Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.
⚡ Executive Summary & Quick Facts
Authoritative Sourceai-performance-engineering is ai-performance-engineering is an open-source project written in Python: Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), cfregly/ai-performance-engineering has accumulated 2,201 GitHub stars and 313 forks. It is written in Python, licensed under Apache-2.0, and ranks #5,250 globally. It is actively maintained with the latest commit recorded on Nov 3, 2026.”
| Repository | cfregly/ai-performance-engineering ↗ |
|---|---|
| Primary Category | developer tools |
| Language & Stack | Python |
| Software License | Apache-2.0 |
| Community Traction | ★ 2.2K stars · ⑂ 313 forks · #5,250 globally |
| Maintenance | ● Active (Last commit: Nov 3, 2026) · 5 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 97/100 · Grade A+Yes, ai-performance-engineering is actively maintained. Continuous telemetry recorded the last code commit on Nov 3, 2026 (10 days ago). Supported by 2,201 stars and 313 community forks, this repository holds a calculated health index of 97/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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+161
STARS · LAST 30 DAYS
5
PER DAY
#764
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +161 | +161 | +450 |
| Per day | 23 | 5 | 5 |
| Forks gained | +33 | +33 | +16 |
ai-performance-engineering gained 161 stars in the last 30 days, about 5 a day, and now has 2.2K. It is about 2 years old and has averaged roughly 1.1K stars a year. It ranks #764 among Python repositories and #5,250 across all languages on GitHubRepo.
Trending Record
42
DAYS ON TRENDING
#777
BEST RANK
Sep 26, 2026
FIRST APPEARANCE
Active
STATUS TODAY
ai-performance-engineering has maintained a continuous presence across global trending indexes, peaking at #777. Below is the 30-day activity profile:
💡 Overview
ai-performance-engineering is an open-source project written in Python: Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.
Engineered for speed, consistency, and developer ease, it solves common hurdles in Python. 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 Python 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
$ pip install ai-performance-engineering⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
ai-performance-engineering coordinates its core functionality through a modular Python 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
Production System Integration
Embed ai-performance-engineering into Python backend services to handle core application logic.
CI/CD Automated Pipelines
Run automated validation, builds, and integration suites during deployments.
Developer Tooling & Workflows
Accelerate developer onboarding with pre-configured project utilities.
Open Source Extension
Fork and customize internal modules under the repository's open Apache-2.0 license.
🚀 Getting Started
Install ai-performance-engineering using your package manager: `pip install ai-performance-engineering`
Initialize your project workspace or configuration file for ai-performance-engineering.
Import ai-performance-engineering into your codebase or invoke it directly from your terminal.
Execute your test suite or run `ai-performance-engineering --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
cfregly/ai-performance-engineering is currently ranked #5,250 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
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| #5,249 | Bush2021/chrome_plus | C++ | ★ 2.2K | Compare ↗ |
| #5,250 | cfregly/ai-performance-engineering This Project | Python | ★ 2.2K | |
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Frequently Asked Questions
What does ai-performance-engineering do? +
Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.
Is ai-performance-engineering actively maintained in 2026? +
Yes, ai-performance-engineering is actively maintained. The latest code push was recorded on Nov 3, 2026 (10 days ago). It holds a calculated Maintenance Health Score of 97/100 (A+ rating) with 2,201 stars and 5 open issues.
What language is ai-performance-engineering written in? +
The primary language is Python. Topics include: software.
How many stars does ai-performance-engineering have? +
ai-performance-engineering has 2,201 stars and 313 forks on GitHub.
How does ai-performance-engineering rank among GitHub repositories? +
With 2,201 stars, cfregly/ai-performance-engineering is ranked #5,250 globally across all repositories tracked on GitHubRepo and #764 among Python projects.
What license is ai-performance-engineering distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
