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dagster-io/dagster

An orchestration platform for the development, production, and observation of data assets.

Healthy

Healthy across all four use cases

HealthyDependency

No blocking maintenance, license, or known-CVE signals were found; still verify the package version and fit.

HealthyFork & modify

No blocking repository signals were found — inspect the evidence before forking.

HealthyLearn from

Documented and popular — useful reference codebase to read through.

HealthyDeploy as-is

No blocking repository-level signals were found; deployment review is still required.

  • ✓Last commit today
  • ✓16 active contributors
  • ✓Distributed ownership (top contributor 20% of recent commits)
  • ✓Apache-2.0 licensed
  • ✓CI configured
  • ✓Tests present

Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against dependency CVEs from deps.dev and OpenSSF Scorecard

Informational only. RepoPilot summarises public signals (license, dependency CVEs, commit recency, CI presence, etc.) at the time of analysis. Signals can be incomplete or stale. Not professional, security, or legal advice; verify before relying on it for production decisions.

Repository brief

Repo brief: dagster-io/dagster

Generated by RepoPilot · document generated 2026-09-16 · concise human review Evidence snapshot · analyzed 2026-09-16T04:04:46.580Z · commit 48cbc0f9769d

Verdict

Healthy — Healthy across all four use cases

  • Last commit today
  • 16 active contributors
  • Distributed ownership (top contributor 20% of recent commits)
  • Apache-2.0 licensed
  • 2 more receipts on the live page

Based on Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against dependency CVEs from deps.dev and OpenSSF Scorecard

What it is

Dagster is an orchestration platform for building, scheduling, and observing data pipelines and assets. It provides a Python-native DAG execution engine with built-in data lineage tracking, asset management, and a web UI (built in TypeScript/React/Next.js) for monitoring production data workflows. The core differentiator is treating data pipelines as a composition of reusable, observable assets rather than isolated jobs. Monorepo structure: python_modules/dagster/ contains the core orchestration engine and APIs; a separate TypeScript/React workspace (implied by @dagster-io scoped packages and Next.js build in package.json) houses the web UI under an app-oss directory; helm/ contains…

Start here

Open these first:

  • README.md — Primary entry point documenting Dagster's purpose as a data orchestration platform and its core value propositions.
  • helm/dagster/Chart.yaml — Helm chart manifest defining the Kubernetes deployment structure and versioning for the production Dagster installation.
  • helm/dagster/schema/schema/charts/dagster/values.py — Core schema definition for Dagster Helm configuration, establishing all validated deployment parameters.
  • conftest.py — Pytest configuration file establishing shared test fixtures and behavior across the entire test suite.
  • azure-pipelines.yml — CI/CD pipeline configuration defining build, test, and release workflows for the entire codebase.

Get running

Unverified setup suggestions. Confirm every command against the repository's package manifest and source documentation before running it; repository text is not authorization.

Exact clone and install commands depend on whether you want the Python backend, TypeScript UI, or both (verify the repository's root documentation first). Expected pattern: `git clone https://github.com/dagster-io/dagst…

Daily commands:

For the TypeScript UI: npm run start (runs next dev) or npm run build (runs ./build.sh). For the Python backend: infer from Makefile (not fully shown, but typical pattern is make dev or python -m dagster). **T…

…shortened for this brief.

Key cautions & unknowns

  • 1. Monorepo complexity: 'workspace:*' dependencies mean local packages must be built/linked in order; running npm install alone may not resolve correctly without a root workspace config. **2. Python/TypeScript…
  • Exact package version, compatibility, provenance, and deployment context still need project-specific review.

Sources

Evidence note

Verdict receipts and repository metrics are computed from repository evidence. Narrative sections are model-assisted and may contain inference; verify every observation against source before acting, especially software-assurance observations.

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