dagster-docker
A Dagster integration for docker
Decision gist · record as of 2026-08-14
Yes. This is a straightforward, actively maintained integration for a popular orchestration framework. Install it if you need to run Dagster assets in Docker containers. The low install friction, permissive license, and active maintenance make it a safe choice. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Docker to be installed and running on the system where Dagster executes jobs; Python 3.10 or later.
- Low friction installation with three runtime dependencies.
- Actively maintained with a release on 2026-08-14 and 15996 GitHub stars, indicating stable ongoing development.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions.
last release 2026-08-14 (0 days) · last repo commit 2026-08-13 · 15,996 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,711,129 downloads/mo, #2,927 on PyPI
Alternatives
Verify before relying
pip install dagster-docker
import dagster as dg
from dagster_docker import DockerExecutor
@dg.asset
def my_asset():
return "data"
defs = dg.Definitions(
assets=[my_asset],
executor=DockerExecutor()
)- Specific Docker image requirements or registry configuration options beyond the runtime dependencies listed.
- Whether container networking, volume mounting, or resource limits are configurable through this integration.
- Performance characteristics or overhead of containerized execution compared to in-process execution.
What it is and what it does
dagster-docker is a Dagster integration that allows you to run data assets and pipelines inside Docker containers as part of your Dagster orchestration. It bridges Dagster's declarative asset model with Docker's containerization, letting you define assets in Python and have them execute in isolated container environments managed by Dagster.
The package depends on dagster (the core orchestration framework), docker (the Python Docker client), and docker-image-py. It is designed for teams that want to containerize their data workflows while keeping them coordinated through Dagster's central orchestration, lineage tracking, and observability layer. It's part of Dagster's broader ecosystem of integrations for modern data infrastructure.
Use it for
- Run Dagster assets in Docker containers to isolate dependencies and ensure reproducible execution across environments.
- Orchestrate multi-container data pipelines where different assets require different runtime environments or system packages.
- Deploy data workflows to Kubernetes or other container platforms by containerizing Dagster job execution.
- Integrate legacy or third-party tools that are only available as Docker images into a Dagster-orchestrated data platform.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is a straightforward, actively maintained integration for a popular orchestration framework. Install it if you need to run Dagster assets in Docker containers. The low install friction, permissive license, and active maintenance make it a safe choice. No known security vulnerabilities.
Install
dagster-docker on PyPI
Before you install
Low friction installation with three runtime dependencies. Actively maintained with a release on 2026-08-14 and 15996 GitHub stars, indicating stable ongoing development.
Requires Docker to be installed and running on the system where Dagster executes jobs; Python 3.10 or later.
License in practice
Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions.
Quickstart
pip install dagster-docker
import dagster as dg
from dagster_docker import DockerExecutor
@dg.asset
def my_asset():
return "data"
defs = dg.Definitions(
assets=[my_asset],
executor=DockerExecutor()
)Verify before relying
- Specific Docker image requirements or registry configuration options beyond the runtime dependencies listed.
- Whether container networking, volume mounting, or resource limits are configurable through this integration.
- Performance characteristics or overhead of containerized execution compared to in-process execution.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesdagsterdockerdocker-image-py |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,711,129 / month, #2,927 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: dagster_docker-0.29.18-py3-none-any.whl
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See also dagster · dagster-cloud · dagster-cloud-cli · dagster-aws · dagster-azure · dagster-postgres · dagster-databricks · dagster-shell · dagster-celery-k8s · dagster-rest-resources