Build Federal Register Compliance Alerts

A production feed needs more than a scheduled scrape. The Federal Register Scraper handles collection from the official Federal Register documents API; the rest of the pipeline should make ownership and state explicit.

Recommended data flow

Saved Apify Task -> raw dataset -> keyed upsert -> qualification -> owner queue -> alert

Use document_number for idempotency and retain docket_ids for downstream joins. Send proposed rules to a comment-deadline queue, final rules to compliance owners, and notices to topic-specific watchers.

Keep raw and derived data separate. The raw table should mirror source fields and collection metadata. The derived table can add scores, owners, workflow status, and internal notes. When a scoring rule changes, rebuild the derived table rather than editing source history.

Failure handling

Promote a snapshot only when the Actor run succeeds and passes basic checks: nonzero rows when rows are expected, valid keys, parseable dates, and no unexpected schema loss. Retry network failures with a bounded policy. Do not create downstream deletion events from a failed collection.

A search result is not a legal conclusion. Proposed rules, final rules, and notices have different effects. Preserve document type and official links so counsel or policy owners can review the actual publication.

Track three operational metrics: successful run rate, time from source publication to owner delivery, and the percentage of alerts that owners accept. Those numbers expose different failures. Availability problems hurt the first, an infrequent schedule hurts the second, and weak qualification hurts the third.

Start with one destination and one owner group. Add CRM, warehouse, or webhook branches after the keyed dataset and alert rules have stayed stable through several runs.