Скачать или смотреть How Facebook & YouTube Handle BILLIONS of Likes & Views!

Ever wondered how platforms like Facebook and YouTube handle billions of likes and views daily? This video breaks down the massive system design challenge behind these familiar features. We explore the engineering marvels that allow these tech giants to process an incredible volume of interactions in near real time.

Discover the core principles these platforms use to manage such immense scale. We delve into distributed systems, asynchronous processing, and the crucial role of caching. Learn how NoSQL databases and specialized counters are essential for high volume writes and reads, and understand the concept of eventual consistency in achieving both performance and accuracy.

Follow the journey of a single like, from the optimistic update on your screen, through API gateways, load balancers, and into robust message queues like Kafka. See how worker services process these events to update counters in systems like Redis or Cassandra.

We also tackle the complexities of view counting. This includes client side tracking, stream processing for near real time aggregation, sophisticated filtering for bot traffic, and batch processing for durable, accurate counts. Find out why a traditional SQL database struggles with this kind of workload, facing issues like write contention and read scalability.

This explanation covers the sophisticated architecture combining distributed counters, aggressive caching strategies, and asynchronous operations that ensure these platforms run smoothly under extreme load. If you are curious about large scale system design, software architecture, or the technology powering social media and video platforms, this is for you.

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#SystemDesign
#Facebook
#YouTube
#BigData
#Scalability
#TechExplained
#SoftwareArchitecture
#DistributedSystems
#Caching
#NoSQL
#RealTimeData
#Likes
#Views
#DataEngineering
#CloudComputing
#TechInsights
#Developer
#Programming
#Backend
#HighAvailability