See detailed status and progress output for all auto-processing modes.
Two views cover most observability needs:
aidb.pipeline_metrics(aliasaidb.pipem) — one row per pipeline with backlog, source/destination counts, status, and error counts. This is the primary view for tracking processing progress.aidb.knowledge_base_metrics(aliasaidb.kbm) — one row per knowledge base with pipeline count, embedding count, and aggregated status across all attached pipelines.
Per-pipeline progress
SELECT * FROM aidb.pipem;
Output
pipeline | auto processing | table: unprocessed rows | volume: scans completed | count(source records) | count(destination records) | Status | count(record errors) | count(blocking errors) ---------------------+-----------------+-------------------------+-------------------------+-----------------------+----------------------------+----------+----------------------+------------------------ feedback_na_pipe | Live | 0 | | 412 | 412 | UpToDate | 0 | 0 product_docs_pipe | Background | | 6 | 1842 | 1842 | UpToDate | 0 | 0 (2 rows)
The change detection mechanism is different for volume and table sources, so the view exposes these metrics:
table: unprocessed rows: How many unique rows are listed in the backlog of change events. Auto-processing captures no new change events whenDisabled.volume: scans completed: How many full listings of the source have been completed.count(source records): How many records exist in the source. Accurate for table sources at all times; updated after each full scan for volume sources.count(destination records): How many rows the pipeline has written to its destination (embeddings, chunks, and so on).
Knowledge base overview
SELECT * FROM aidb.kbm;
Output
name | pipelines | embeddings | status ------------------------------+-----------+------------+---------- public.product_catalog_kb | 1 | 1842 | UpToDate public.customer_feedback_kb | 2 | 915 | UpToDate (2 rows)
The status column rolls up the worst pipeline status across all pipelines attached to that KB — drill into aidb.pipeline_metrics to find which pipeline is responsible.