This function has to be enabled via the feature flag --enable-feature=promql-experimental-functions. double_exponential_smoothing(v range-vector, sf scalar, tf scalar) produces a smoothed value for each float time series in the range in v. The lower the smoothing factor sf, the more importance is given to old data. The higher the trend factor tf, the more trends in the data is considered. Both sf and tf must be between 0 and 1. For additional details, refer to NIST Engineering Statistics Handbook . In Prometheus V2 this function was called holt_winters.

February 28, 2025 - Dig into your Prometheus metrics with functions that help you filter, analyze, and spot trends—so you can make sense of your data faster.

April 25, 2025 - Instead, it uses a built-in function called default_rollup(). This function is optimized for data with irregular sample intervals and adjusts the rollup window automatically based on the data or step size. ... The engine pulls all time series named http_requests_total within the given time range from the metrics storage · Converts the instant vector http_requests_total to last_over_time(http_requests_total[lookback]) (in Prometheus) or default_rollup(http_requests_total[lookback]) (in VictoriaMetrics)

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.

July 2, 2021 - The naming makes the purpose of these functions quite obvious. For instance, avg_over_time() is what you may use to compute a moving average of some metric. Similarly, stddev_over_time() can be used to produce a moving standard deviation. However, there is always a caveat. Prometheus supports different logical types of metrics - gauges, counters, histograms, and summaries.

July 9, 2026 - Use the histogram_fraction() function to calculate the percentage of requests with responses in 200 ms or less: histogram_fraction(0, 0.2, sum(rate(http_request_duration_seconds[5m]))) If you’re querying a histogram with a metric name ending in _bucket, you’re querying a classic Prometheus histogram.

March 12, 2026 - Learn how to use Prometheus's rate() function. See two example use cases for rate() used for alerting and for SLO calculation.

The Prometheus monitoring system and time series database. - prometheus/promql/functions.go at main · prometheus/prometheus

The Prometheus monitoring system and time series database. - prometheus/promql/parser/functions.go at main · prometheus/prometheus

up{job="prometheus"} or up{job="node"} Open in PromLens · Include any label sets that are present both on the left and right side: node_network_mtu_bytes and (node_network_address_assign_type == 0) Open in PromLens · Include any label sets from the left side that are not present in the right side: node_network_mtu_bytes unless (node_network_address_assign_type == 1) Open in PromLens ·

August 10, 2023 - A Prometheus query using the PromQL query language can return either an instant vector or a range vector, depending on the metric type and the result you are asking for. Now that we’ve got all that out of the way, let’s return to the original question: what are Prometheus functions?

October 9, 2024 - Functions, such as abs to take the absolute value or rate to compute the rate of increase per second. Aggregations, like sum and max, with optional dimensions, e.g., sum by (status).

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September 26, 2021 - The deriv function estimates the slope of each time series in a range vector and calculates the per-second derivative of the time series in a range vector. deriv should only be used with gauges. The following expression calculate how far resident memory is changing per second based on samples from the past hour for the job prometheus.

2 weeks ago - This page describes how to enable IAP directly on a Cloud Run service and secure traffic bound for a Cloud Run service by routing to IAP for authentication. By enabling IAP on Cloud Run directly, you can secure traffic with a single click from all ingress paths, including default run.app URLs ...

March 15, 2020 - You can use Prometheus to collect data and categorize issues. You use this data to configure a system for prioritizing ops and security tasks. In this article, you will learn about the main advantages of using Prometheus for Kubernetes monitoring, ...

March 21, 2023 - For example, you can use the rate function to calculate the rate of increase of a counter over a time range, or the increase function to calculate the total increase of a counter over a time range. You can also use PromQL expressions to calculate rates of change or derivatives of counter data, which can be useful for monitoring trends and identifying anomalies. In summary, counters in Prometheus are used to represent monotonically increasing values that track cumulative events or occurrences over time.

June 3, 2025 - Using these tricks will allow you to use Prometheus with the throttle wide open. Aggregation is a great way to construct powerful PromQL queries. 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.