Скачать или смотреть How to Detect Metrics Loss in Prometheus with One Query

Learn how to create a single alert in Prometheus to detect if any device goes offline, using an elegant one-query solution.
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How to Detect Metrics Loss in Prometheus with One Query: A Comprehensive Guide

As more devices become integrated into our monitoring systems, keeping track of their status in real-time is essential. One recurring challenge for system administrators is detecting when a device goes offline. If you have numerous devices—each emitting metrics—you might wonder if there’s an efficient way to set up alerts for when any device stops emitting metrics without the cumbersome task of creating individual alerts for each device.

This guide delves into a solution using Prometheus for effectively detecting when a device goes offline using just one query.

Understanding the Challenge

When you want to monitor a group of devices, you typically want a single alert to notify you of any device going offline. Creating an alert for each device can be overwhelming and could lead to alert fatigue. Hence, finding a way to aggregate this data into a single alert mechanism becomes imperative.

The Approach: Using Prometheus Queries

In Prometheus, you work with metrics that are actively reported. If a device stops emitting metrics, that absence can be challenging to capture directly. However, Prometheus offers a clever workaround using timeshift queries. Let’s explore how you can leverage a single query to detect if a particular metric stops being actively emitted.

The Solution

Prometheus Query Syntax

You can use the following query to monitor your metrics:

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Query

someMetric{}: This represents the metric you are interested in monitoring.

unless: This operator allows you to perform an operation only if certain conditions are met.

(someMetric{} - 100000) offset 3m: This part is used to compare the most recent data against the data from three minutes ago. The subtraction by an arbitrary value (in this case, 100000) helps create a distinguishing factor.

What Does This Do?

Monitoring Presence: The expression inside the parentheses will only return a value if one of the conditions returns true. It helps identify when:

The metric first appears.

The metric disappears (offsetted metric is present).

Interpreting Results:

If you get values within the normal range, it indicates that the metric is present.

A significantly smaller value indicates the metric has disappeared.

How to Set Up an Alert

To create an alert based on this expression, simply configure it to trigger when the query returns a value below a certain threshold (e.g., adjust the threshold as required for your specific use case).

Consideration on Alert Duration

Be mindful that the alert will only last as long as specified by the offset. In the example above, it will only trigger for 3 minutes after the metric stops being emitted. If you want to catch events over a longer period, consider increasing the offset to something like 1 hour:

Longer Offset: Alerts can remain active for an extended duration, but keep in mind that this may delay your awareness of an offline device.

Visualizing Scenarios

To better understand how this works, consider two cases:

Case 1: The metric was present longer than the offset.

[[See Video to Reveal this Text or Code Snippet]]

Case 2: The metric is present for only a short time.

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Detecting if a metric stops being emitted across devices can be efficiently managed using a clever Prometheus query. By employing a combined approach with unless and time offsets, you can set up a single alerting mechanism to easily track the status of your devices. Just ensure you adapt the threshold and offset to your monitoring needs for optimal perfo