Cloud-Native Genomics Data Pipeline
Built a production microservice pipeline for New Zealand's largest cattle genetics company. The system ingests high-throughput genomic data, processes it through a multi-stage validation and enrichment pipeline, and delivers results to downstream analytics platforms. Designed for fault tolerance and horizontal scalability on AWS, with comprehensive observability through structured logging, distributed tracing, and real-time alerting.
The Challenge
New Zealand's largest cattle genetics company needed to process high-throughput genomic data at a scale their existing systems couldn't sustain. Genomic sequencing runs generate large, irregular bursts of data that must be validated, enriched, and delivered to downstream analytics platforms without dropping records or introducing silent errors, all while remaining resilient to node failures during long-running processing jobs.
The Solution
Built a production microservice pipeline on AWS, designed for fault tolerance and horizontal scalability from day one.
- Ingestion: Handles high-throughput genomic data arriving in irregular bursts, with backpressure and retry handling built into every stage.
- Validation & enrichment: A multi-stage pipeline validates incoming records against domain rules and enriches them with reference data before they reach analytics consumers.
- Fault tolerance: Services are designed to fail gracefully and resume from checkpoints, so a single node failure never means reprocessing an entire batch.
- Observability: Structured logging, distributed tracing, and real-time alerting give the team full visibility into pipeline health and data quality at every stage.
The Outcome
The client now runs genomic data through a pipeline that scales horizontally with sequencing volume rather than against it, with full traceability from raw ingestion through to the analytics platforms their scientists and breeders rely on every day.