apache/dolphinscheduler

DolphinScheduler is a distributed, high-performance workflow orchestration platform designed for managing complex data pipelines and task dependencies. It provides a modular architecture that supports diverse data sources, task types, and storage backends, enabling users to define, schedule, and monitor intricate workflows. The system features a robust alerting subsystem with multiple notification channels, comprehensive audit logging, and flexible authentication mechanisms including OIDC and LDAP. It is designed for scalability and reliability, offering Kubernetes and Terraform deployment options alongside a standalone mode for development.

This period focused on restructuring the codebase into a modular plugin architecture, introducing dedicated modules for alerts, datasources, and task execution. The work standardized the API layer with new DTOs, controllers, and security implementations, while establishing a unified service layer and common utilities to support the new plugin-based design.

92 changes

This period focused on significantly expanding the platform's capabilities by introducing a wide array of new task, data source, and alert plugins, alongside a modular DAO architecture. The team also established a robust plugin-based storage system supporting multiple cloud providers and enhanced the alert server with RPC and health monitoring features.

85 changes

This period focused on enhancing the platform's extensibility by introducing new task and datasource plugins for cloud services like AWS, Alibaba Cloud, and gRPC. Concurrently, the codebase was refactored to improve observability through a new audit logging system and centralized configuration, while also strengthening reliability with comprehensive test coverage and stricter input validation.

31 changes

apache/dolphinscheduler was measured the same way every project in this corpus was: the same rubric, at a pinned commit, with the result published in full. Point the surveyor at a repository you know and see whether you agree with it.