developing event-driven microservices with event sourcing and cqrs (london java community)
TRANSCRIPT
@crichardson
Event-driven microservices with event sourcing and CQRS
Chris Richardson
Founder of Eventuate.io Founder of the original CloudFoundry.com Author of POJOs in Action
@crichardson [email protected] http://eventuate.io
@crichardson
Presentation goal
Show how Event Sourcing and Command Query Responsibility
Segregation (CQRS) are a great way to implement
microservices
@crichardson
About Chris
@crichardson
About Chris
Consultant and trainer focusing on modern
application architectures including microservices
(http://www.chrisrichardson.net/)
@crichardson
About Chris
Founder of a startup that is creating a platform that makes it easier for developers to write transactional
microservices (http://eventuate.io)
@crichardson
For more information
http://learnmicroservices.io
@crichardson
Agenda
Monolith vs. microservices
Event-driven microservices
Overview of event sourcing
Implementing queries in an event sourced application
@crichardson
Let’s imagine you are building a large, complex application,
e.g. an online store
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Successful software development
Architecture
Process OrganizationAgile Continuous delivery …
Small, autonomous, teams
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?Architecture
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@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
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But successful
applications keep
growing ….
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Monolithic architecture
Process OrganizationAgile Continuous delivery …
Small, autonomous, teams
@crichardson
Apply functional decomposition
X axis - horizontal duplication
Z axis
- data
partit
ioning
Y axis - functional
decomposition
Scale b
y split
ting s
imilar
thing
s
Scale by splitting
different things
@crichardson
Microservice architecture
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
REST
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Microservice architecture
Process OrganizationAgile Continuous delivery …
Small, autonomous, teams✔ ✔
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Drawbacks
Complexity
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DrawbacksComplexity of developing a distributed system
Implementing inter-process communication
Handling partial failures
Complexity of implementing business transactions that span multiple databases (without 2PC)
Complexity of testing a distributed system
Complexity of deploying and operating a distributed system
Managing the development and deployment of features that span multiple services
Fortunately solutions exists
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The benefits typically outweigh the drawbacks
for large, complex applications
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Issues to address
How to deploy the services?
How do the services communicate?
How do clients of the application communicate with the services?
How to partition the system into services?
How to deal with distributed data management problems?
….
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Agenda
Monolith vs. microservices
Event-driven microservices
Overview of event sourcing
Implementing queries in an event sourced application
Data management patterns
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The Database
Shared database
Order Service Customer Service … Service
Order table Customer table …
orderTotal creditLimit
Tight coupling Simple and
ACID
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Database per service
Order Service Customer Service
Order Database Customer Database
Order table Customer table
orderTotal creditLimit
Loose coupling 😀 but more complex 😓 and….
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2PC (aka. distributed transactions)
is not viable choice for most modern applications
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Customer management
How to maintain data consistency without 2PC?
Order management
Order Service
placeOrder()
Customer Service
updateCreditLimit()
Customer
creditLimit ...
has ordersbelongs toOrder
total
Invariant: sum(open order.total) <= customer.creditLimit
?
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Event-driven architecture
@crichardson
Use event-driven, eventually consistent order processing
Order Service
Customer Service
Order created
Credit Reserved
Credit Check Failed
Place Order
OR
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How atomically update database and publish an event
Order Service
Order Database
Message Broker
insert Order
publish OrderCreatedEvent
dual write problem
?
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Failure = inconsistent system
Order Service
Order Database
Message Broker
insert Order
publish OrderCreatedEvent
X
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2PC is not an option
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Reliably publish events when state changes
@crichardson
Agenda
Monolith vs. microservices
Event-driven microservices
Overview of event sourcing
Implementing queries in an event sourced application
@crichardson
Just publish events
Application
Database
Message Broker
update
publish
X
@crichardson
Event sourcingFor each domain object (i.e. DDD aggregate):
Identify (state changing) domain events, e.g. use Event Storming
Define Event classes
For example,
ShoppingCart: ItemAddedEvent, ItemRemovedEvent, OrderPlacedEvent
Order: OrderCreated, OrderCancelled, OrderApproved, OrderRejected, OrderShipped
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Persists events NOT current state
Order
status ….
101 ACCEPTED
Order tableX
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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
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Replay events to recreate state
Order
state
OrderCreated(…) OrderAccepted(…) OrderShipped(…)
Events
Periodically snapshot to avoid loading all events
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The present is a fold over history
currentState = foldl(applyEvent, initialState, events)
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Familiar concepts restructured
class Customer {
public void reserveCredit( orderId : String, amount : Money) {
// verify
// update state this.xyz = … }
public List<Event> process( ReserveCreditCommand cmd) { // verify … return singletonList( new CreditReservedEvent(…); ) }
public void apply( CreditReservedEvent event) { // update state this.xyz = event.xyz }
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Event
Aggregates: Command ⇒ Events
AggregateCommand Event
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Aggregates: Event ⇒ Updated aggregate
AggregateEvent Updated Aggregate
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Request handling in an event sourced application
HTTP Handler
Event Store
pastEvents = findEvents(entityId)
Order
new()
applyEvents(pastEvents)
newEvents = processCmd(someCmd)
saveEvents(newEvents) (optimistic locking)
Order Service
applyEvents(newEvents)
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Event Store publishes events consumed by other services
Event Store
Event Subscriber
subscribe(EventTypes)
publish(event)
publish(event)
Customer
update()
Customer Service
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Event Store publishes events consumed by other services
Event Store
Event Subscriber
subscribe(EventTypes)
publish(event)
publish(event)
CQRS View
update()
Service Xyz
send notifications
…
Event store = database + message broker
Hybrid database and message broker
Implementations:
Home grown/DIY
geteventstore.com by Greg Young
http://eventuate.io (mine)
Event Store
Save aggregate
events
Get aggregate
events
Subscribe to events
@crichardson
Benefits of event sourcingSolves data consistency issues in a Microservice/NoSQL based architecture
Reliable event publishing: publishes events needed by predictive analytics etc, user notifications,…
Eliminates O/R mapping problem (mostly)
Reifies state changes:
Built in, reliable audit log
temporal queries
Preserved history ⇒ More easily implement future requirements
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Drawbacks of event sourcingRequires application rewrite
Weird and unfamiliar style of programming
Events = a historical record of your bad design decisions
Must detect and ignore duplicate events
Idempotent event handlers
Track most recent event and ignore older ones
…
Querying the event store can be challenging
Some queries might be complex/inefficient, e.g. accounts with a balance > X
Event store might only support lookup of events by entity id
Must use Command Query Responsibility Segregation (CQRS) to handle queries ⇒ application must handle eventually consistent data
@crichardson
Agenda
Monolith vs. microservices
Event-driven microservices
Overview of event sourcing
Implementing queries in an event sourced application
@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
@crichardson
Use Command Query Responsibility Segregation
(CQRS)
@crichardson
Command Query Responsibility Segregation (CQRS)
Application logic
Commands Queries
X
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Command Query Responsibility Segregation (CQRS)
Command side
Commands
Aggregate
Event Store
Events
Query side
Queries
(Materialized) View
Events
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Query side design
Event Store
Updater
View Updater Service
Events
Reader
HTTP GET Request
View Query Service
View Store
e.g. MongoDB
ElasticSearch Neo4J
update query
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Persisting a customer and order history in MongoDB
{ "_id" : "0000014f9a45004b 0a00270000000000", "_class" : "net.chrisrichardson…..views.orderhistory.CustomerView", "version" : NumberLong(5), "orders" : { "0000014f9a450063 0a00270000000000" : { "state" : "APPROVED", "orderId" : "0000014f9a450063 0a00270000000000", "orderTotal" : { "amount" : "1234" } }, "0000014f9a450063 0a00270000000001" : { "state" : "REJECTED", "orderId" : "0000014f9a450063 0a00270000000001", "orderTotal" : { "amount" : "3000" } } }, "name" : "Fred", "creditLimit" : { "amount" : "2000" } }
Denormalized = efficient lookup
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Persisting customers and order info using Spring Data for MongoDB...
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Persisting customers and order using Spring Data for MongoDB...
Benefits and drawbacks of CQRS
Benefits
Necessary in an event sourced architecture
Separation of concerns = simpler command and query models
Supports multiple denormalized views
Improved scalability and performance
Drawbacks
Complexity
Potential code duplication
Replication lag/eventually consistent views
@crichardson
Summary
Use microservices to accelerate development
Use an event-driven architecture to maintain data consistency
Implement an event-driven architecture using event sourcing
Use CQRS to implement materialized views for queries
