Customer Sharing: 17 Media - Scale to 12,000,000 Users with AWS
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10 million downloads in less than 8 months! The speaker from 17 Media will share what challenges they have faced in this massive user growth and how they have have been so successful in the cloud. You are invited to learn a lot from the cloud journey of the 17 Media.
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Customer Sharing: 17 Media - Scale to 12,000,000 Users with AWS
- 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 5/20/2016 Scale to 12,000,000 users with AWS Kevin Li, Product Lead, 17 Media
- 2. Your Life’s Moment 17 – 你的生活點滴
- 4. Principle of Architecture Evolution Figure out the business need of the current stage Balance the quality and time to market Optimize the bottleneck first
- 5. What’s the need of 17 architecture? Scalable Available Personalized Grow with the users Always there for users Understand the users
- 6. The journey of our architecture
- 7. User 100 – Launch ASAP
- 8. First 100 users Don’t even think about scalability Launch and verify the idea ASAP Amazon Route 53 Amazon EC2 MongoDB Request
- 9. User 100,000 – CDN and Cache
- 10. User 100,000 Cache the database Use CDN to deliver the live streaming content CDNAmazon Route 53 Amazon EC2 MongoDB Request Amazon ElastiCache
- 11. User 1 million – Design for failure
- 12. Design for failure Failures are the norm, not exceptions Suppose the rate of failure of one machine is once every 10 years (120 month) The mean time of failure (MTTF) is 1 month if you have 120 servers
- 13. Always assume that things will go WRONG, and design for it
- 14. Design for failure Amazon Route 53 Amazon EC2 MongoDB Amazon EC2 Amazon EC2 MongoDB MongoDB Elastic Load Balancing Multi-AZ Multi-AZ Mix spot and on-demand to save the cost TIP: Use C3 instance for spot Amazon ElastiCache
- 15. Are your servers PET or CATTLE?
- 16. Pet servers Unique, lovingly hand raised servers When they get ill, someone has to fix it at 4 am Usually database server, like mysql, mongo,…
- 17. Cattle servers They are almost identical If they get ill, replace with another one Usually API servers, workers
- 18. Let AWS raise the pets, and we raise the cattle
- 19. User 5 million – Build loosely coupled systems
- 20. User 5 million – Build loosely coupled systems Our system was a monolithic system consists of API ServerStreaming Server Worker Application Server
- 21. API ServerStreaming Server Worker Application Server We discovered a bug that the API servers didn’t send requests to worker
- 22. API ServerStreaming Server Worker Application Server After fixed, the overloaded worker crashed the whole server
- 23. Split the service, so that it’s easier to scale, and fail independently
- 24. Build loosely coupled systems API Server Streaming Server Worker API Server API Server Streaming Server Worker Worker Amazon SQS API Cluster Worker Cluster Streaming Cluster
- 25. Monitor for each service, and design for failure
- 26. User 10,000,000 – Data
- 27. Business Intelligence Who’s our best streamers? How’s the retention changes among different version? We need a real-time data pipeline and self-service tool for the business team Which event is the most effective?
- 28. User 10,000,000 - Data and Personalization Amazon Kinesis Amazon S3 bucket Amazon EC2 Event Data AWS Lambda A real-time self-service dashboard for the management and marketing team
- 29. Fraud Detection and Security Monitoring Hackers are always trying to get valuable stuff from your service, like virtual goods, data,… Lots of spammer leaves dirty words or fraud information You’ll need enough data to detect the fraud and prevent it
- 30. “50% of reddit’s development time focused on stopping spam and vote cheating” - Jeremy Edberg, Chief Architect of Reddit
- 31. Log Search Our customer service often received many questions To answer those questions, we need a log search system “I bought 1,000 points, but didn’t receive” “My stream isn’t smooth enough, there is a bug!”
- 32. User 10,000,000 – Log Search Amazon Kinesis Amazon EC2 Event Data HTTP Request AWS Lambda Amazon Elasticsearch Service Amazon S3 bucket
- 33. User 10,000,000 – Data Architecture Amazon Kinesis Amazon S3 bucket Amazon EC2 Event Data AWS Lambda HTTP Request AWS Lambda Amazon Elasticsearch Service
- 34. If you are interested in building scalable distributed systems… We are hiring! kevin@17.media
- 35. Thank you