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Workflow Manager
Workflow automation and scheduling system are used to author, schedule, and manage data pipelines. A Workflow manager includes scheduling and triggering jobs, resolving dependencies between steps and workflows, versioning, and monitoring and alerting on failures.
The classic workflow orchestration problem consists of scheduling the movement of data from a production database to a data warehouse. As modern-day data ecosystems have grown more complex, a workflow manager automates the ETL process and the scheduling of dependent API calls.Another factor contributing to an increase in task failures is more data professionals are integrating data: data engineers, data scientists, machine learning engineers, etc. A workflow manager provides a common orchestration framework that data scientists, ML and data engineers, and others can use to acquire and engineer data at every phase of a data science or ML project’s lifecycle, such as triggering a model build via an API call, resulting in infrastructure creation, fine-grained observability into pipeline status.
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Last modified 30d ago