---
title: "FLsystem-paper vs machine-learning-systems-design"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/amberljc-flsystem-paper-vs-chiphuyen-machine-learning-systems-design"
tools: ["amberljc-flsystem-paper", "chiphuyen-machine-learning-systems-design"]
---

# FLsystem-paper vs machine-learning-systems-design

*GraphCanon updated Aug 14, 2026*

## Verdict

Pick FLsystem-paper if fLsystem-paper is a curated list of federated learning systems literature geared towards providing research and development insights exclusively from big tech companies and open-source projects; pick machine-learning-systems-design if a booklet designed to provide an overview of machine learning systems design, featuring hands-on exercises and practical resources.

[FLsystem-paper](https://github.com/AmberLJC/FLsystem-paper) reports 75 GitHub stars, 7 forks, and 1 open issues, last pushed Feb 7, 2024. [machine-learning-systems-design](https://huyenchip.com/machine-learning-systems-design/toc.html) has 11k stars, 1.6k forks, and 11 open issues, last pushed Apr 15, 2023. Figures are from public GitHub metadata via [FLsystem-paper's repository](https://github.com/AmberLJC/FLsystem-paper) and [machine-learning-systems-design's repository](https://github.com/chiphuyen/machine-learning-systems-design).

| | [FLsystem-paper](/tools/amberljc-flsystem-paper.md) | [machine-learning-systems-design](/tools/chiphuyen-machine-learning-systems-design.md) |
| --- | --- | --- |
| Tagline | A curated list of FL system-related academic papers and frameworks | A booklet on machine learning systems design with exercises |
| Stars | 75 | 10,509 |
| Forks | 7 | 1,628 |
| Open issues | 1 | 11 |
| Language | - | HTML |
| Adopt for | FLsystem-paper is a curated list of federated learning systems literature geared towards providing research and development insights exclusively from big tech companies and open-source projects. | A booklet designed to provide an overview of machine learning systems design, featuring hands-on exercises and practical resources. |
| Persona | - | developer harness |
| Runtime | - | - |
| License | (unknown) | License information is unavailable. |
| Categories | Developer Tools, Model Training | Data & Retrieval, Developer Tools, Evaluation & Observability, Inference & Serving, Model Training |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [FLsystem-paper](/tools/amberljc-flsystem-paper.md) | [machine-learning-systems-design](/tools/chiphuyen-machine-learning-systems-design.md) |
| --- | --- | --- |
| Days since push | 909d | 1217d |
| Open issues (now) | 1 | 11 |
| Stars delta | Unknown | +54 (30d) |
| Open issues delta | Unknown | 0 (30d) |
| Full report | [trust report](/tools/amberljc-flsystem-paper/trust.md) | [trust report](/tools/chiphuyen-machine-learning-systems-design/trust.md) |

## Decision facts: FLsystem-paper

- **Hosting:** self hosted - (no information available)
- **Pricing:** freemium - The repository itself is free and open source, but usage might involve proprietary frameworks or projects from big tech companies that could have their own licensing models.
- **Adopt for:** FLsystem-paper is a curated list of federated learning systems literature geared towards providing research and development insights exclusively from big tech companies and open-source projects.
- **License detail:** (unknown)

## Decision facts: machine-learning-systems-design

- **Pricing:** freemium - Free to use, no charge for the booklet but additional content like answers to practice questions may be contained in a book that entails a cost.
- **Adopt for:** A booklet designed to provide an overview of machine learning systems design, featuring hands-on exercises and practical resources.
- **License detail:** License information is unavailable.
- **Persona:** developer harness

## Choose when

### Choose FLsystem-paper if…

- (no information available)
- Pricing: The repository itself is free and open source, but usage might involve proprietary frameworks or projects from big tech companies that could have their own licensing models..
- Tags unique to FLsystem-paper: federated-learning, machine-learning, papers.
- When you need to focus on federated learning systems contributions from major technology firms like Apple, Google, Meta, Microsoft, IBM, Nvidia, WeBank, and Alibaba.

### Choose machine-learning-systems-design if…

- Pricing: Free to use, no charge for the booklet but additional content like answers to practice questions may be contained in a book that entails a cost..
- Tags unique to machine-learning-systems-design: data-science, machine-learning-production, mlops.
- Also covers Data & Retrieval, Evaluation & Observability, Inference & Serving.
- Use for a quick initial introduction to the key aspects of ML system design if you are unfamiliar with the foundational concepts.

## When NOT to use FLsystem-paper

- If your research scope is broader than federated learning systems; this repository focuses specifically on the system aspects within FL.
- For a comprehensive collection that includes other ML domains, as FLsystem-paper restricts its curation to federated learning systems and closely related works.

## When NOT to use machine-learning-systems-design

- Not recommended if you require an exhaustive guide; this booklet has been superseded by a more comprehensive book 'Designing Machine Learning Systems'.
- Avoid using solely as the basis for designing production-ready machine learning systems without further reading and validation from current industry standards or more recent resources.

## Common questions

### What is the difference between FLsystem-paper and machine-learning-systems-design?

FLsystem-paper: A curated list of FL system-related academic papers and frameworks. machine-learning-systems-design: A booklet on machine learning systems design with exercises. See the comparison table for live GitHub stats and shared categories.

### When should I choose FLsystem-paper over machine-learning-systems-design?

Choose FLsystem-paper over machine-learning-systems-design when (no information available); Pricing: The repository itself is free and open source, but usage might involve proprietary frameworks or projects from big tech companies that could have their own licensing models.; Tags unique to FLsystem-paper: federated-learning, machine-learning, papers; When you need to focus on federated learning systems contributions from major technology firms like Apple, Google, Meta, Microsoft, IBM, Nvidia, WeBank, and Alibaba.

### When should I choose machine-learning-systems-design over FLsystem-paper?

Choose machine-learning-systems-design over FLsystem-paper when Pricing: Free to use, no charge for the booklet but additional content like answers to practice questions may be contained in a book that entails a cost.; Tags unique to machine-learning-systems-design: data-science, machine-learning-production, mlops; Also covers Data & Retrieval, Evaluation & Observability, Inference & Serving; Use for a quick initial introduction to the key aspects of ML system design if you are unfamiliar with the foundational concepts.

### When should I avoid FLsystem-paper?

If your research scope is broader than federated learning systems; this repository focuses specifically on the system aspects within FL. For a comprehensive collection that includes other ML domains, as FLsystem-paper restricts its curation to federated learning systems and closely related works.

### When should I avoid machine-learning-systems-design?

Not recommended if you require an exhaustive guide; this booklet has been superseded by a more comprehensive book 'Designing Machine Learning Systems'. Avoid using solely as the basis for designing production-ready machine learning systems without further reading and validation from current industry standards or more recent resources.

### Is FLsystem-paper or machine-learning-systems-design more popular on GitHub?

machine-learning-systems-design has more GitHub stars (10,509 vs 75). Stars measure visibility, not whether either tool fits your constraints.

### Are FLsystem-paper and machine-learning-systems-design open source?

Yes - both are open-source projects on GitHub.

### Where can I find alternatives to FLsystem-paper or machine-learning-systems-design?

GraphCanon lists graph-backed alternatives at [FLsystem-paper alternatives](/tools/amberljc-flsystem-paper/alternatives) and [machine-learning-systems-design alternatives](/tools/chiphuyen-machine-learning-systems-design/alternatives) ([FLsystem-paper markdown twin](/tools/amberljc-flsystem-paper/alternatives.md), [machine-learning-systems-design markdown twin](/tools/chiphuyen-machine-learning-systems-design/alternatives.md)), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at [this comparison](/compare/amberljc-flsystem-paper-vs-chiphuyen-machine-learning-systems-design.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, FLsystem-paper or machine-learning-systems-design?

FLsystem-paper: Dormant. machine-learning-systems-design: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for FLsystem-paper and machine-learning-systems-design?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FLsystem-paper trust report](/tools/amberljc-flsystem-paper/trust); [machine-learning-systems-design trust report](/tools/chiphuyen-machine-learning-systems-design/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=amberljc-flsystem-paper`](/api/graphcanon/graph?tool=amberljc-flsystem-paper)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_