---
id: dagster-cloud
version: "1.13.18"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# dagster-cloud

License: permissive · Maintenance: active · Downloads: 4.7M/mo

## What it is and what it does

Dagster Cloud is the managed, cloud-hosted version of the Dagster orchestration framework. It provides a Python package that acts as an agent and CLI for deploying, managing, and monitoring data pipelines on Dagster's infrastructure. The package wraps core Dagster functionality (via the dagster dependency) with cloud-specific tooling: a command-line interface built on typer and questionary, HTTP request handling via requests, and executable packaging via pex. It supports both serverless and hybrid deployment models, allowing teams to run data workflows without managing orchestration infrastructure directly.

Typical usage involves installing the package, authenticating with Dagster Cloud credentials, and using the CLI to deploy Dagster jobs and assets to the cloud platform. The package is designed for developers and system administrators who want to orchestrate data pipelines with minimal infrastructure overhead. It's part of the broader Dagster ecosystem but specifically targets users who prefer managed hosting over self-hosted Dagster deployments.

Use it for:

- Deploy Dagster data pipelines to a managed cloud platform without provisioning orchestration infrastructure.
- Use the dagster-cloud CLI to manage agents, monitor job runs, and configure cloud deployments from the command line.
- Run data workflows in a serverless environment with automatic scaling and built-in CI/CD integration.
- Manage multiple Dagster environments (dev, staging, prod) using Dagster Cloud's branching and multi-environment features.
- Integrate data orchestration into a team's existing cloud infrastructure using hybrid deployment mode.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Dagster Cloud is a managed orchestration platform that deploys and runs data pipelines with serverless or hybrid infrastructure, providing CLI tooling and agent management for Dagster workflows.

Yes, if you are already using Dagster and want to move to a managed cloud platform. The package is actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is low. However, verify first whether your use case requires a Dagster Cloud account and whether the feature set (branching, CI/CD) you need is included in your tier.

## Install

pip install dagster-cloud
uv add dagster-cloud
poetry add dagster-cloud

## Installing dagster-cloud

Before you install: Low install friction with a wheel-only distribution. Actively maintained with a release on 2026-08-14 and last commit on 2026-08-22. Depends on seven runtime packages including dagster, typer, and requests—all common, stable dependencies.

License in practice: Apache-2.0 is permissive: you can use, modify, and distribute this package freely in commercial and open-source projects, provided you include a copy of the license and state significant changes.

Quickstart:

pip install dagster-cloud

from dagster_cloud import DagsterCloudAgent

# Configure and deploy via CLI or programmatically
# dagster-cloud agent start

Requires Python 3.10 or later (supports up to 3.14). Dagster Cloud Agent typically requires cloud credentials and network access to Dagster Cloud infrastructure.

Verify before relying:

- Whether the package can be used standalone or requires a Dagster Cloud account and active subscription.
- What specific cloud providers or deployment models (serverless vs. hybrid) are supported by this version.
- Whether branching and CI/CD features mentioned in the description are included in the open-source distribution or require a paid tier.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 4.7M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

data pipeline orchestration, serverless workflow execution, dagster cloud deployment, data orchestration platform, workflow scheduling and monitoring, hybrid cloud data pipelines, orchestration agent management, orchestration, data-pipeline, managed-service

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