This paper explores architectural strategies, resources allocation guidelines and cloud-native workflows that are time-tested to support mega-scale live streams and examines common failure scenarios and anti-patterns, identifies infrastructure bottlenecks and proposes fallback strategies to enhance resilience and reliability at massive concurrency scales.

Abstract

The rapid pace of content creation, proliferation of larger screen devices and easy internet access have led to an unprecedented surge in global user demand for the best-quality content streaming. When it comes to live sports streaming, unpredictable traffic patterns during a game can often overwhelm even the most well-designed systems. Reasons for this being: - The inadequate capabilities of traditional autoscalers to keep pace with a traffic spike; - Infrastructure limitations that are apparent only at mega-scale; and - Suboptimal system configurations. This paper explores architectural strategies, resources allocation guidelines and cloud-native workflows that are time-tested to support mega-scale live streams. This paper also examines common failure scenarios and anti-patterns, identifies infrastructure bottlenecks and proposes fallback strategies to enhance resilience and reliability at massive concurrency scales. Additionally, it shares our experience of supporting live cricket streaming on the AWS cloud for Indian audiences, where traffic can surge by over 1 million viewers per minute and occasionally drops from millions to a few hundred within seconds.

Introduction

The rise of video streaming platforms has revolutionized the way that the world consumes media today. This modern streaming landscape is characterized by a relentless demand for scalable, high-performance applications that can accommodate millions of concurrent users while maintaining the highest-quality user experiences.

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