# Netflix/maestro

Maestro: Netflix’s Workflow Orchestrator

Repository: https://github.com/Netflix/maestro
Canonical: https://ross.abutalabs.com/products/netflix-maestro
Homepage: https://maestro-doc.github.io
Language: Java
License: Apache-2.0
License Family: permissive
Topics: analytics, automation, batch-processing, dag, data-engineering, data-ops, data-orchestrator, data-pipelines, data-science, elt, etl, java, machine-learning, mlops, orchestration, scheduler, workflow, workflow-engine, workflow-orchestration, agentic-workflow
Last push: 2026-08-26T17:54:39+00:00

## Health v2 (maintenance only)
Score: 69/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 62
- inputs: {"age_days": 869, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3829, forks 307 (observed 2026-08-28T04:08:23.115400+00:00)

## What it is
Netflix Maestro is a general-purpose workflow orchestrator providing workflow-as-a-service for data, ML, and software pipelines. It schedules DAG-based workflows at massive scale, handling hundreds of thousands of workflows and millions of jobs daily.

## Use cases
- orchestrate ETL and ELT data pipelines as DAGs
- schedule machine learning and MLOps workflows
- run batch processing jobs on a schedule
- manage workflow dependencies and triggers at scale
- orchestrate agentic workflows
- self-host a workflow-as-a-service platform

## When to choose
- you need proven, large-scale workflow orchestration used in production at Netflix
- you want a scalable DAG scheduler for data and ML pipelines
- you need a workflow engine with strict SLOs and high throughput

## When to avoid
- you need a lightweight single-machine cron replacement
- your team is not comfortable running Java/Spring services
- you want a simple UI-first orchestrator with minimal setup

## Facets
- artifact type: service
- maturity: active
- function: workflow-automation, scheduling, etl
- domain: big-data, machine-learning, developer-tools
- platform: jvm, cloud, self-hosted
- tags: workflow-orchestrator, dag, waas, data-pipelines, mlops, scheduler, elt, batch-processing, data-engineering, automation, docker, web-server

## Member repositories
- Netflix/maestro (main) score 69

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:23.115400+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:26:19.938336+00:00, confidence not recorded.
  - readme: https://github.com/Netflix/maestro (fetched 2026-08-28T04:08:23.115400+00:00, sha 884ddf0c7dc5)
  - homepage: https://maestro-doc.github.io (fetched 2026-08-29T09:20:59.292290+00:00, sha dacfd1f16011)
- Data as of 2026-08-30T08:39:29.467469+00:00.