[docs-patrol] Document AWS VPC Flow unsupported-format pipeline_error behavior

Recent code changes in the repository have introduced documentation drift. The following change needs a corresponding documentation update.

## Changes Requiring Documentation Updates

### 1. AWS VPC Flow now emits pipeline errors for unsupported plain-text formats

**Commit(s):**
- [`ddd75707f42fb6fbea02af51f4fec692f842b5a7`](https://github.com/elastic/integrations/commit/ddd75707f42fb6fbea02af51f4fec692f842b5a7)

**What changed:**
- The VPC Flow ingest pipeline added a `fail` processor for records whose token count does not match supported layouts and where parsing did not populate `aws.vpcflow.srcaddr`.
- This changed behavior from silently indexing unsupported formats unparsed to surfacing them as pipeline errors.

**Evidence:**
- `packages/aws/data_stream/vpcflow/elasticsearch/ingest_pipeline/default.yml:72-77` adds:
- `fail` on `ctx?._temp_?.message_token_count != null && ctx?.aws?.vpcflow?.srcaddr == null`
- message: `Unsupported VPC Flow Log format... Use a custom ingest pipeline to parse this format.`
- `packages/aws/changelog.yml:12-16` documents this as version `6.16.0` behavior change.

**Documentation impact:**
- `packages/aws/docs/vpcflow.md` documents supported formats (`:51-62`) and states only that Parquet is unsupported (`:86`), but does not explain the new unsupported plain-text failure behavior.
- Users now need explicit guidance that unsupported plain-text formats generate `pipeline_error` events and that custom ingest pipelines are required for those layouts.

## Suggested Actions

- [ ] Update `packages/aws/docs/vpcflow.md` to document that unsupported plain-text VPC Flow layouts now trigger pipeline errors instead of being silently indexed.
- [ ] Add a short troubleshooting note describing expected error behavior and recommending custom ingest pipelines for unsupported formats.
- [ ] If applicable, add an example of an unsupported custom layout symptom (`pipeline_error` with unsupported format message) so users can recognize this condition quickly.

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