter
--network monitoring
-p 9104:9104
-e DATA_SOURCE_NAME="$DATA_SOURCE_NAME"
prom/mysqld-exporterTreat this as a layout, not a credential-handling recommendation. Environment variables can be exposed through container inspection and operational tooling. Prefer a protected secret file or your platform’s secret store, pin the image version, and bind port 9104 only to the interface Prometheus uses. Do not publish 9104 directly to the public internet.
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If Prometheus runs in the same container network, it can scrape the exporter by its container name and port. If Prometheus runs on another host, allow only that host’s address through the VPS firewall. The database itself should remain protected by its own bind-address and firewall policy.
Expose and verify the exporter endpoint
Once the process is running, request its metrics endpoint from the Prometheus host or from the VPS during setup. A successful response is plain-text Prometheus metrics rather than an HTML error page. Confirm that the endpoint is listening on the intended interface and that a local firewall has not blocked it.
Grafana’s verification guidance names two useful first checks: mysql_version_info should identify the database version, and mysql_global_status_connections should report connection status. If neither appears, solve exporter-to-database authentication before changing Grafana panels.
Configure Prometheus to scrape the exporter
Add the exporter as a scrape target in Prometheus. The exact file path and reload mechanism depend on how Prometheus was installed, but the target normally resolves to port 9104:
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scrape_configs:
- job_name: mysql
static_configs:
- targets:
- 127.0.0.1:9104Replace the target with the exporter host name or address when Prometheus is remote. Keep the job label stable; dashboards and alert rules often select metrics by job. After editing the YAML, validate it with the Prometheus installation’s configuration check, reload Prometheus using its supported service or reload method, and open the Prometheus targets page. The target must show UP. A target that is DOWN means Prometheus cannot complete the HTTP scrape, regardless of whether the database itself is healthy.
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Choose a scrape interval deliberately
A very short interval increases HTTP requests, exporter queries, and stored samples. A long interval reduces overhead but makes short connection spikes and latency events harder to see. Start with the interval appropriate to your incident-response needs, then watch exporter scrape duration and database load. Do not increase frequency until you know the exporter completes comfortably within the interval.
Connect Grafana and build useful views
In Grafana, add Prometheus as the data source and select it for a MySQL dashboard. Verify the data source with a query for mysql_version_info before importing or building panels. A working version panel proves the path from database to exporter to Prometheus to Grafana; a connection-status panel then confirms that changing database state is being collected.
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Grafana’s MySQL exporter quickstart describes roughly 1,000 Prometheus time series by default. That is configuration-dependent: enabling additional collectors, database objects, or labels can change the count. High cardinality increases storage and query cost, so keep only metrics that answer an operational question.
Panels worth creating first
- Exporter reachability: show scrape success and scrape errors so a dashboard outage is not mistaken for a database outage.
- Version and uptime: display
mysql_version_infoand the server’s uptime metric to identify restarts and unexpected upgrades. - Connections: graph active connections and compare them with the configured server limit. Alert on sustained saturation, not a single brief burst.
- Throughput: chart query activity and other status counters as rates, which makes traffic changes easier to interpret than raw monotonically increasing totals.
- InnoDB health: include buffer-pool size and related activity when InnoDB is the storage engine carrying the workload.
- Replication: add replication panels only when the server is configured as a replica or source and the corresponding metrics exist.
- Host pressure: collect Linux node metrics separately for CPU, memory, filesystem, and disk I/O. Database exporter metrics cannot explain host exhaustion by themselves.
Use recording rules for expensive rates or aggregates that many panels share. Keep alert expressions tied to a clear action: for example, an operator should know whether to investigate connection leaks, storage pressure, replication, or a failed exporter.
Alerting that separates database faults from monitoring faults
Start with an alert when the Prometheus target is not being scraped. Pair it with a second alert for database symptoms, because a silent exporter can otherwise make every database panel appear normal. Useful alert groups include:
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- Exporter endpoint unreachable or scrape errors increasing.
- Unexpected database restart or uptime reset.
- Connection usage approaching the server’s configured ceiling for a sustained period.
- Query throughput or latency indicators deviating from the service’s normal operating range.
- InnoDB buffer-pool pressure or abnormal activity.
- Replication problems when replication is part of the topology.
- Linux disk, memory, or CPU exhaustion from node-level metrics.
Set a delay (“for” duration) long enough to avoid paging on one failed scrape, but short enough to catch a real outage. Test each rule by stopping the exporter in a maintenance window or using a staging database; confirm both notification routing and the runbook linked to the alert.
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Metrics collection is database work. On a busy VPS, an indiscriminate collector set or aggressive scrape interval can add contention exactly when the server is under stress.
- Limit permissions: grant only
PROCESS,REPLICATION CLIENT, andSELECTrequired by the documented setup. Do not reuse an application or administrative login. - Limit connections: use
MAX_USER_CONNECTIONS 3where supported and configureexporter.max_open_connections. The exporter documentation sets a default maximum of two open connections per scrape. - Bound waits: configure lock-wait and query-timeout controls so a metrics query cannot wait indefinitely behind application work.
- Restrict the network: firewall port 9104 to Prometheus, bind the exporter to a private or loopback address where possible, and never expose it broadly.
- Protect secrets: use a root-owned or service-account-owned client file, restrictive permissions, and a rotation procedure. Avoid putting passwords in shell history, public container manifests, or shared dashboards.
- Enable collectors selectively: every collector should answer a dashboard or alert question. Watch scrape duration, exporter errors, and database load after each change.
- Pin versions: record the exporter, database, Prometheus, and Grafana versions so a future upgrade can be rolled back.
Self-hosted stack or Grafana Cloud?
You can operate Prometheus and Grafana on your own infrastructure or use Grafana Cloud’s documented MySQL integration. The hosted integration uses Prometheus MySQL Exporter, supplies preconfigured dashboards, and includes 15 preconfigured alert rules according to Grafana Labs’ 2026 documentation. The open-source exporter remains the database adapter in either approach; the difference is who operates the storage, UI, upgrades, and alert delivery.
| Decision factor | Self-hosted Prometheus and Grafana | Grafana Cloud MySQL integration |
|---|---|---|
| Operational ownership | You patch, upgrade, back up, retain, and monitor Prometheus and Grafana. | The service operator maintains the hosted control plane; you still maintain the exporter and database credentials. |
| Network placement | Keep metrics inside your VPS or private network if desired. | Plan an outbound or private connectivity path from the exporter to the hosted service and protect credentials. |
| Retention and query cost | Choose local storage, retention, and capacity; hardware and administration are yours. | Retention and usage depend on the hosted service terms and current plan. |
| Dashboards and alerts | Build or import panels and rules yourself. | Preconfigured dashboards and 15 alert rules are documented for the MySQL integration. |
| Collector control | Full control over scrape intervals, collectors, recording rules, and labels. | Exporter settings remain yours, while hosted limits and integration defaults also apply. |
| Portability | Prometheus data and configuration stay under your control. | Migration requires planning for remote storage, dashboards, and alert configuration. |
| Monthly cost | Infrastructure and operational labor are your costs; no figure is established here. | Service pricing depends on the current Grafana Cloud offering and usage; check the current terms. |
Choose self-hosting when local control, private networking, or custom retention is more important than reducing operations. Choose the hosted path when you want managed storage and ready-made dashboards and accept service-dependent retention, connectivity, and cost.
Troubleshoot in the order the data flows
Prometheus target is DOWN
- From the Prometheus host, test the exporter HTTP endpoint and confirm it returns metrics.
- Check that the exporter is listening on the address and port in the scrape target, commonly
:9104. - Review firewall rules and container-network membership; allow Prometheus, not the whole internet.
- Read exporter logs for startup, bind, or database-connection errors, then recheck the target page.
The endpoint responds, but database metrics are missing
- Search the endpoint output for
mysql_version_infoandmysql_global_status_connections. - Test the exporter account with the same host, port or socket, and credentials.
- Verify the account’s host component:
127.0.0.1andlocalhostare different authentication identities. - Confirm the account has the documented grants and that the server version supports the collectors you enabled.
Authentication fails with “access denied”
Reset or rotate the dedicated password, check for a password character that was interpreted by a shell or container environment, and ensure the exporter is using the intended client file. If the connection moved from TCP to a Unix socket, create or grant the matching localhost account rather than changing the application account.
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Scrapes are slow or increase database load
- Measure exporter scrape duration and compare it with the Prometheus interval.
- Disable collectors that do not feed a dashboard or alert.
- Increase query and lock-wait controls only with an understanding of the resulting missing samples; never allow metrics queries to compete indefinitely with application transactions.
- Lower scrape frequency, reduce concurrent exporter connections, and inspect host CPU, memory, and disk pressure.
Metrics disappeared after an upgrade
Compare the exporter and database versions with the supported compatibility statement, inspect collector errors, and check whether a configuration-file value overrides a command-line value. Pin the last known-good exporter release while you test a compatible version and update dashboards that depended on renamed or unavailable collectors.
Operational checklist
- Database version is within the documented MySQL 5.6+ or MariaDB 10.3+ range.
- A dedicated exporter account exists with the required grants and a host pattern matching the connection method.
- The password is stored in a protected secret or client file.
- The exporter is pinned to a known release and bound to a restricted interface.
- Port 9104 is reachable only from Prometheus or the approved monitoring network.
- Prometheus shows the target as UP.
mysql_version_infoandmysql_global_status_connectionsappear in Prometheus.- Grafana panels cover reachability, uptime, connections, throughput, and InnoDB health; replication and host panels exist when those workloads are present.
- Alerts have tested notification routes and an owner-runbook.
- Scrape duration, exporter errors, database load, and time-series count are reviewed after changes.
What a healthy deployment looks like
A healthy setup has one clearly identified exporter endpoint, a Prometheus target that remains UP, and current values for version, connections, throughput, and storage-engine health. Credentials are limited to the exporter, the exporter cannot be reached from the public internet, and its query and connection limits prevent monitoring from becoming a second workload. Grafana makes those signals visible, while separate node metrics explain whether a database symptom is caused by CPU, memory, disk, or network pressure on the VPS.
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