Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
The Rocky Road from Monolithic to Microservices Architecture
Search
cnu
November 25, 2017
Programming
0
870
The Rocky Road from Monolithic to Microservices Architecture
The explanation of our Microservices architecture and the lessons we learnt from it.
cnu
November 25, 2017
Tweet
Share
More Decks by cnu
See All by cnu
Redisconf 2018: Probabilistic Data Structures
cnu
1
800
Probabilistic Data Structures
cnu
0
500
AWS Lambda - Pycon India 2016
cnu
0
400
ZeroMQ - PyCon India 2013
cnu
2
1.4k
Other Decks in Programming
See All in Programming
Elm Form Validation
bkuhlmann
0
510
Snowflakeで眠ったデータを起こそう!
estie
0
120
Git Lint
bkuhlmann
4
750
Git Rebase
bkuhlmann
11
1.6k
Ruby GitHub Packages
bkuhlmann
0
630
Amazon SQSコンシューマー疎結合への旅 - 出張! #DevelopersIO IT技術ブログの中の人が語る勉強会 #3
quiver
0
270
Micro Frontends for Java Microservices - Devnexus 2024
mraible
PRO
0
490
What We Can Learn From OSS
inouehi
0
420
DMMプラットフォームがTiDB Cloudを採用した背景
pospome
8
4.1k
Rethinking UI building strategies @ SFI 2024
letelete
0
270
検証も兼ねて個人開発でHonoとかと向き合った話
hanetsuki
1
930
VSCodeでのDatabricks開発もお勧めしたい/I would also recommend Databricks development with VSCode.
kazumain
0
250
Featured
See All Featured
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
20
1.9k
Designing for Performance
lara
601
67k
Robots, Beer and Maslow
schacon
PRO
155
7.9k
The Invisible Side of Design
smashingmag
294
49k
What’s in a name? Adding method to the madness
productmarketing
PRO
16
2.6k
Embracing the Ebb and Flow
colly
80
4.1k
Statistics for Hackers
jakevdp
789
220k
KATA
mclloyd
15
12k
No one is an island. Learnings from fostering a developers community.
thoeni
16
2.1k
Java REST API Framework Comparison - PWX 2021
mraible
PRO
18
6.9k
Bash Introduction
62gerente
604
210k
Let's Do A Bunch of Simple Stuff to Make Websites Faster
chriscoyier
501
140k
Transcript
THE ROCKY ROAD FROM MONOLITHIC TO MICROSERVICES ARCHITECTURE
THE ROCKY ROAD FROM MONOLITHIC TO MICROSERVICES ARCHITECTURE
SRINIVASAN RANGARAJAN Head of Product Engineering
SRINIVASAN RANGARAJAN https://cnu.name Twitter: @cnu Github: @cnu
RETAIL AUTOMATION PRODUCT
Catalog & User Events Processing Recommendation
MONOLITHIC ARCHITECTURE
MONOLITHIC ARCHITECTURE Image Processing API Image Searcher File Storage
MINIMUM TWO SERVERS BEHIND ELB Load Balancer
CLOUD VS BARE METAL
EXPENSIVE
NOT REALTIME
NOT PERSONALIZABLE
API Data Store Ingestion Image Processing Image Searcher User Event
Personalization Engine
GOTHAM
API Data Store Ingestion Image Processing Image Searcher User Event
Personalization Engine
JOKER • Convert client’s catalog into one common MAD Format
• Normalization of fields and metadata • Can process batch and streaming data • Major cause of chaos in the system
GORDON • Routes the product metadata to the right micro
services • Is it a new product? or update to an existing product? • Streaming data from AWS SQS
WONDER WOMAN • Not a microservice, But a tool used
to generate rules for the catalog • Rules are send to the Image Processing microservice • Works on Samples of data and not entire dataset
WATCHTOWER • Central Source of Truth for all metadata •
Backed by an RDBMS Database (Postgresql) • Input via SQS and REST API • Output via REST API
INGESTION Gordon Joker Joker Joker Wonder Woman Watchtower Next Stage
API Data Store Ingestion Image Processing Image Searcher User Event
Personalization Engine
NIGHTWING • Computer Vision and Deep Learning Models • Convert
Image to high dimensional vectors • Tag image with visual attributes • Computer Intensive
API Data Store Ingestion Image Processing Image Searcher User Event
Personalization Engine
BATMAN • Custom very fast Vector Indexer and Search Engine
• Stores everything in memory • Two sub-parts: Indexer and Searcher • Store binary information about image in DynamoDB
API Data Store Ingestion Image Processing Image Searcher User Event
Personalization Engine
SUPERMAN • User behaviour based recommendation • Multiple products like
Collaborative filtering, Cross Product recommendation • Records every user event data and stores in a data warehouse
TWO FACE • Individual User level Personalization • Shows a
different “face” to each user • Dynamic and realtime
API Data Store Ingestion Image Processing Image Searcher User Event
Personalization Engine
FLASH • Very fast data structure storage - redis instance
• User session level history, Product Availability, etc. • Fast access, but non- expirable
GCPD • “Global Cache for Products Digested” • Rough first
level of cache for the results
API Data Store Ingestion Image Processing Image Searcher User Event
Personalization Engine
ROBIN • API Gateway for all our products • Combines
data from other micro services like Batman, Two Face, Watchtower, Superman, etc and returns JSON Response
API Data Store Ingestion Image Processing Image Searcher User Event
Personalization Engine Joker, Gordon, Wonder Woman Nightwing Batman Robin Watchtower, GCPD, Flash Superman, Two Face
LESSONS WE LEARNT
START WITH A MONOLITH. CHIP OFF PIECES AND BUILD THE
MICROSERVICES. Lesson 0
–Melvin Conway “… organizations which design systems ... are constrained
to produce designs which are copies of the communication structures of these organizations."
DEPLOY HETEROGENOUS MICROSERVICES IN A SINGLE SERVER Lesson 1
Compute Optimized Server Memory Optimized Server Nightwing Batman Robin Robin
Robin Joker Joker Joker Gordon Watch tower Watch tower Joker
IMMUTABLE MICROSERVICES Lesson 2
Constable Inspector Assistant Commissioner Commissioner
ASYNCHRONOUS IS BETTER THAN SYNCHRONOUS Lesson 3
None
NOT ALL MICROSERVICES NEED TO BE SERVERS Lesson 4
ADD REQUEST ID OR TRANSACTION ID TO DEBUG EASILY Lesson
5
GIVE A CHARACTER TO YOUR MICROSERVICES Lesson 6
None
THANK YOU
http://cnu.name/talks/ @cnu