Case Study: BearingPoint achieves scalable multi-cloud ML with Astronomer Astro

BearingPoint cuts pipeline incidents 90% with Astronomer

BearingPoint, a leading global consultancy, faced significant challenges scaling its multi-cloud ML operations. Their custom Python orchestration framework was fragile, causing frequent pipeline incidents and high operational overhead for their lean engineering team. They needed a reliable, cloud-agnostic solution to power their mission-critical data products for enterprise customers.

By implementing Astronomer's Astro platform, BearingPoint standardized on Apache Airflow for orchestration. Astronomer provided a consistent operational model across AWS and Azure, enabling reliable pipelines for credit scoring and retail forecasting applications. The results were transformative: a 90% reduction in incidents, 95% faster MTTR, and 6% engineering time savings, all achieved without adding infrastructure management overhead.

BearingPoint