For example, sum(rate(metric[5m])) by (service) is far cheaper than querying all individual Pod-level series. Use recording rules for repeated queries: If a dashboard panel queries the same expensive expression on every load, create a Prometheus ...

December 16, 2024 - The examples use Grafana as a frontend for Prometheus, but these queries are universal and should work with any Prometheus-compatible frontend.

Return a whole range of time (in this case 5 minutes up to the query time) for the same vector, making it a range vector:

October 9, 2024 - An example query is sum by (status) (rate(http_requests_total[5m]) > 0). This takes the 5-minute rate of HTTP requests, filters to those that had some requests, then sums by status.

The Prometheus data source is preinstalled in Grafana, so you don’t need to install it manually. Write queries using PromQL in the query editor, or use Metrics Drilldown to explore metrics without writing queries.

August 10, 2024 - Note: Using $__interval in your Grafana queries is often sufficient for many types of queries, particularly when you want your data to automatically adjust to the dashboard's time range and resolution. ... These are the queries and functions I use often and I thought it could be of a great help for beginners. Credits to https://promlabs.com/promql-cheat-sheet/ which helped me a lot during my initial days with Promql. Mastering Prometheus queries and effectively using Grafana’s templated variables can significantly enhance your monitoring capabilities.

February 5, 2020 - Examples of scalars include 0, 18.12, and 1000000. All calculations in Prometheus are floating point operations. When you group together scalars as a set of metrics in a single point in time, you get the instant vector data type. When you run a query asking for only the name of a metric, such as bicycle_distance_meters_total, the response is an instant vector.

June 27, 2026 - Query gauges directly — no rate() needed. A histogram records observations in buckets. Examples: request duration, response size. Use histogram_quantile() to calculate percentiles like p50, p95, and p99.

Reference a template variable to make a query interactive. For example, filter by a selected instance value:

For example, sum(rate(metric[5m])) by (service) is far cheaper than querying all individual Pod-level series. Use recording rules for repeated queries: If a dashboard panel queries the same expensive expression on every load, create a Prometheus ...

May 19, 2025 - It forms the backbone of Prometheus's monitoring capabilities, enabling both visualization and alerting based on collected metrics. ... A typical PromQL query consists of several components that can be combined to create powerful expressions: ... This query returns a value of 1 (up) or 0 (down) for each monitored target, providing a quick check of which services are running.

January 28, 2022 - This video walks you through how to use the metrics browser to discover all the available metrics in Prometheus and build a query with the specific metrics you want and the labels you want to filter on. To learn more about the metrics browser and other features available in the Prometheus data source for Grafana, check out our documentation.

Learn about querying metrics in Amazon Managed Service for Prometheus using a query language, or tools such as Amazon Managed Grafana.

The following shows an example data source configuration: Follow the standard way of adding a new Grafana graph. Then: Click the graph title, then click "Edit". Under the "Metrics" tab, select your Prometheus data source (bottom right). Enter any Prometheus expression into the "Query" field, while using the "Metric" field to lookup metrics via autocompletion.

Viewers can add filters by selecting a label, operator (=, !=, =~, !~), and value. Grafana automatically applies these filters to all Prometheus queries on the dashboard. Example: A viewer adds the filter namespace = production.

June 27, 2022 - In this article, we’ll take a closer look at the Prometheus Grafana solution, and how it works, and walk through real-world examples to help you gain hands-on experience with these powerful DevOps tools. Let’s begin with a look at the high-level features of Prometheus and Grafana. Key features that make Prometheus such an effective monitoring and alerting solution are: ... Prometheus’s native query language, PromQL, is a key component of working with Prometheus.

July 19, 2022 - At first, this started as a project to build a visual editor for Prometheus, but it became pretty clear that this pattern of selector + operations is applicable for more data sources. Grafana Loki was an obvious example here because LogQL, the query language in Loki, started with the design goal of being as close to PromQL as possible.

August 1, 2025 - There’s a lot going on in there. For now, copy the SystemCPULoad query that we pulled from Prometheus earlier into the query line: Upon clicking off of the query, you’ll see that Grafana immediately executes the query and starts rendering graph data:

Intervals are typically used in aggregation functions like sum or average. For example, this is a Prometheus query that uses the interval variable: rate(http_requests_total[$__interval]).

Press the graph, we get an error saying that expression type "range vector" for range query, must be Scalar or instant Vector