Maestro: Netflix’s Workflow Orchestrator
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+96
STARS · LAST 30 DAYS
3
PER DAY
#120
MOST-STARRED Java
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +21 | +96 | +270 |
| Per day | 3 | 3 | 3 |
| Forks gained | +2 | +6 | +16 |
maestro gained 96 stars in the last 30 days, about 3 a day, and now has 3.8K. It is about 2 years old and has averaged roughly 1.9K stars a year. It ranks #120 among Java repositories and #1,649 across all languages on GitHubRepo.
Trending Record
1
DAYS ON TRENDING
#2566
BEST RANK
Sep 30, 2026
FIRST APPEARANCE
Active
STATUS TODAY
maestro has maintained a continuous presence across global trending indexes, peaking at #2566. Below is the 30-day activity profile:
💡 Overview
maestro is an open-source project written in Java: Maestro: Netflix’s Workflow Orchestrator.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agentic-workflow, analytics, automation. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Java for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ git clone https://github.com/Netflix/maestro.git
cd maestro⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
JDK 17 or higher (OpenJDK / GraalVM)
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
maestro coordinates its core functionality through a modular Java pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with maestro.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install maestro using your package manager: `git clone https://github.com/Netflix/maestro.git`
Initialize your project workspace or configuration file for maestro.
Import maestro into your codebase or invoke it directly from your terminal.
Execute your test suite or run `maestro --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Java, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
Netflix/maestro is currently ranked #1,649 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #1,644 | devinross/tapkulibrary | Objective-C | ★ 3.9K | Compare ↗ |
| #1,645 | corazawaf/coraza | Go | ★ 3.8K | Compare ↗ |
| #1,646 | pulsejet/memories | PHP | ★ 3.8K | Compare ↗ |
| #1,647 | appshubcc/Bettbox | Go | ★ 3.8K | Compare ↗ |
| #1,648 | TNG/ArchUnit | Java | ★ 3.8K | Compare ↗ |
| #1,649 | Netflix/maestro This Project | Java | ★ 3.8K | |
| #1,650 | space-wizards/space-station-14 | C# | ★ 3.8K | Compare ↗ |
| #1,650 | yvgude/lean-ctx | Rust | ★ 3.8K | Compare ↗ |
| #1,652 | symfony/yaml | PHP | ★ 3.8K | Compare ↗ |
| #1,653 | haml/haml | Ruby | ★ 3.8K | Compare ↗ |
| #1,653 | kube-rs/kube | Rust | ★ 3.8K | Compare ↗ |
Frequently Asked Questions
What does maestro do? +
Maestro: Netflix’s Workflow Orchestrator
What language is maestro written in? +
The primary language is Java. Topics include: agentic-workflow, analytics, automation, batch-processing, dag.
Is maestro actively maintained? +
Yes, the last recorded push was on Sep 30, 2026 with 38 open issues being tracked.
How many stars does maestro have? +
maestro has 3,842 stars and 310 forks on GitHub.
How does maestro rank among GitHub repositories? +
With 3,842 stars, Netflix/maestro is ranked #1,649 globally across all repositories tracked on GitHubRepo and #120 among Java projects.
What license is maestro distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
