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ashishps1 / awesome-engineering-articles

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A curated collection of 300+ engineering blog articles from top tech companies. Learn how the best engineering teams solve real-world problems at scale.

algomaster.io ai data-engineering database distributed-systems engineering
344
62
100% credibility
Found Feb 17, 2026 at 29 stars 10x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

A curated collection of over 300 engineering blog articles from leading tech companies, organized by company with topics like AI, performance, and databases, and years published.

How It Works

1
🔍 Find the collection

While looking for real-world engineering tips from big tech companies, you discover this curated list on GitHub.

2
📂 Browse the companies

You open the page and see a friendly table listing dozens of top companies like Netflix, Google, and Airbnb with their best articles.

3
🏢 Pick a company to explore

Choose a company that interests you and scan their handpicked articles on topics like speed, smart recommendations, or handling huge crowds.

4
📖 Dive into the stories

Click on article links to read how these teams solve massive everyday challenges in simple, inspiring ways.

5
⭐ Save and share

Star the list to keep it handy or suggest new articles to help others learn too.

🎉 Unlock expert insights

You've gained practical knowledge from the world's top engineering teams to make your own work smarter and faster.

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AI-Generated Review

What is awesome-engineering-articles?

This GitHub repo delivers a curated collection of 300+ engineering blog articles from top tech companies like Netflix, Uber, and Meta. It organizes them by company in markdown tables, tagging topics such as AI/ML, databases, performance, and search, with direct links, years, and summaries. Developers get a one-stop github curated list to study how the best teams tackle scaling, infrastructure, and real-world problems without endless googling.

Why is it gaining traction?

Unlike scattered bookmarks or generic aggregators, this awesome curated collection focuses solely on high-quality, technical posts from proven engineering orgs, making it a true genius for quick deep dives. The clean table format and contributing guidelines encourage community growth, standing out as a practical github curated programming resource. Developers hook on the time savings—filter by topic or company for targeted insights like DoorDash's search engine or Figma's Postgres scaling.

Who should use this?

Senior engineers architecting distributed systems, ML leads researching production models, or backend devs optimizing at scale. Ideal for tech leads onboarding teams with battle-tested case studies, or anyone prepping system design interviews by reviewing Netflix's counters or Uber's Kafka setups.

Verdict

Solid starter for engineering lore, but with 26 stars and 1.0% credibility score, it's early-stage—docs are just the README, no tests needed. Star it and contribute to build momentum; worth bookmarking over rebuilding your own list.

(198 words)

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