Build a product catalog pipeline that pushes feed updates to a search index via an event-driven architecture

Verified steps

1. Set up a change-data-capture (CDC) stream from your source-of-truth (e.g., PostgreSQL via Debezium, or a PIM system via webhook) that emits product create/update/delete events to a queue (e.g., Amazon SQS or Kafka topic).
2. Write a consumer service that reads events from the queue and translates product payloads into the OpenSearch document schema; handle field normalisation (e.g., lowercase brand names, flatten nested variant attributes).
3. For creates and updates, use the OpenSearch bulk API (POST /_bulk) with index action entries; for deletes use the delete action. Batch events into groups of 500–1000 per bulk request for throughput, and implement exponential backoff on 429 or 5xx responses.
4. Manage index schema changes via index aliases: when a schema migration is required, create a new index, backfill it, and atomically swap the alias (POST /_aliases with add and remove actions) so zero-downtime schema changes do not affect live search.
5. Monitor indexing lag and error rates; set up a dead-letter queue for events that fail after retries, and alert on queue depth growth so catalog drift is detected before it affects customer-facing search quality.