Case Study: Petal scales data orchestration incrementally with Dagster Labs

How Petal Incrementally Adopted a Data Orchestrator

Petal, a FinTech company, faced challenges with its outdated data orchestration system that relied on a complex web of Jenkins and CRON jobs. This setup lacked the dependencies, event-based triggering, and end-to-end visibility of a modern data platform, which was critical for supporting internal teams and external financial partners. To overcome this, the company adopted Dagster's orchestration platform, specifically utilizing Dagster+ Serverless to manage its infrastructure.

By incrementally adopting Dagster, the vendor, Petal was able to integrate its existing pipelines without disruption, weaving in its dbt Core transformations and moving away from Jenkins. The solution provided the event-based triggering and dependency graph the team needed, streamlining their overall data pipeline. Dagster's integration laid a foundation for future capabilities like enhanced data cataloging and collaboration, enabling the small data team to scale its platform efficiently.

Petal

Liem Truong

Engineering Manager