Scaling e-commerce and transactional systems globally
summary
OLX runs services across 40 countries, 17 brands, 300M devices and finds most ecommerce stacks are still a single monolith behind a load balancer. Practical options are clear: clone the app for quick horizontal scale, shard data per market, or split by service into microservices with independent stores — but microservices multiply storage and integration cost. OLX centralizes utility platforms like messaging and image services centralized and invests in automation, infrastructure as code and containers first, avoids touching critical legacy without experienced hands, and measures cost per transaction before big rewrites.
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chapters (46)
- 0:00Introduction
- 0:37Who is Susan Berman
- 2:02Ecommerce systems
- 2:35Ecommerce systems today
- 3:30monoliths
- 4:13my personal experience
- 4:37Scaling architecture
- 5:06Product guys
- 7:25Statistics
- 7:55Scalability
- 8:24Scale
- 8:43Overdoing
- 9:39Scaling everything
- 10:32Processes
- 11:48Problems in your system
- 12:25Overkill
- 13:11Processes should not be over
- 13:32Technology
- 13:42Getting to real stuff
- 15:11Business people dont care
- 15:35Architecture cheat list
- 16:42Agile architecture
- 19:08Trade time
- 19:18Buy vs make
- 20:15Centralization
- 20:39standardization
- 21:28ATF scale cube
- 23:13Traditional eCommerce system
- 23:32Scaling horizontally
- 25:00Sharding
- 26:20Shard in data
- 26:38Why scaling
- 27:45Shared resources
- 29:40Scaling options
- 30:28Announcing
- 32:07Scaling services
- 34:17Consistency
- 36:23Drawing boxes
- 37:10One example
- 37:49Messaging architecture
- 38:44Data lake
- 39:07Load balancer
- 39:19Image service
- 39:34Real life advice
- 41:06Automation and infrastructure
- 42:44Questions
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