Скачать или смотреть How to Use label_value() in Your Prometheus Queries Effectively

Discover how to get label values from one metric to use in another with Prometheus. Learn about the `label_replace()` function and best practices to streamline your queries.
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Getting label_value() with Prometheus Queries: A Step-by-Step Guide

When working with Prometheus, one common challenge developers face is retrieving label values from one metric to use in another query. This situation often arises when you have multiple metrics that share a common context, such as a service or environment, and you want to leverage these shared properties in your queries. In this guide, we'll explore how to achieve this using functions like label_replace() and the group_left operator.

The Problem: Extracting Label Values

Let's begin with a scenario where you have two metrics:

Metric 1: You want to extract label values from this metric.

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Metric 2: You need to use the host label values from the first metric.

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The challenge is to pass the host values from Metric 1 into Metric 2. While you might assume that you can use label_values(), this function is typically reserved for use in Grafana panel variables and doesn't work directly within Prometheus query syntax itself.

The Solution: Using label_replace() and group_left

Step 1: Aligning Labels

Since the labels between Metric 1 and Metric 2 do not match initially, we need to address this using the label_replace function. This function allows us to rename or modify label values easily. Here's the expression we'll use:

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This line effectively copies the domain label values from metric_2 to a new label, host. After applying this transformation, both metrics will share a common label, host, allowing us to combine them in a query.

Step 2: Constructing the Query

Next, we want to perform the join between the transformed Metric 2 and Metric 1. The proper query for this operation looks like this:

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Step 3: Handling the Issues of Multiplicities

While the previous query does work, it might not yield the expected results because it can produce an excessive multiplication of values. This occurs if the metrics are misaligned during the operation. To prevent this, we can nullify the contribution of Metric 1 by multiplying it by zero like so:

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This query structure allows us to isolate and only return values from Metric 2, without interference from Metric 1.

Final Note on Performance

It's crucial to note that while this query structure works, it might not be the most optimized version. There are still potential improvements to be made. For example, omitting any labels inside group_left() that aren't necessary for your analysis can keep things even simpler, such as:

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

Wrap-up

Understanding how to navigate between metrics in Prometheus is an essential skill for developers looking to harness the full capabilities of the platform. By utilizing the label_replace() function and combining metrics appropriately, you can manipulate and query your data more effectively.

If you have any questions or need assistance with query optimization, feel free to reach out. Happy querying!