The document discusses the advantages of microservices architecture over monolithic architecture, emphasizing faster development, easier scaling, and the ability to use various technologies. It outlines the role of Redis in caching, messaging, and maintaining data consistency through event-driven models, particularly in inter-service communication. The document suggests organizing teams around microservices and utilizing event sourcing and CQRS for efficient data management.

1. Microservices and Redis
Chris Richardson
Founder of Eventuate.io
Founder of the original CloudFoundry.com
Author of POJOs in Action
@crichardson
chris@chrisrichardson.net
http://eventuate.io

2. @crichardson
About Chris

3. @crichardson
Why microservices?

4. @crichardson
The monolithic architecture
Tomcat
Browser
WAR
SQL
database
HTML
REST/JSON
Client
App
Simple to ….
Develop
Test
Deploy
Scale
Catalog
Module
Reviews
Module
Orders
Module
StoreFront UI
Module

5. @crichardson
But successful
applications
keep growing
….
Eventually, agile
development
and
deployment
becomes
impossible

6. @crichardson
Microservice architecture = functional
decomposition
Browser
Mobile
Device
Store
Front UI
API
Gateway
Catalog
Service
Review
Service
Order
Service
…
Service
Catalog
Database
Review
Database
Order
Database
…
Database
HTML
REST
REST

7. @crichardson
Develop and deploy faster

8. @crichardson
Scale more easily

9. @crichardson
Pick the best technology

10. @crichardson
Microservices are not a free lunch
BUT
for most large, complex applications are good
choice

11. @crichardson
Where does Redis fit in?

12. Using Redis within a service
Caching
High performance messaging
High performance database
Catalog
Service
Catalog
DB

13. @crichardson
Using Redis for inter-service communication
API
Gateway
Catalog
Service
Review
Service
…
Service
Pub/Sub
Need Product
Details X
GET /product/X
Need … Need … Need …Info Info Info

14. @crichardson
Redis and the API Gateway
API
Gateway
Caching
Rate limiting
Routing

15. @crichardson
How to maintain data consistency?

16. @crichardson
Database per service
Catalog
Service
Review
Service
Order
Service
…
Service
Catalog
Database
Review
Database
Order
Database
…
Database
How to maintain data
consistency without
2PC?

17. @crichardson
Customer DB
How to maintain data consistency without
2PC?
Order DB
Order Service
placeOrder()
Customer Service
updateCreditLimit()
Customer
creditLimit
...
has ordersbelongs toOrder
total
Invariant:
sum(open order.total) <= customer.creditLimit
?

18. @crichardson
Use event-driven, eventually consistent order
processing
Order
Service
Customer
Service
Order created
Credit Reserved
Credit Check Failed
Place Order
OR

19. @crichardson
How to atomically update database and
publish an event without 2PC?
Order Service
Order
Database
Message Broker
insert Order
publish
OrderCreatedEvent
dual write problem
?

20. @crichardson
Use event sourcing
Order Service
Order
Database
Event Store
insert Order
Save
OrderCreatedEvent
X
Persistence
and notification

21. @crichardson
Event sourcing: persists events
NOT current state
Event table
Entity type
Event
id
Entity
id
Event
data
Order 902101 …OrderApproved
Order 903101 …OrderShipped
Event
type
Order 901101 …OrderCreated Order
state
total
Replay

22. @crichardson
How to implement queries?

23. @crichardson
Find recent, valuable customers
SELECT *
FROM CUSTOMER c, ORDER o
WHERE
c.id = o.ID
AND o.ORDER_TOTAL > 100000
AND o.STATE = 'SHIPPED'
AND c.CREATION_DATE > ?
Customer Service
Order Service
What if event
sourcing is used?
…. is no longer easy

24. @crichardson
Command Query Responsibility Segregation
(CQRS)
Command side
Commands
Aggregate
Event Store
Events
Query side
Queries
Materialized
View
Events
POST
PUT
DELETE GET

25. @crichardson
Food to Go example - on github.com
http://bit.ly/redis-pia
94619:Monday [0700_2:1430, 1130_1:1430, ...]
94619:Tuesday [0700_2:1430, 1130_1:1430, ...]
… …
Restaurant
View
Updater
Service
Restaurant
View
Query
Service
ZRANGEBYSCORE
Event Store
Restaurant
events Materialized view of
restaurant locations
and opening hours
GET
available
restaurants
ZADD
ZREM
Sorted sets

26. @crichardson
Summary
Organize into small, agile, autonomous teams responsible for one or more
microservices
Use an event-driven architecture, based on event sourcing and CQRS
Use Redis throughout a microservices architecture

27. Thank you!
@crichardson
http://eventuate.io