Keeping publishing recommendations current
Data Engineering → AI Engineering · Production experience
A publishing data platform had to process older content in backfills and keep up with new content through incremental updates. Each path could fail independently.
My contribution
After a database administrator identified locks that delayed recommendation processing, I updated the affected jobs to close database connections consistently. I also helped validate backfills and incremental updates in Airflow and recorded the results.
What it enabled
Closing connections consistently addressed one source of delays in preparing recommendations. Checking both paths gave the engineering team a way to see how the workflows handled existing and newly arriving content.
Why the scale mattered
The recommendation workflows were configured for 37 production publishing sites. A failure in a shared processing path could leave recommendations stale across multiple sites, so the team needed evidence from both paths.
A separate ingestion incident
I corrected a publisher’s webhook configuration and monitored the feed. Follow-up monitoring showed the webhooks were healthy again.
Incident details come from project records. Read the published background.