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If Grafana sends a DatasourceNoData notification every four hours, the cadence alone does not identify the cause. Grafana creates a separate DatasourceNoData alert instance when an evaluation returns no data or only null values; later notifications may be repeats for an alert that is still firing, or may follow new No Data state transitions. Check the alert’s state history and the notification policy that matches this separate alert to tell which is happening.
What DatasourceNoData means
With the default No Data behavior, Grafana treats an evaluation that returns no series or all-null values as a No Data state. It creates a separate alert instance labeled alertname: DatasourceNoData, rather than simply changing the name of your 5xx-rate alert. That instance may not carry all the original rule’s labels, so it can match a different notification policy. See Grafana’s documentation on handling missing data.
This is different from a query returning a zero 5xx rate. Zero is a value; no series or null values mean Grafana cannot evaluate the expected value from that result. A rule can therefore be configured and operating while a particular evaluation produces no usable data.
Why the alert arrives every four hours
Grafana has separate timing controls for evaluating rules and notifying people. The evaluation group interval determines how often queries run. The pending period determines how long a condition must hold before the alert changes state. A notification policy’s repeat interval can send another notification while an alert remains firing. These settings do not establish what a four-hour cadence means in your deployment. Review the rule evaluation timing and notification behavior separately.
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Use the alert state history to distinguish repeated notifications for one continuously firing instance from separate transitions into No Data. Then inspect the notification policy matched by DatasourceNoData, including its repeat interval. The four-hour pattern may relate to notification repetition, evaluation and state changes, or another deployment-specific setting; the title alone cannot determine which.
Trace the missing result before changing the rule
- Identify the alert instance. In the alert details and state history, record the alert name, rule UID, data source UID, and event timestamps. Confirm whether each event belongs to the separate
DatasourceNoDatainstance. - Compare event timestamps with state transitions. If the instance stayed firing between messages, investigate notification repetition. If it repeatedly entered No Data, focus on why evaluations are returning missing or null results.
- Inspect the query result at an event time. Check whether the query returned no series, only null values, or a numeric value. Review its labels, range or time window, and aggregation. For a rate expression, check whether the numerator or denominator disappears when traffic is absent.
- Check the alert’s route. Because the no-data instance has its own alert name and may have different labels, verify which notification policy it matches rather than assuming it follows the original 5xx rule’s route.
The exact query and rule configuration are not specified here, so a particular PromQL defect cannot be diagnosed from the notification text alone. Grafana’s current documentation also notes that interface wording and behavior can vary by version and by whether a rule is Grafana-managed or data source-managed.
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Choose what missing telemetry should mean
Set the No Data response according to the monitoring objective, not just to stop the messages. Grafana documents four available responses: No Data, Alerting, Normal, and Keep Last State.
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- Alerting: Treat missing data as an alerting condition. Use this when an unevaluable signal should be handled as an incident rather than as a separate informational state.
- Normal: Treat missing data as non-alerting. This may quiet notifications, but it can also hide telemetry loss.
- Keep Last State: Preserve the previous state through a missing result. This can avoid reacting to a temporary gap, but does not make the missing data observable as a new alert state.
Decide whether missing telemetry is actionable, whether absence should count as zero or remain unknown, whether brief gaps should preserve the prior state, and which route should receive the no-data alert. These are monitoring-policy decisions, not merely notification cleanup.
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When absence really should count as zero
If a missing Prometheus series genuinely means a zero 5xx rate, Grafana gives this example for making the query return zero when the original query returns nothing: your_metric_query OR on() vector(0). See Grafana’s Prometheus alerting guidance.
Use this pattern only when absence means zero for the metric and service in question. If missing series can indicate a scrape failure, broken instrumentation, or another meaningful telemetry gap, converting absence to zero can mask the problem. In that case, retain a missing-data signal and route it appropriately.
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