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GitHub Old Engineering Blog
See what the GitHub Engineering team is up to—from building features to solving the nagging challenges teams face as they grow.
By GitHub Old · GitHub Old · Added 2026-10-12
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Learn this repo
About 37 min left. Your work is saved as you go.
What this code is
GitHub Old maintains this code. You should know the basics: caching, queues and replication.
Ideas you will meet
- Distributed Systems
- Consensus, time, failure and the fundamentals of scale-out.
Go deeper on this
A path through videos, articles, other case studies and code on the same ideas as GitHub Old Engineering Blog.
Warm upGet the vocabulary first.
Books · Free from the author
Concurrent and Distributed Systems (Cambridge lecture notes)
Eight lectures on time, broadcast, replication, consensus and transactions, with notes, slides and video. Free from the author under CC BY-SA.
University of CambridgeIntermediate
Books · Free from the author
Computer Networks: A Systems Approach
How networks are built and why: protocols, routing, congestion control and the internet's architecture. The authors publish it free online under CC BY 4.0.
Systems ApproachIntermediate
WatchHow others solve the same problem, on video.
Videos belong to their creators and play from YouTube. More on YouTube (opens in a new tab)
ReadEngineers explain it in their own words.
Blogs · Free from the author · Read here
Scalable Web Architecture and Distributed Systems
A full chapter on the building blocks of large websites: availability, performance, reliability, scalability, caches, proxies, indexes, load balancers and queues. Free to read here under CC BY 3.0.
The Architecture of Open Source ApplicationsBeginner40 min
Papers · Read here
Facebook’s photo storage
This paper describes Haystack, an object storage system optimized for Facebook’s Photos application. Facebook currently stores over 260 billion images, which translates to over 20 petabytes of data.
USENIXIntermediate
See it in another companyThe same ideas, a different system.
Case Studies · Read here
Aroma: Using ML for Code Recommendation at Facebook
Thousands of engineers write the code to create our apps, which serve billions of people worldwide. This is no trivial task—our services have grown so diverse and complex that the codebase contains…
FacebookIntermediate
Case Studies · Read here
Brooklin: Distributed Service for Near Real-Time Data Streaming at LinkedIn
Brooklin—a distributed service for streaming data in near real-time and at scale—has been running in production at LinkedIn since 2016, powering thousands of data streams and over 2 trillion messages per day. Today, w...
LinkedInIntermediate
Read the codeSee how it looks when it is real.
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Curated reading list of articles on the architecture of scalable, reliable systems.
binhnguyennusIntermediate
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