How dbt Labs reduced dbt-related compute costs by 64% with Fusion and state-aware orchestration

dbt Labs achieved a 64% reduction in compute costs by transitioning to its Fusion engine and implementing State-Aware Orchestration (SAO), which intelligently determines when data transformations are necessary, thus avoiding unnecessary compute use. Initially, the migration to Fusion was focused on enabling intelligent orchestration, despite challenges such as parse issues and package dependencies. Once Fusion was stable, activating SAO resulted in immediate savings by preventing redundant data processing. Further optimization entailed simplifying job architecture from ten complex jobs to three main workflows, based on data freshness needs, which streamlined operations and aligned them with business requirements rather than technical constraints. Despite some challenges, such as managing new model builds and ensuring data freshness, the transition demonstrated the benefits of aligning technical implementations with business needs, resulting in significant cost savings and simplified operations.

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