PromCon EU 2024Talk abstract
The weirdest PromQL you’ll ever see: PromQL for Reporting, Analytics, and Business Intelligence
Speaker(s): Sam Jewell
Prometheus is fantastic at managing high frequency data. But what if you have an analytics use case? Sometimes we just want to lower the frequency; to see daily, weekly or monthly data and find long-term trends or growth rates.
We might want to consider any of these use cases per day, week or month, such as: - Activity: requests or transactions - Usage or consumption, for billing or auditing - Count of events: alerts or incidents, for example.
Why use Prometheus rather than more traditional analytics tools for this? By querying Prometheus directly we can avoid creating/maintaining a data-pipelines, avoid data exports and staleness problems, and lean on the power of the Prometheus ecosystem: For example, we can create overviews for management, plan ahead, and alert on our reports.
Yet querying Prometheus by calendar-month in particular can be surprisingly tricky. PromQL doesn’t support using 1M in subqueries because month-lengths vary.
In this talk I’ll: - Take you on a journey, to understand all the ways that the time dimension can be controlled when querying PromQL with: - The @ operator - Subqueries - The offset keyword - Navigate more PromQL gotchas along the way: - Why do we need rate and labelreplace - How to control the MaxDataPoints when querying from Grafana - Use of Joins and the absent function - Conclude by showing two different ways we can render monthly data FTW: - Render a saw-tooth cumulative counter which resets to zero every month-start - Use `and dayof_month()` in your query to get true monthly data from a counter
After this talk you will be able to query for daily, weekly or monthly data directly from Prometheus. As a result, you’ll be able to spot longer term trends or growth rates. And you’ll be able to compare with data from your other sources, for correlation or auditing purposes.
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