Dagster-slurm: Bringing Modern Data Orchestration to Slurm-Managed

Jul 16, 2026·
Dr. Georg Heiler
Dr. Georg Heiler
Hernan Picatto
Hernan Picatto
· 1 min read
Abstract
dagster-slurm is an open-source Python integration that allows data scientists and research software engineers to run Dagster pipeline assets on both a laptop and Slurm-managed HPC supercomputers without making any code changes. It automatically handles SSH transport, environment packaging via pixi-pack, and Slurm job submission, while streaming logs and scheduler metrics back to the Dagster UI in real time. The talk covers the full workflow, from local development to staging and production deployment on a real HPC cluster, using a live demo with a self-contained Docker Compose environment. It has been validated on VSC-5 in Austria and CINECA Leonardo in Italy.
Date
Jul 16, 2026 2:35 PM
Location

McNamara Alumni Center, Minneapolis, Minnesota

events

Abstract

dagster-slurm is an open-source Python integration that allows data scientists and research software engineers to run Dagster pipeline assets on both a laptop and Slurm-managed HPC supercomputers without making any code changes. It automatically handles SSH transport, environment packaging via pixi-pack, and Slurm job submission, while streaming logs and scheduler metrics back to the Dagster UI in real time.

The talk covers the full workflow, from local development to staging and production deployment on a real HPC cluster, using a live demo with a self-contained Docker Compose environment. It has been validated on VSC-5 in Austria and CINECA Leonardo in Italy.

Dr. Georg Heiler
Authors
senior data expert
Georg is a co-founder @Jubust and a Senior data expert at Magenta as well as a ML-ops engineer at ASCII. He is solving challenges with data. His interests include geospatial graphs and time series. Georg transitions the data platform of Magenta to the cloud and is handling large scale multi-modal ML-ops challenges at ASCII.
Hernan Picatto
Authors
Researcher & data scientist

Researcher at the Supply Chain Intelligence Institute Austria (ASCII).

My research interest lies at the intersection of forecasting extreme events and causal analysis in high-frequency time series.