# Enrichment, Filtering and Redaction — OpenTelemetry

Source: https://www.skillbyai.com/en/opentelemetry/s-process

> Clean data before export.

## Processors for quality and privacy

Useful processors include **k8sattributes** (adds pod, namespace and deployment names), **resourcedetection** (cloud and host metadata), **attributes** and **transform** (rename, hash or delete attributes using OTTL, the OpenTelemetry Transformation Language), **filter** (drop health-check spans or noisy metrics) and **redaction** (remove values matching sensitive patterns). Doing this centrally ensures personal data and secrets never reach third-party backends.

## Dropping health checks and removing sensitive attributes

Filter and attributes processors (contrib distribution).

```yaml
processors:
  filter/health:
    error_mode: ignore
    traces:
      span:
        - 'attributes["url.path"] == "/healthz"'
  attributes/scrub:
    actions:
      - key: user.email
        action: delete
      - key: enduser.id
        action: hash

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [memory_limiter, filter/health, attributes/scrub, batch]
      exporters: [otlp/tempo]
```

## Do not rely on redaction alone

Avoid recording sensitive data in the first place; Collector redaction is a safety net.

**Quiz:** Which processor adds Kubernetes pod and namespace names to telemetry?

- [x] k8sattributes
- [ ] batch
- [ ] debug
- [ ] memory_limiter

*Answer:* k8sattributes. Enrichment from the Kubernetes API.