Apple's 200-engineer ML team replaced Airflow with Kestra to orchestrate large-scale ETL workloads with declarative syntax and robust fault tolerance.
Industry
Technology
Headquarter
Cupertino, USA
Solution
Apple is a global technology leader whose services, including the App Store, Apple Music, and device ecosystems, generate some of the world's largest data volumes, processed daily by a 200-engineer ML team.
Data Stack
Kestra
Commands
Upload
Query
Parallel
Senior Engineering Manager
Apple ML Team
What would change if your ML data pipelines processed at massive scale, orchestrating complex ETL workloads between your data warehouse and ML platform with declarative simplicity?
