Introduction
Today (pre-project) there is no defined structure for organizing transformations, jobs, and associated configuration. This makes it challenging for ETL developers and DevOps to keep pipeline development work organized posing challenges for collaboration and migration across environments. In addition, there are inconsistencies in how configuration references are resolved resulting in behavior that is not easy to understand or explain. For example, it is not clear how conflicting configuration references are resolved and where they are derived from.
Projects aim to address these and other gaps. Specifically, introducing Projects in Pentaho Data Integration enable the following:
Organization: Projects provide a logical container for related data integration tasks, ETL processes, and metadata, enabling better development and deployment workflows with reduced complexity.
Version Management: Projects facilitate tracking changes, maintaining version history, and supporting collaborative development of data integration solutions.
Scalability: As data environments grow more complex, projects help segment and modularize integration work, making large-scale data transformations simpler to manage.
Isolation: Different projects can have unique configurations, connection parameters, and transformation strategies without interfering with each other, promoting clean architectural separation.
Pipeline Execution Consistency: The work required to be done as part of this feature will enable us to address inconsistencies and lack of visibility into configuration management and resolution
Implementing a project concept would significantly enhance Pentaho Data Integration's usability and enterprise-level data management capabilities.