{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/0aa2652adedb4315ab12c244be16f515\" frameborder=\"0\" width=\"1662\" height=\"1246\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1246,"width":1662,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1246,"thumbnail_width":1662,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/0aa2652adedb4315ab12c244be16f515-d2c0650fd86157a0.gif","duration":604.032,"title":"Hyperliquid Trade Settlement Pipeline Overview","description":"This Loom presents the architecture for a Hyperliquid settlement pipeline that ingests live trade data, batches it, and submits batches to a mock chain with dead-letter handling for failures. It describes four services: FeedAdapter (WebSocket to Trades), Ingestor (normalize and validate), BatchPublisher (flush by size of 50 trades or time), and Chain submitter (submit batch data). The system uses Kafka via Redpanda, at-least-once delivery with mockchain deduplication via shared objects and batch and readup IDs, plus exponential backoff for WebSocket reconnects. It includes demos showing successful chain submissions, a dead-letter queue test by forcing a chain failure rate of 1, and an end-to-end test verifying processed trade counts match input after duplication checks to avoid data loss."}