Alex (The Engineering Bolt) ⚡Are you looking to master system design in record time? The fastest way to accelerate your learning is by studying real-world architectures of companies that handle massive scale and complexity. We've curated 14 essential case studies that reveal the secrets behind some of the world's most efficient and scalable systems. Dive in, and in just one month—or even less—you'll significantly elevate your system design prowess.
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1. How PayPal Supported a Billion Transactions Per Day with Only 8 Virtual Machines
Ever wonder how PayPal processes an astronomical number of transactions without an army of servers? Discover how they leveraged the Actor Model—a concurrency design pattern—to efficiently handle a billion transactions daily using just eight virtual machines.
2. 8 Reasons Why WhatsApp Supported 50 Billion Messages Daily with Only 32 Engineers
WhatsApp's lean team managed to support billions of messages every day. Uncover the engineering philosophies and architectural choices that made this possible, including their use of Erlang and a relentless focus on simplicity.
3. How Uber Computes ETA at Half a Million Requests Per Second
Providing accurate estimated arrival times (ETA) is crucial for Uber's user experience. Explore how Uber's system handles 500,000 ETA requests per second, ensuring riders know exactly when their driver will arrive.
4. How YouTube Supported 2.49 Billion Users with MySQL
Scaling a database to handle billions of users is no small feat. Learn how YouTube utilized MySQL and Vitess, an open-source scaling solution, to serve a global audience without sacrificing performance.
5. How Uber Finds Nearby Drivers at 1 Million Requests Per Second
Matching riders with drivers instantly is at the heart of Uber's service. Unpack the geospatial indexing and real-time processing techniques that enable Uber to handle a million location-based requests every second.
6. How Stripe Prevents Double Payments Using Idempotent APIs
Payment errors can erode trust. See how Stripe avoids duplicate charges by implementing idempotent APIs, guaranteeing that multiple identical requests result in a single action.
7. How Amazon S3 Achieves 99.999999999% Durability
Data durability is critical for storage services. Learn about the design principles and redundancy mechanisms that allow Amazon S3 to offer eleven nines of durability, ensuring your data is safe and accessible.
👉 Learn about S3's architecture
- How AWS Lambda Works
Serverless computing is transforming how we build applications. Dive into AWS Lambda's architecture to understand how it executes code in response to events without server management.
9. How Cloudflare Supports 55 Million Requests Per Second with 15 Postgres Clusters
Handling internet-scale traffic requires robust infrastructure. Discover how Cloudflare manages 55 million requests per second by efficiently utilizing just 15 PostgreSQL clusters.
10. How to Scale an App to 10 Million Users on AWS
Scaling isn't just for giants like Amazon or Google. Learn practical strategies for scaling your application to handle 10 million users using AWS services, from load balancing to database optimization.
11. How Instagram Scaled to 2.5 Billion Users
From a simple photo-sharing app to a global social media platform, Instagram's growth is a masterclass in scaling. Explore the architectural decisions and technologies that supported its explosive user base expansion.
👉 Discover Instagram's journey
12. How Tinder Scaled to 1.6 Billion Swipes Per Day
Real-time matching at scale is complex. See how Tinder handles 1.6 billion swipes daily, ensuring quick matches and a seamless user experience through efficient system design.
👉 Explore Tinder's architecture
13. Slack Architecture
Collaboration tools need to be reliable and fast. Explore Slack's architecture to understand how it supports millions of users with real-time messaging and integrations.
14. How Meta Achieves 99.99999999% Cache Consistency
Maintaining cache consistency at scale is challenging. Discover how Meta (formerly Facebook) achieves near-perfect cache consistency across its massive infrastructure, ensuring users see up-to-date information.
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