/Neo Kim

How Disney+ Scaled To 11 Million Users On Launch Day tl;dr: Disney+ scaled to 11M users on launch by running infrastructure in multiple regions for high availability and low latency, using CDN for caching, Kinesis for data streaming, DynamoDB for storing video timestamps and watchlists, a document store for the movie catalog, and machine learning for recommendations. They pre-partitioned and autoscaled DynamoDB to handle growing traffic. Neo discusses the architecture. 

featured in #506


How Zapier Automates Billions Of Tasks tl;dr: Neo takes a look at Zapier's architecture, highlighting its use of Nginx, Python Django, MySQL, Redis, AWS Lambda, RabbitMQ, and Celery for automating billions of tasks. It details Zapier's tech stack, asynchronous processing, scalability strategies, and how they handle task execution and history tracking, using technologies like GraphQL, Next.js, AWS S3, Kafka, and Elasticsearch for efficiency and scalability. 

featured in #493


How Disney+ Hotstar Delivered 5 Billion Emojis in Real Time tl;dr: This post outlines how Disney+ Hotstar delivered billions of emojis in real-time during the cricket World Cup in India to create a more engaging live experience. The post described how emojis were received from clients, processed and delivered at scale.

featured in #489