How Can I Use Multiple Values in Source_Labels with Prometheus?
In the world of modern monitoring and alerting, Prometheus stands out as a powerful and flexible tool that empowers engineers to gain deep insights into their systems. One of its strengths lies in its ability to finely tune how metrics are scraped and labeled, enabling precise querying and alerting. Among the many configuration nuances, handling multiple values within `source_labels` is a topic that often sparks curiosity and presents unique challenges for users aiming to optimize their metric collection.
Understanding how to work with multiple values in `source_labels` can unlock new levels of control over metric relabeling and transformation. This concept plays a crucial role in scenarios where metrics need to be combined, filtered, or modified based on several label sources simultaneously. While the idea might seem straightforward at first glance, the underlying mechanics and best practices require careful consideration to avoid common pitfalls and ensure efficient configuration.
As you delve deeper into this topic, you will discover how Prometheus processes multiple labels within `source_labels`, the impact on relabeling rules, and practical strategies to leverage this feature effectively. Whether you’re refining your monitoring setup or troubleshooting complex label manipulations, mastering multiple values in `source_labels` is an essential step toward harnessing the full potential of Prometheus.
Using Multiple Values in source_labels for Relabeling
In Prometheus configuration, the `source_labels` field is a crucial component in the `relabel_configs` section, allowing one to specify which label values will be used as inputs for relabeling. When you want to combine or match multiple label values, `source_labels` accepts a list of labels rather than a single label. This flexibility enables complex transformations and extractions from metrics metadata.
When multiple labels are specified in `source_labels`, Prometheus concatenates their values into a single string, using the `separator` option to delimit them. By default, this separator is `;`. This concatenated string is then processed by the chosen relabeling action, such as `replace`, `keep`, `drop`, or `labelmap`.
Key points about using multiple values in `source_labels`:
- Order matters: The labels are concatenated in the order they are listed.
- Separator customization: The default separator can be overridden using the `separator` field.
- Regex matching: The resulting concatenated string can be matched against a regex pattern to extract or manipulate parts of the combined labels.
- Flexible relabel actions: Actions like `replace` or `hashmod` can then operate on the concatenated string to create or modify target labels.
For example, if you want to create a new label that combines the values of `job` and `instance`, you might configure:
“`yaml
- source_labels: [job, instance]
separator: “;”
regex: “(.*);(.*)”
target_label: combined
replacement: “$1-$2”
action: replace
“`
This configuration concatenates the values of `job` and `instance` with a semicolon, matches them with the regex, and replaces the `combined` label with the two values joined by a hyphen.
| Field | Description | Default Value | Example Usage |
|---|---|---|---|
| source_labels | List of labels whose values are concatenated for relabeling | None (required field) | [job, instance] |
| separator | String used to join multiple label values | “;” (semicolon) | “-” or “|” |
| regex | Regular expression to match concatenated string | “.*” (matches everything) | “(.*);(.*)” to split two labels |
| target_label | Label to assign the relabel result | None (required for certain actions) | combined |
| replacement | String used to replace matched regex groups | $1 (first regex group) | “$1-$2” to join two groups with a hyphen |
| action | Relabeling action (replace, keep, drop, etc.) | replace | replace |
Common Use Cases for Multiple source_labels
Using multiple values in `source_labels` is useful in a variety of scenarios where metric labels need to be manipulated or combined before further processing or storage. Some common use cases include:
- Combining labels for unified identification: For example, combining `job` and `instance` labels to create a unique identifier for metrics aggregation or alerting rules.
- Extracting parts of multiple labels: Using regex on concatenated label values to extract subcomponents and assign them to new labels.
- Conditional filtering: Matching combined label values to selectively keep or drop metrics based on complex label combinations.
- Hash-based sharding or routing: Applying hashing on concatenated label values to distribute metrics evenly across backends or shards.
- Label normalization: Standardizing label values by combining and transforming multiple source labels into a consistent format.
Best Practices and Limitations
When working with multiple `source_labels`, consider the following best practices to ensure reliable and maintainable Prometheus configurations:
- Explicit separators: Always specify a `separator` if the default semicolon might conflict with label values or regex patterns.
- Clear regex patterns: Use precise regex expressions that match the exact structure of concatenated labels to avoid unexpected matches.
- Minimize complexity: Avoid overly complex concatenations or regex captures that can reduce readability and increase debugging difficulty.
- Document configurations: Annotate relabel rules with comments explaining the purpose of combining multiple labels and the intended transformations.
- Test changes: Use Prometheus’s `promtool` or a dry-run environment to validate relabel configurations before deploying to production.
Limitations to be aware of:
- The concatenation and regex matching happen on strings, so label value encoding or special characters may cause mismatches.
- There is no built-in way to combine labels with conditional logic beyond regex matching; complex logic may require external metric processing.
- Using too many concatenated labels or very large label values can impact relabeling performance.
By carefully leveraging multiple values in `source_labels`, Prometheus users can create flexible and powerful relabeling pipelines that adapt metrics to their monitoring and alerting requirements effectively.
Using Multiple Values in source_labels for Prometheus Relabeling
Prometheus relabeling configuration allows for dynamic modification of label sets during service discovery or before ingestion. The `source_labels` field plays a crucial role by specifying which existing labels to extract values from. Incorporating multiple values in `source_labels` is a common requirement when you want to combine or conditionally manipulate labels based on several inputs.
Fundamentals of Multiple Values in source_labels
- `source_labels` accepts a list of label names.
- The values corresponding to these labels are concatenated with a separator (default is `;`).
- This concatenated string serves as the input for the `regex` and `replacement` fields in the relabeling rule.
- Effective use of multiple `source_labels` facilitates complex transformations, such as combining hostnames and ports, extracting substrings, or conditional relabeling based on multiple criteria.
Syntax and Example Configuration
“`yaml
relabel_configs:
- source_labels: [__meta_kubernetes_pod_name, __meta_kubernetes_pod_container_port_number]
separator: “:”
regex: (.+)
replacement: $1
target_label: combined_label
“`
- source_labels: Lists multiple labels whose values are concatenated.
- separator: Defines how values are joined (colon `:` in this case).
- regex: Matches the combined string.
- replacement: Uses capture groups to generate the new label value.
- target_label: The label to be set or modified.
In this example, the pod name and container port number are combined into a single label `combined_label` with a colon separator, such as `my-pod:8080`.
Advanced Techniques with Multiple source_labels
| Technique | Description | Example Use Case |
|---|---|---|
| Conditional Matching | Use regex to selectively process label combinations based on patterns. | Only relabel pods with specific ports or names. |
| Label Value Extraction | Extract substrings or specific components from concatenated labels using regex capture groups. | Extract version numbers from combined app and tag. |
| Multi-step Relabeling | Chain multiple relabel_configs to progressively transform and refine labels. | First combine labels, then extract and set new labels. |
| Dynamic Target Labeling | Use replacement values derived from concatenated source_labels to set dynamic target labels. | Construct dynamic `instance` labels for metrics. |
Practical Examples Demonstrating Multiple source_labels
- Combining Hostname and Port
“`yaml
relabel_configs:
- source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_port]
separator: “:”
regex: (.+)
replacement: $1
target_label: __address__
“`
This rule appends a port from a pod annotation to the address label, overriding the default scrape target.
- Filtering Based on Multiple Labels
“`yaml
relabel_configs:
- source_labels: [job, env]
regex: (api-server);(prod)
action: keep
“`
Only keeps targets where `job` equals `api-server` and `env` equals `prod`.
- Extracting Version from Combined Labels
“`yaml
relabel_configs:
- source_labels: [app, version]
separator: “-”
regex: .+-v(\d+\.\d+\.\d+)
target_label: app_version
replacement: $1
“`
Combines `app` and `version` labels separated by a hyphen, then extracts semantic versioning into a new label.
Best Practices When Using Multiple Values in source_labels
- Always specify the `separator` explicitly to avoid ambiguity, especially if label values may contain default separators.
- Test regex patterns thoroughly with sample label combinations to ensure correct matching and capturing.
- Use descriptive target label names to maintain clarity in metrics and queries.
- Be cautious with chaining complex relabel_configs to avoid unintended label overwrites or drops.
- Leverage the `action` field (`replace`, `keep`, `drop`, `labelmap`, etc.) strategically to control the relabeling flow.
Common Pitfalls and Troubleshooting
| Issue | Cause | Resolution |
|---|---|---|
| Unexpected label concatenation | Missing or incorrect `separator` in source_labels | Define an explicit `separator` to control concatenation. |
| Regex not matching | Incorrect pattern for combined label string | Test regex using concatenated label values beforehand. |
| Labels not appearing in output | Relabeling action set to `drop` or `keep` filters | Verify `action` and ensure conditions match expected values. |
| Replacement group errors | Incorrect usage of capture groups in `replacement` | Check regex groups and reference them correctly ($1, $2). |
Conclusion on Using Multiple Values in source_labels
Utilizing multiple values in `source_labels` unlocks powerful label transformation capabilities in Prometheus relabeling. By carefully combining label values, applying precise regex patterns, and controlling the relabeling actions, users can tailor their metric labels to fit complex infrastructure and monitoring requirements. Mastery of these techniques enhances the flexibility and accuracy of Prometheus scraping and metric labeling strategies.