Foundations Of Scalable Systems Pdf Github Free Upd May 2026

You're looking for a write-up on the foundations of scalable systems, specifically a PDF that is available for free on GitHub.

Stick to the GitHub repos and author-approved PDFs. The engineers who write these books fund the next editions. If you use a free PDF and love it, buy a physical copy for your bookshelf. It is a career investment, not a cost. foundations of scalable systems pdf github free

• Horizontal scaling: The ability to add more machines to a system to handle increased load.
• Load balancing: Distributing workload across multiple machines to ensure no single point of failure.
• Caching: Storing frequently accessed data in memory to reduce latency.
• Database sharding: Splitting a large database into smaller, more manageable pieces.
• Microservices architecture: Breaking down a monolithic system into smaller, independent services.

• Database scaling (Sharding, Replication, Leader-Follower).
• Microservices communication (Synchronous REST vs. Asynchronous Messaging).
• Distributed system fallacies and CAP Theorem trade-offs (Consistency vs. Availability vs. Partition Tolerance).

• Kleppmann, M. (2017). Designing data-intensive applications: The big ideas behind reliable, scalable, and maintainable systems. O'Reilly Media.
• Hawkins, T. (n.d.). Scalable Systems. GitHub repository.
• MIT OpenCourseWare. (n.d.). Foundations of Scalable Systems. Free online course.

• Week 1 (Protocols): Read the networking chapters from Distributed Systems (Tanenbaum) PDF. Focus on RPC vs REST vs gRPC.
• Week 2 (Data): Open the DDIA Summary PDF. Replicate the "SSTables and LSM Trees" example on paper.
• Week 3 (Consistency): Read the CAP Theorem section in System Design Primer PDF. Build a simple Python script that simulates network partition.
• Week 4 (Queues): Go to GitHub repo donnemartin/system-design-primer. Study the "Message Queues" section. Implement a producer-consumer model in your language of choice.
• Week 5 (Caching): Download the O'Reilly Scalability Guide. Build a Redis cache with a TTL eviction policy.
• Week 6 (Project): Combine all PDF learnings to design a scalable URL shortener (like TinyURL) using sharding and async logging.

1. Design for Failure: Anticipating and designing for failure, using techniques such as redundancy and fault tolerance.
2. Monitor and Measure: Monitoring and measuring system performance to identify bottlenecks and areas for improvement.
3. Automate: Automating processes and tasks to reduce manual intervention and improve efficiency.
4. Test for Scalability: Testing systems for scalability, using techniques such as load testing and stress testing.

CS6650 Course Site: Ian Gorton's bsds-6650 GitHub repository provides academic materials and detailed lecture notes for his "Building Scalable Distributed Systems" course, which closely mirrors the book's structure. You're looking for a write-up on the foundations