I apologize if my explanation was unclear. I currently have four tables for 
web analytics data. I aim to create a query that triggers an alert when 
either the data retrieval stops or the number of rows falls below one. Any 
recommendations on how to formulate this query?
On Wednesday, February 14, 2024 at 2:28:33 PM UTC+1 Brian Candler wrote:

> I'm not sure why you're summing over increase, but if you plot that PromQL 
> expression in the web UI, does its value drop to zero when the problem 
> occurs?
>
> If so, just add "== 0" to the end of this expression and you can use it as 
> an alerting expression.
>
> On Wednesday 14 February 2024 at 11:37:32 UTC h0ksa wrote:
>
>> sum by (table) (increase(pinot_server_realtimeRowsConsumed_Count[5m])) 
>>
>> right now iam using this query 
>>
>> and rows are always rising in the database but i want to know when they 
>> stop and trigger an alert 
>>
>> On Wednesday, February 14, 2024 at 12:31:53 PM UTC+1 Brian Candler wrote:
>>
>>> What Prometheus metrics are you collecting? For example, do you have a 
>>> metric for the total number of rows in the database? Or do you have a 
>>> metric for the last time a row was inserted? Or some other metric which can 
>>> identify new rows - if so, what?
>>>
>>> What is the "previously suggested function"?
>>>
>>> We can't really suggest an alerting function without seeing the metrics 
>>> themselves.
>>>
>>> On Wednesday 14 February 2024 at 10:16:01 UTC h0ksa wrote:
>>>
>>>> Hi all ,
>>>>
>>>>
>>>> I have a dataset with 5000 rows, and my objective is to determine if 
>>>> any new rows have been inserted or created within the last 5 minutes. The 
>>>> previously suggested function may not be suitable because the row count is 
>>>> never expected to drop below 1. Consequently, my focus is on identifying 
>>>> instances where no rows have been created within a 5-minute timeframe. If 
>>>> no new rows are found during this period, I intend to initiate an alert. 
>>>> So 
>>>> which function to use 
>>>> increase()
>>>> delta()
>>>> increase()  or another one .
>>>
>>>

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