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A blank error-rate graph after zooming does not necessarily mean Prometheus stopped receiving metrics. In a payments-incident account by Sergey Shinder, a panel showed an error spike across a full day, then returned no data when narrowed to roughly 20 minutes. The reported cause was a rate-query window shorter than the service’s 60-second scrape cadence. Grafana’s current documentation confirms the underlying risk: rate-window variables depend on the configured scrape interval, so an incorrect setting can leave a zoomed-in query without enough samples.
Why the line disappeared after zooming
Shinder’s account describes an error-rate panel that divided the rate of a 5xx counter by the rate of all requests. Both rate() expressions used Grafana’s $__interval. On the one-day view, the dynamically calculated interval was about two minutes, and the graph showed a bump. After selecting the roughly 20-minute period around the event, the interval would have been about two seconds, but the data source’s 15-second minimum interval raised it to 15 seconds. The service was reportedly scraped every 60 seconds. Those incident details come from the author’s personal case report, not an independently audited postmortem. Read Shinder’s account on DEV Community.
A 15-second rate window is too short to contain two samples when new samples arrive only every 60 seconds. Prometheus’s rate() needs at least two samples in the selected range to calculate a rate. With fewer than two, the expression has no rate to return at that evaluation step. A graph can therefore look healthy over a broad range and go blank when the range selector shrinks below the actual sample cadence. That symptom alone does not establish that the service stopped emitting metrics.
How Grafana’s interval variables affect a rate query
Grafana calculates $__interval using the selected time range and panel width. Zooming changes the range, which can make the interval smaller. That is useful for adjusting graph resolution, but a rate calculation also needs a window wide enough to capture samples.
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Grafana documents $__rate_interval specifically for rate() and increase(). Its calculation is max($__interval + scrape_interval, 4 * scrape_interval). Grafana uses the per-query Min step when one is set; otherwise, it uses the data source’s Scrape interval setting. The four-scrape-interval floor is intended to give rate calculations enough samples, but it only works when Grafana’s scrape-interval value reflects the actual cadence. Grafana’s Prometheus template-variable documentation warns that leaving the data source at its 15-second default when Prometheus actually scrapes every 60 seconds can still make $__rate_interval too small.
Fix the panel query and align scrape settings
- Check the real cadence. Find the affected target’s
scrape_intervalin the Prometheus configuration. Compare it with the Grafana data source’s Scrape interval setting. - Inspect the range selector. Open the panel query and look inside each
rate()orincrease()expression. Check whether it uses$__interval, then compare the resulting range at a broad view and at the zoom level where the line disappears. - Use the rate-specific variable. For a panel rate query, use a range such as
rate(http_requests_total[$__rate_interval])rather than placing$__intervalinsiderate(). - Set Grafana’s scrape interval accurately. In the Grafana data source configuration for Prometheus, set Scrape interval to match the actual Prometheus cadence. Otherwise,
$__rate_intervalmay be calculated from the wrong value. - Retest at the diagnostic range. Zoom back into the outage window and confirm that the panel returns a rate. If it remains blank, verify that the target has samples for the selected metrics and time range, and that the query’s labels and filters match those series.
What to do when targets have different scrape cadences
If targets served through a data source use different scrape intervals, Grafana advises setting the data source interval to the longest interval in use, or overriding the per-query Min step on panels that need a different value. The choice depends on the panel: a single conservative data-source value is simpler, while a per-query override can make sense when a particular panel targets a known cadence. The value used by Grafana must not imply a faster scrape cadence than the target actually has.
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Use fixed windows in recording rules
Grafana’s $__rate_interval depends on query-evaluation context, so Grafana recommends a fixed range for recording-rule queries rather than relying on that dashboard variable. In Shinder’s account, alert ratios were converted to recording rules with a fixed five-minute window. That was the author’s reported follow-up practice, not a universal requirement; choose a fixed range appropriate to the rule’s evaluation and the data’s scrape cadence.
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Make the graph’s time window visible
Shinder also reports adding the rate window to each panel title, so maintainers could see the temporal resolution behind the plotted rate. The author says a dashboard-repository linter then found 43 additional queries with the same interval pattern. That count describes one repository, not a general measure of how often dashboards have this issue. The account also says the linter rejected $__interval inside irate(); that is the author’s lint policy, not a rule established by Grafana’s cited guidance.
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