awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
💡 Why It Matters
The awesome-scalability repository addresses the critical need for engineers to design scalable and reliable systems. It serves as a comprehensive resource for ML/AI teams looking to enhance their architecture and design patterns. With a steady growth of 1,969 stars over 96 days, it demonstrates a strong community interest, indicating its relevance and maturity as a production-ready solution. However, it may not be the right choice for teams seeking highly specialised frameworks or those working on very small-scale projects.
🎯 When to Use
This repository is a strong choice when teams are developing large-scale systems that require robust architecture and proven design patterns. Teams should consider alternatives if they are focused on niche applications or require highly specific solutions not covered in this resource.
👥 Team Fit & Use Cases
This open source tool for engineering teams is particularly useful for software architects, backend developers, and data engineers. It typically finds application in products and systems that handle large volumes of data, such as cloud services, data pipelines, and machine learning platforms.
🎭 Best For
🏷️ Topics & Ecosystem
📊 Activity
Latest commit: 2026-01-04. Over the past 97 days, this repository gained 2.0k stars (+3.0% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.