Log pipelines: JSON first, processors in order, filters scoped tight
# Log pipelines and parsing rules, in the right order
A pipeline is an ordered list of processors applied to logs matching its filter. Order is the whole game: each processor sees the output of the previous one.
## Build order
1. **Filter first.** Scope the pipeline to `source` / `service` / `env`. A pipeline that matches everything will eventually mangle something it should not touch.
2. **Parse structure before content.** JSON parser first (for JSON logs), then grok for the remaining unstructured bits. Grok on already-parsed JSON is wasted work; JSON parse after grok sees a reshaped message.
3. **Remap the reserved attributes.** `status`, `service`, `host`, timestamp: get these right and severity filtering, trace correlation, and time math all work. Get them wrong and nothing downstream behaves.
4. **Enrich last.** Tag additions, lookups, and sampling decisions go after parsing, so they can key off parsed attributes.
## The JSON-first rule
If you control the app, log JSON. Then the pipeline is a JSON parser plus attribute remaps, and format changes (new fields) do not break parsing. Grok is for logs you do not control (vendor appliances, legacy apps). Every grok rule is maintenance debt: the format will drift and the rule will silently stop matching.
## Test discipline
Every rule gets tested against a real raw line from Live Tail before saving, and re-tested when the app version changes the format. Pipeline changes deploy alongside the app change that alters the format, not the week after.
## Verify
New logs show parsed attributes in the explorer, trace IDs link to traces, and status severity filters behave. Remember old logs are not reprocessed: verify on fresh data only.Find related guidance
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