# Dagster 1.11: Build Me Up Buttercup

> Introducing Dagster 1.11 “Build Me Up Buttercup”, shaped hand-in-hand with design partners and the community!

Source: https://dagster.io/blog/dagster-1-11-build-me-up-buttercup
Published: 2025-06-26

Introducing Dagster 1.11 “Build Me Up Buttercup”, shaped hand-in-hand with design partners and the community!

**Release Highlights:**

- **Components (stable)** brings configurable, reusable building blocks in YAML or Python that declare Dagster definitions without boilerplate.
- dg CLI (stable) is new command-line companion scaffolds code, accelerates development, and keeps large projects manageable.
- Cross-platform **create-dagster** command to spin up an opinionated **project or workspace** layouts in seconds.
- Various **quality-of-life boosts** across core orchestration and the UI.
- **Ecosystem power-ups**: Iceberg, dbt Cloud, Airflow, Fivetran, and an in-app Integrations Marketplace.
- …and more!

*Read on for the details.*

## **Components (stable):** Configurable, Reusable Building Blocks for Data Pipelines

Components deliver configurable, reusable building blocks in YAML or Python, letting you define Dagster assets and pipelines effortlessly.

- **Plug-and-play in YAML *or* Python:** Rapidly build pipelines from concise YAML or lightweight Python that lets you spin up arbitrary Dagster definitions (such as assets, resources, schedules, checks, and more) with almost no boilerplate. Ready-made components ship for **dbt, Fivetran, Airbyte, Sling, DLT, Power BI, and more**. Check out [Components documentation](https://docs.dagster.io/guides/build/components).

![\_\_wf\_reserved\_inherit](https://dagster.io/blog-assets/f12d95e489cbdc1808db.gif)

- **Automatic Documentation**: Metadata you already write auto-generates live reference pages and inline help, keeping builders unblocked and sparing you the README grind.

![\_\_wf\_reserved\_inherit](https://dagster.io/blog-assets/6350765a643fdc296f2a.gif)

- **Low-code, High-clarity DSL**
  - **Custom Components:** If you’re a data platform team serving many data users, wrap any internal script or third-party tool in a custom component and hand it over with the same polished tooling as the built-ins. No extra glue, no re-training your stakeholders.
  - **Powerful tooling:** High-quality errors, strongly typed definitions, and robust tooling integrated into your CI/CD workflows, for robust YAML management.
  - *Pythonic Templating:* Want more customization? Register reusable variables and Python helpers for extensive customization; this allow your stakeholders to craft entire workflows in one defs.yaml, without touching boilerplate.

## **dg (Stable): Your All-in-One CLI**

Think of **dg** as an IDE you run from your terminal: scaffold code, spin up a local Dagster with UI, launch jobs, and introspect definitions—all behind one command.

- **Code generation:** dg `scaffold` quickly generates definitions such as assets, components, and more, with zero boilerplate.
- **Local development & ad-hoc execution:** dg dev launches a full Dagster instance + UI in one command. dg `launch` kicks off jobs or assets right from the CLI for quick ad-hoc execution.
- **Introspection & validation:** View and validate definitions easily with dg list and dg check.
- **DX utilities:** Easily configure VSCode/Cursor extensions, generate schemas, and inspect components.

*All commands you're familiar with in the existing dagster CLI are also available here.* The dg CLI will eventually supersede the existing dagster CLI entirely, offering enhanced usability and a unified experience. (Note: Certain sub-commands are still forthcoming and will be added soon.)

![\_\_wf\_reserved\_inherit](https://dagster.io/blog-assets/6c764b9ff593c0d94e9d.gif)

### **create-dagster**: One-shot project bootstrapper

Instantly set up production-ready Dagster projects or workspaces with one simple command and no dependencies required. This modernized command supersedes the previous scaffold workflow, offering:

- A standardized Python directory layout.
- Preconfigured local dg CLI setup.
- Workspace scaffolding capability (newly supported).
- No active Python environment required (pipx, uvx, brew, curl friendly).

![\_\_wf\_reserved\_inherit](https://dagster.io/blog-assets/368b557c1f49455244f3.gif)

## UI

- **Unified asset selection:** A flexible, expressive syntax to easily define selections across your assets. Powers alerts, insights, and saved views. **Learn more in** <https://dagster.io/blog/updated-asset-selection-syntax>
- **Runs › Backfills** consolidates all backfill activity under the Runs page for faster navigation.
- **Enhanced Asset Graph:** Redesigned, customizable nodes with detailed health indicators.

![\_\_wf\_reserved\_inherit](https://dagster.io/blog-assets/509f098dc5074cb6abcc.gif)

## Core Orchestration Enhancements

- **Improved Partial Retries:** A new re-execution option enabled for re-running only failed assets within multi-asset steps, rather than all asset assets within a failed step. This saves resources and time in heavy dbt execution, multi-asset factories.
- **Checks in Ops:** You can now use asset checks with Ops. Fits your operational and dynamic workflows that don’t fit in Assets paradiam.
- **Hooks in Assets:** Success/failure callbacks now available in assets.
- **Efficient Backfills & Concurrency Management:** Improved backfill policies and multi-threading support enhance scheduling efficiency; run blocking is now default, preventing oversubscription.

## Integrations

- **Fivetran integration GA:** the **`FivetranWorkspace`** resource is now GA \[[docs](https://docs.dagster.io/integrations/libraries/fivetran)].
- **dbt Cloud (Beta):** first-class job launches and lineage capture  \[[docs](https://docs.dagster.io/integrations/libraries/dbt/dbt-cloud)].
- **Apache Iceberg (Preview):** Iceberg IOManager writes/reads lake-house tables \[[docs](https://docs.dagster.io/integrations/libraries/iceberg)].
- **Airflow (Beta):** Airflow Component lets you surface Airflow DAGs inside Dagster for mixed-orchestrator observability \[[docs](https://docs.dagster.io/migration/airflow-to-dagster/airflow-component-tutorial)].
- **Integrations Marketplace (Preview):** “Integrations” tab to browse first- and third-party integrations natively in Dagster UI (enable via User Settings → “Display integrations marketplace”).

![\_\_wf\_reserved\_inherit](https://dagster.io/blog-assets/82c66296764a89213dc8.gif)

## Acknowledgments

Huge thanks to everyone who opened issues, filed PRs, tested previews, and cheered us on. Dagster wouldn’t be what it is without you.

- [Anush (Anush008)](https://github.com/Anush008)
- [Alex Noonan (C00ldudeNoonan)](https://github.com/C00ldudeNoonan)
- [Dino Scheidt (D1no)](https://github.com/D1no)
- [Exlll (Exlll)](https://github.com/Exlll)
- [Fredrik Bakken (FredrikBakken)](https://github.com/FredrikBakken)
- [HynekBlaha (HynekBlaha)](https://github.com/HynekBlaha)
- [OwenKephart (OwenKephart)](https://github.com/OwenKephart)
- [Pedram Navid (PedramNavid)](https://github.com/PedramNavid)
- [Morgan PERRE (Thenkei)](https://github.com/Thenkei)
- [Julien "uj" Abadji (Uinelj)](https://github.com/Uinelj)
- [Andreas Buchmüller (abuchmueller)](https://github.com/abuchmueller)
- [Adam Bloom (adam-bloom)](https://github.com/adam-bloom)
- [Alexander Grueneberg (agrueneberg)](https://github.com/agrueneberg)
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- [Ross Housewright (ross-whatnot)](https://github.com/ross-whatnot)
- [Marco polo (salazarm)](https://github.com/salazarm)
- [Sean Quinlan (sbquinlan)](https://github.com/sbquinlan)
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- [shimon pats (shimon-cherrypick)](https://github.com/shimon-cherrypick)
- [Sean Mackesey (smackesey)](https://github.com/smackesey)
- [Paul Stepler-Camp (steplercamp)](https://github.com/steplercamp)
- [Steven Ayers (stevenayers)](https://github.com/stevenayers)
- [Mohan Talla (tallamohan)](https://github.com/tallamohan)
- [Dimitry Foures (thedimlebowski)](https://github.com/thedimlebowski)
- [Martin Erpicum (tintamarre)](https://github.com/tintamarre)
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- [Yuhan Luo (yuhan)](https://github.com/yuhan)
- [Shane Zarechian (zero-stroke)](https://github.com/zero-stroke)

Stay tuned for more updates and enhancements in future releases—and, as always, happy data engineering!