What are various workflow managers for GenAI and ML?

Airflow 

Astronomer => It takes Airflow to next level by running it as managed solution. It claims to have 1500+ integrations. 

Prefect 

Selentica Elements Workflow manager 

Dagster 

Prefect UI is like this below 

Main benefits with Prefect are 

Log retention and debugging

Clear observability with system-level metrics

Retries and transactional semantics

Flexible infrastructure and storage configuration

Intuitive UI and dashboard

Dagster 

https://dagster.io/

Frictionless end-to-end development workflow for data teams. Easily build, test, deploy, run, and iterate on data pipelines.

Modern, flexible architecture built to be fault-tolerant.

The critical “single pane of glass” for your data team: observe, optimize, and debug even the most complex data workflows.

Software-Defined Assets (SDAs) are a core concept in the Dagster framework. Working with SDAs is not mandatory, but they add a whole new dimension to the orchestration layer. SDAs allow you to:

• Manage complexity in your data environment.

• Write reusable, low-maintenance code.

• Gain greater control and insights across your pipelines and projects.

Selentica Elements Workflow manager

https://elements.salentica.com/kb/article/629-introduction-to-workflow-manager/