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Scaling APIs to Billions - Extreme-Scale Reliability

Conf42 via YouTube

Overview

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Learn how to architect and scale APIs to handle billions of requests through this 18-minute conference talk that presents a comprehensive four-layer scaling framework. Explore real-world case studies from Netflix, Uber, and RevenueCat to understand extreme-scale reliability challenges and solutions. Master edge layer strategies including request coalescing and traffic pattern optimization, while discovering advanced techniques for rate limiting and multi-region architecture design. Dive into sharding methodologies and service mesh implementations that enable massive scalability. Understand the critical role of observability and predictive autoscaling in maintaining system reliability at extreme scale. Examine future challenges in API scaling and gain practical insights for building resilient, high-performance systems capable of handling billions of API requests with consistent reliability.

Syllabus

Introduction and Speaker Background
Transition to Extreme Scale Reliability
Case Studies: Netflix, Uber, and RevenueCat
Four-Layer Scaling Framework
Edge Layer Strategies
Request Coalescing and Traffic Patterns
Rate Limiting and Multi-Region Architecture
Sharding Techniques and Service Mesh
Observability and Predictive Autoscaling
Future Challenges and Conclusion

Taught by

Conf42

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