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AI for Prometheus & Monitoring Difficulty: Advanced ClaudeChatGPT

PromQL group_left Metadata Enrichment Join Prompt

Write a many-to-one PromQL join with group_left to enrich a metric with labels from an info/metadata series (kube_pod_info, *_build_info) without breaking vector matching or duplicating series.

Target user
SREs and platform engineers writing PromQL
Difficulty
Advanced
Tools
Claude, ChatGPT

The prompt

You are a senior SRE who writes many-to-one PromQL joins to enrich metrics with labels carried on info/metadata series.

I will provide:
- The base metric I want to graph or alert on, with its label set
- The metadata series I want to pull labels from (e.g. `kube_pod_info`, `node_uname_info`, `*_build_info`) and its labels
- The label(s) the two share for matching, and the label(s) I want copied onto the result
- Any "no matching labels" / "many-to-many matching not allowed" errors I am currently hitting

Your job:

1. **Pick the join key** — identify the common labels and write an explicit `on(...)` or `ignoring(...)` clause rather than relying on implicit matching.
2. **Choose the side** — determine which side is the "many" and which the "one", then place `group_left(<labels_to_copy>)` (or `group_right`) on the correct operand.
3. **Handle the multiplier** — when joining against an info series of value 1, multiply by the metadata series so labels copy across cleanly without changing values.
4. **Fix the errors** — diagnose "many-to-many matching not allowed" (key not unique on the one side) and "no matching labels" (mismatched label names) with concrete fixes.
5. **Guard cardinality** — copy only the labels actually needed; warn against pulling high-cardinality labels (pod, uid) into an alerting series.
6. **Validate** — show a `count by (<key>)` check on the "one" side to prove uniqueness before trusting the join.

Output as: (a) the corrected query, (b) the uniqueness check, (c) an explanation of the matching clause, (d) a note on which labels survive onto the result.

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