1. overall
1.1. bottom - platform
1.1.1. infrastructure and storage
1.1.2. logging
1.1.3. app provisioning
1.1.4. routing and service discovery
1.1.5. development and deploy
1.1.6. languages
1.1.7. testing
1.1.7.1. octopus
1.1.8. reliability
1.1.9. map
1.2. middle - marketplace
1.2.1. high available, self-healing, persistent
1.2.2. speed and throughput
1.2.3. optimizing and balancing
1.2.4. seeing and using data
1.3. top - web and mobile
1.3.1. web
1.3.2. mobile
2. unique techs
2.1. database
2.1.1. original arch
2.1.1.1. initial arch
2.1.1.1.1. Untitled
2.1.1.2. tech stack
2.1.1.2.1. python
2.1.1.2.2. ORM layer - SQLAlchemy
2.1.1.2.3. PostgreSQL
2.1.2. separate trip data
2.1.2.1. trip data problem
2.1.2.1.1. percentage
2.1.2.1.2. fastest growing
2.1.2.1.3. most IOPS
2.1.2.2. evaluate existing products
2.1.2.2.1. not confident good fit
2.1.2.3. schemaless
2.1.2.3.1. def
2.1.2.3.2. requirements
2.1.2.3.3. challenges during the process
2.1.2.3.4. resulting arch
2.1.3. transit from postgres to mysql
2.1.3.1. postgres
2.1.3.1.1. architectures
2.1.3.1.2. problems
2.1.3.2. mysql
2.1.3.2.1. architecture
2.1.4. Schemaless
2.1.4.1. def
2.1.4.1.1. database sharing layer built on top of MySQL
2.1.4.2. architecture
2.1.4.3. data model
2.1.4.3.1. example
2.1.4.3.2. trip data model
2.1.4.4. features
2.1.4.4.1. triggers
2.1.4.4.2. indexes
2.1.4.5. encoding
2.2. ETA & efficient route
2.3. ringpop
3. big data analytics
3.1. overview
3.1.1. Untitled
3.2. data ingestion
3.2.1. overview
3.2.1.1. Untitled
3.2.2. sources
3.2.2.1. kafka
3.2.2.2. SOA database tables
3.2.2.3. schemaless
3.2.3. streamific
3.2.3.1. Apache Helix
3.2.3.2. Akka
3.3. kafka
3.3.1. overview
3.3.1.1. Untitled
3.3.2. mirrormaker limitations at uber
4. microservices
4.1. moving to SOA
4.1.1. tech stack