...we could get the top 3 CPU users grouped by application (app) and process type (proc) like this: topk(3, sum by (app, proc) (rate(instance_cpu_time_ns[5m]))) Assuming this metric contains one time series per running instance, you could count the number of running instances per application ...

June 12, 2026 - It tells Prometheus which labels to keep in the result, allowing you to group related time series, like by service, region, or environment. This lets you move from individual metrics to more useful summaries that still carry enough context to ...

September 26, 2025 - This architecture is why Prometheus ...sts_total)) This query works in two steps. First, count by (status_code) (http_requests_total) groups all HTTP requests by their status code (like 200, 404, 500)....

December 17, 2025 - However, understanding how many unique values exist for a given label is crucial for cardinality management and query optimization. This guide shows you how to count unique label values using PromQL. Use count(group by (label_name) (metric_name)) to ...

August 10, 2020 - group always produces 1 as a the ... aggregation's label handling that is what's important rather than the numeric result: count without(cpu) ( group without(mode) (node_cpu_seconds_total) )...

Available aggregation operators: sum(), min(), max(), avg(), stddev(), stdvar(), count(), count_values(), group(), bottomk(), topk(), quantile() ... Only keep series from the left-hand side whose sample values are larger than their right-hand-side matches: ... histogram_quantile( 0.9, sum by(le, path, method) ( rate(demo_api_request_duration_seconds_bucket[5m]) ) )

December 17, 2020 - count(group by(le, job) (demo_api_request_duration_seconds_bucket)) This way, you are able to get a good idea about the cost split-up of your metrics. For understanding the semantic meaning of your metrics, their documentation string and metric type information (counter, gauge, histogram, summary) are very useful. This information is not directly accessible via PromQL, but the Prometheus server keeps it in memory for each target and it can be queried via another metadata API endpoint.

June 3, 2025 - If you’re familiar with SQL, you’ll remember that GROUP BY allows you to group results by a field (e.g country or city) and apply an aggregate function, such as AVG() or COUNT(), to values of another field.

August 5, 2025 - If you want to count the total number of requests grouped by the method label (e.g., GET, POST), you can use: ... This query sums the total requests and groups the result by the method label, giving you the total number of requests for each HTTP method.

March 30, 2023 - What Grafana version and what operating system are you using? Grafana v9.1.4 What are you trying to achieve? I’m collecting metrics about log files with filestat_exporter, and i would like to have graphic with the count of rotated logs per day based on values of the label path. file_stat_size_bytes{fqdn=~“$fqdn”,path=~“/var/log/mylog-[0-9].*.log”} so the path label has values like this: /var/log/mylog-2023-03-18.0.log /var/log/mylog-2023-03-18.1.log /var/log/mylog-2023-03-18.2.log ...

June 15, 2017 - Is there a way to do a group by query on Prometheus database like there’s for Graphite databases?

September 6, 2024 - Data Explosion: Grouping by numerous labels might result in an explosion of time series. Be mindful of this to avoid overwhelming your Prometheus server. Misleading Aggregations: Ensure your by() clauses make logical sense to avoid misleading aggregations. Double-check that the labels used align with your intended analysis. The count_values() function offers an alternative approach to counting unique label values:

October 7, 2024 - PromQL (Prometheus Query Language) is a powerful query language used to extract and analyze metrics from time-series data stored in Prometheus. It’s designed for use in monitoring and alerting systems, allowing users to query and aggregate metrics effectively. In this blog, we’ll cover grouping in PromQL, explore the core functions, and look at various ways to combine them to build insightful queries.

December 2, 2024 - To count unique label values in Prometheus, you can use the count function along with the by clause to aggregate metrics based on a specific label.

November 30, 2019 - For our purposes we can use any of the straightforward operators such as sum, min, or max; I'll use sum. Using 'sum(...) by (user)' will produce a series like this: ... Having generated this new vector, we simply count how many elements are in it with count().

March 24, 2021 - > > I am looking at something like: > group by (job) (my_updates_total{job="Job123"}) count by (job) (my_updates_total{job="Job123"}) > > It seems to work but feels a bit odd, is it right? > > -- > You received this message because you are subscribed to the Google Groups "Prometheus Users" group.

July 24, 2024 - Prometheus Query Language (PromQL) offers powerful tools for label grouping. The primary method involves using the group() operator along with the by clause.

In case the threshold value is not aligned to one of the bucket boundaries of the histogram, either linear (for NHCB and zero buckets of exponential histogram) or exponential (for non zero bucket of exponential histogram) interpolation is applied to compute the estimated count of observations that remain in the bucket containing the threshold. In case when some observations get trimmed, the new sum of observation values is recomputed (approximately) based on the remaining observations. The following binary comparison operators exist in Prometheus: ... Comparison operators are defined between scalar/scalar, vector/scalar, and vector/vector value pairs. By default they filter.