- etl_offload.py: autonomous agent backfills/tails source DBs (PG/MySQL/
Mongo/Cassandra) to S3 as Parquet in small chunks, accumulates a live
federated business matrix (/api/etl/status, /api/etl/business, /run, /config).
- storage_s3.py: buffer generated CDC + masked curated rows to S3, overlay
live last-write into analytics; put_object_bytes for Parquet parts.
- trino_federated.py: capture generated rows + archive to S3; generator_active.
- dataflow.py: pulse generate + kafka/spark->S3 archive edges when active.
- StorageView: realtime ETL ingest panel; TrinoFederationView: realtime
business KPIs/charts from /api/etl/business.
- ChangesView: top KPIs/charts now overlay the live WS stream on server stats
so they update in lock-step with the bottom feed; faster 2.5s refresh.
- useCommandCenter: retain 800 live CDC changes.
Generated data is now visible flowing into the source systems on the Data
Flow graph: a manual "Generate data" burst (and the continuous live loop)
stamps a last_tick, and a new generator_active() helper lights up the
generator -> postgres/mysql/mongodb/cassandra edges for ~12s. Neo4j stays
dark since the live generator does not write to it.
Redesigned the Changes tab into a "New & Changed Data" dashboard driven by
the live CDC stream: animated KPI cards (new/updated/deleted + throughput),
a change-volume area chart, an operation-mix donut, per-system and
top-table breakdown bars, plus the existing filterable change feed.
mo