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MySQL alerting

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You can use Grafana Alerting with MySQL to create alerts based on your MySQL data. This allows you to monitor metrics, detect anomalies, and receive notifications when specific conditions are met.

For general information about Grafana Alerting, refer to Grafana Alerting.

Before you begin

Before creating alerts with MySQL, ensure you have:

• A MySQL data source configured in Grafana.
• Appropriate permissions to create alert rules.
• Understanding of the metrics you want to monitor.

Supported query types

MySQL alerting works with time series queries that return numeric data over time. Table formatted queries are not supported in alert rule conditions.

To create a valid alert query:

• Include a time column that returns a SQL datetime or UNIX epoch timestamp
• Return numeric values for the metrics you want to alert on
• Sort results by the time column

For more information on writing time series queries, refer to MySQL query editor.

Query format requirements

Create an alert rule

To create an alert rule using MySQL:

1. Navigate to Alerting > Alert rules.
2. Click New alert rule.
3. Enter a name for the alert rule.
4. Select your MySQL data source.
5. Build your query using the query editor:
   • Set the Format to Time series
   • Include a time column using the $__time() or $__timeGroup() macro
   • Add numeric columns for the values to monitor
   • Use $__timeFilter() to filter data by the dashboard time range
6. Configure the alert condition (for example, when the average is above a threshold).
7. Set the evaluation interval and pending period.
8. Configure notifications and labels.
9. Click Save rule.

For detailed instructions, refer to Create a Grafana-managed alert rule.

Example alert queries

The following examples show common alerting scenarios with MySQL.

Alert on high error count

Monitor the number of errors over time:

SQL Copy

SELECT
  $__timeGroup(created_at, '1m') AS time,
  COUNT(*) AS error_count
FROM error_logs
WHERE $__timeFilter(created_at)
  AND level = 'error'
GROUP BY time
ORDER BY time

Condition: When error_count is above 100.

Alert on average response time

Monitor API response times:

SQL Copy

SELECT
  $__timeGroup(request_time, '5m') AS time,
  AVG(response_time_ms) AS avg_response_time
FROM api_requests
WHERE $__timeFilter(request_time)
GROUP BY time
ORDER BY time

Condition: When avg_response_time is above 500 (milliseconds).

Alert on low order volume

Detect drops in order activity:

SQL Copy

SELECT
  $__timeGroup(order_date, '1h') AS time,
  COUNT(*) AS order_count
FROM orders
WHERE $__timeFilter(order_date)
GROUP BY time
ORDER BY time

Condition: When order_count is below 10.

Alert on disk usage percentage

Monitor database storage metrics:

SQL Copy

SELECT
  $__timeGroup(recorded_at, '5m') AS time,
  AVG(disk_used_percent) AS disk_usage
FROM system_metrics
WHERE $__timeFilter(recorded_at)
  AND metric_type = 'disk'
GROUP BY time
ORDER BY time

Condition: When disk_usage is above 85.

Limitations

When using MySQL with Grafana Alerting, be aware of the following limitations:

Template variables not supported

Alert queries cannot contain template variables. Grafana evaluates alert rules on the backend without dashboard context, so variables like $hostname or $environment won’t be resolved.

If your dashboard query uses template variables, create a separate query for alerting with hard coded values.

Table format not supported

Queries using the Table format cannot be used for alerting. Set the query format to Time series and ensure your query returns a time column.

Query timeout

Complex queries with large datasets may timeout during alert evaluation. Optimize queries for alerting by:

• Adding appropriate WHERE clauses to limit data
• Using indexes on time and filter columns
• Reducing the time range evaluated

Best practices

Follow these best practices when creating MySQL alerts:

• Use time series format: Always set the query format to Time series for alert queries.
• Include time filters: Use the $__timeFilter() macro to limit data to the evaluation window.
• Optimize queries: Add indexes on columns used in WHERE clauses and GROUP BY.
• Test queries first: Verify your query returns expected results in Explore before creating an alert.
• Set realistic thresholds: Base alert thresholds on historical data patterns.
• Use meaningful names: Give alert rules descriptive names that indicate what they monitor.