Breakout Session
summary
Concrete claims and concrete fixes: the team scales a site to support millions of active users, handles 3B saves stored in PostgreSQL and achieves 99.999% uptime by iterating real changes — PostgreSQL 9 as primary store, Joyent Public Cloud hosting, SSD-backed replicas, memcached, HAProxy, PgBouncer, Redis and Solr/ElasticSearch for search, read-splitting and vertical sharding for the huge saves table, and moving event blobs to object storage (Manta); each change reports measurable latency, IO or replica lag improvements.
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chapters (41)
- 0:00Introduction
- 2:47Data Layer
- 3:00MongoDB
- 3:19Oracle
- 3:37PostgreSQL
- 4:29Relational Model
- 5:04Trivia
- 6:04Positives
- 6:19Scalability
- 6:46Performance
- 6:58Performance Scalability
- 7:15Whats Next
- 7:26Privacy
- 7:44Wanelo Stores
- 9:08Why not Heroku
- 9:31Foundations of a Web App
- 9:44Web Apps
- 11:12Premature Optimization
- 13:27Cheap Tricks
- 15:20CDN
- 16:13Redundancy
- 18:18Architecture
- 20:56Scaling Issues
- 22:34Downtime
- 25:40What am I waiting for
- 28:41Types of waiting
- 30:40Recipes
- 31:30Memcache
- 33:45Optimizing sequel
- 36:45Fixing slow queries
- 39:11Simple optimization
- 41:21RAM is a no brainer
- 44:07Replication
- 46:57Special Considerations
- 49:52Tracking Data
- 50:57Tuning Progress
- 52:37Skip Buffering
- 52:52Database Schema
- 53:07Vertical Sharding
- 53:27Microservices
- 53:47Horizontal sharding
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