The Dagster community meets every 2 months on the second Tuesday at 9 AM PST. At each meetup, the Dagster team will provide product updates and, depending on interest, community members will give lightning talks or demos. Click to register and be added to the calendar invite.

In our ninth Dagster Community Meeting, we heard from Alessandro Marrella at Earnest Research on using Dagster to power their machine learning pipelines. Owen and Max from the Elementl team presented our Dagster logging improvements and on our Dagster Cloud Private Beta.

In our eighth Dagster Community Meeting, we heard from Carlson Cheng at Thinking Machines on running Dagster for ML pipelines in production. With our new 0.12.0 release, our team presented our new features and the road to 1.0.

In our seventh Dagster Community Meeting, Simon Späti from Rohde & Schwarz MNT discussed the production Dagster setup at R&S, and the core team presented our recent API "approachability" improvements, as well as upcoming 0.12.0 features.

In our sixth Dagster Community Meeting, the core team presented upcoming 0.11.0 features, including Dynamic Orchestration, a system to establish Asset Lineage, and a new documentation site.

In our fifth Dagster Community Meeting, Dennis Hume from Drizly and Noah Kantrowitz from Geomagical Labs discussed about their production Dagster setups.

In our fourth Dagster Community Meeting, we showcased some 🔥 features in the upcoming 0.10.0 release.

Orchestrating dbt with Dagster: how to place dbt in context, de-silo your operational systems, improve monitoring, and enable self-service operations.

David Wallace, the data platform engineer at Good Eggs, shares some light on the different approaches to metadata management.

Emily, the data infrastructure lead at Drizly, covers how Dagster adds testing functionality for a dbt run and allows analysts to run specific models on production.

At the November Community Meeting, Tobias Macy talked about running Dagster in Production at MIT Open Learning, Dmitry Matasov showcased building a platform for data analysts using Dagster, and Daniel Gibson from the Dagster team presented new features coming out in Dagster 0.10.0.

This talk describes how Dagster can enable a unified stack of tooling across a wide dynamic range of use cases: from a laptop to a Kubernetes cluster; from local development, to monitoring in production; from data science, to data engineering, to machine learning.

This is the September 2020 community meeting where the Dagster team announced Dagster 0.9.0.

Digging Into Dagster: An Opinionated Open Source Framework For Data Orchestration

This is a kickoff meeting for the Dagster community where the Dagster team announced Dagster 0.8.0.

Weera Kasetsin, the data science lead at LINE Company (Thailand), talks about how LINE builds modern data application with the Dagster features of multiple output, pipeline modes and type-checking.

Scale By The Bay 2019

Dagster with Nick Schrock: Discussion on modern data engineering and why it continues to be so difficult for engineers to be productive with their data

We introduce Dagster, an open source Python library for building ETL processes, ML pipelines, and similar software systems, all of which we call data applications.

In this episode Nick Schrock, the founder of Elementl, explains his motivation for creating a product for data management, how the programming model simplifies the work of building testable and maintainable pipelines, and his vision for the future of data programming.

This talk introduced Dagster, an open source framework for building and modeling data processing computations.