Yes, you can you use label replace to group all the misc together: sum by (new_group) ( label_replace( label_replace(my_metric, “new_group”, “$1”, “group”, “.+”), “new_group”, “misc”, “group”, “misc group.+” ) ) The inner label_replace copies all values from group into new_group, the outer overwrites those which match “misc group.+” with “misc”, and we then sum by … Read more
I have the same question before. Here is my solution: use job_name as the group label add more target option to separate instance and add labels For you the code may like this: – job_name: ‘development’ static_configs: – targets: [ ‘192.168.1.1:9100’ ] labels: service: ‘1’ – targets: [ ‘192.168.1.1:9101’ ] labels: service: ‘2’
count(count by (a) (hello_info)) First you want an aggregator with a result per value of a, and then you can count them.
My answer tries to elaborate on Carl’s answer. I assume that the GUI layout may have changed a little since 2016, so it took me while to find the “name” option. Assuming you have a metric as follows: # HELP db2_prometheus_adapter_info Information on the state of the DB2-Prometheus-Adapter # TYPE db2_prometheus_adapter_info gauge db2_prometheus_adapter_info{app_state=”UP”) 1.0 and … Read more
Use the default data dir, which is /prometheus. To do that, use this line instead of what you have in your command: … –volume a-new-volume:/prometheus \ … Found here: https://github.com/prometheus/prometheus/blob/master/Dockerfile Surprisingly is not mentioned in the image docs
InfluxDB CEO and developer here. The next version of InfluxDB (0.9.5) will have our new storage engine. With that engine we’ll be able to efficiently store either single event data or regularly sampled series. i.e. Irregular and regular time series. InfluxDB supports int64, float64, bool, and string data types using different compression schemes for each … Read more
In an ideal world (where your samples’ timestamps are exactly on the second and your rule evaluation happens exactly on the second) rate(counter[1s]) would return exactly your ICH value and rate(counter[5s]) would return the average of that ICH and the previous 4. Except the ICH at second 1 is 0, not 1, because no one … Read more
What you need is the increase() function, that will calculate the difference between the counter values at the start and at the end of the specified time interval. It also correctly handles counter resets during that time period (if any). increase(http_requests_total[24h]) If you have multiple counters http_requests_total (e.g. from multiple instances) and you need to … Read more