Yes, that Grafana API seems to be unnecessary complicated compared to just
using PromQL.

On Sat, Feb 3, 2024, 17:16 'Brian Candler' via Prometheus Users <
[email protected]> wrote:

> Even without a subquery, a rule can include a range vector expression and
> then reduce it to an instant vector, e.g.
>
> expr: avg_over_time(snmp_scrape_duration_seconds[5m]) >= 3
>
> On Saturday 3 February 2024 at 16:04:56 UTC Ben Kochie wrote:
>
>> All rule evaluations are instant queries. You do all the "reducer
>> functions" in PromQL itself.
>>
>> For example, you can use subquery syntax to do something like
>> `avg_over_time()`.
>>
>> On Sat, Feb 3, 2024 at 5:02 PM 'Andrew Dedesko' via Prometheus Users <
>> [email protected]> wrote:
>>
>>> Hi,
>>>
>>> I'm wondering whether prometheus uses instant queries or range queries
>>> when evaluating alert expressions?  The context about why I'm asking might
>>> help clarify my question.
>>>
>>> I'm comparing Grafana Cloud's alerting functionality with prometheus.
>>> From Grafana Cloud we're querying Google Cloud Metrics with PromQL (it's
>>> Google's Monarch DB with a PromQL interface).  Grafana Cloud's alerting
>>> system takes your PromQL query and performs a *range query* against
>>> Google Cloud Metrics, returning multiple data points over the range you
>>> have selected (e.g. 10 minutes ago to now).  Then you need to choose a
>>> reducer function to turn the time series into an instant scalar (e.g. min,
>>> max, last, mean).
>>>
>>> Prometheus alerts don't seem to have an option for specifying a range
>>> and also don't have a reducer option.  So this leads me to believe
>>> prometheus uses instant queries to evaluate alert expressions.  But I'd
>>> like to know for sure.
>>>
>>> Thanks for reading!
>>>
>>> Here's the Grafana Cloud documentation on alert query ranges and
>>> reducers:
>>>
>>> https://grafana.com/docs/grafana/latest/alerting/alerting-rules/create-grafana-managed-rule/
>>>
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>>> .
>>>
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