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1
Intro
2
Outline
3
Storage stack @Pinterest
4
Why HBase ?
5
Where?
6
Personalized Feeds
7
Following Feed on HBase
8
"Misc" Challenges
9
Feeds Architecture
10
Rich Pins - 11
11
Recommendations
12
HOW?
13
MTTR - 11
14
MTTR - IV
15
Simulate, Simulate, Simulate
16
Performance
17
In the Pipeline...
18
Single Points of Failure - 11
Description:
Explore Pinterest's journey in architecting and scaling Feed storage using HBase in this 27-minute talk by software engineer Varun Sharma. Gain insights into the critical role of Feeds in user experience, the rationale behind choosing HBase, and the implementation of personalized and following feeds. Delve into various challenges faced, including rich pins, recommendations, and single points of failure. Learn about performance optimization techniques, simulation strategies, and future pipeline plans. Discover how Pinterest tackled Mean Time To Recovery (MTTR) issues and designed a robust Feeds architecture to support one of its most demanding applications.

HBase and Its Associated Services - Data@Scale

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