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@crichardson
Events on the outside, on
the inside and at the core
Chris Richardson
Founder of the original CloudFoundry.com
Author of POJOs in Action
@crichardson
chris@chrisrichardson.net
http://plainoldobjects.com
http://microservices.io
http://eventuate.io
@crichardson
Presentation goal
How event sourcing
enables the event-driven
enterprise
@crichardson
About Chris
@crichardson
About Chris
Consultant and trainer focusing
on microservices
(http://www.chrisrichardson.net/)
@crichardson
About Chris
Founder of a startup that is creating
a platform that makes it easy for
application developers write
microservices
(http://bit.ly/trialeventuate)
@crichardson
For more information
https://github.com/cer/event-sourcing-examples
http://microservices.io
http://plainoldobjects.com/
https://twitter.com/crichardson
http://eventuate.io/
@crichardson
Agenda
Events on the outside
Events on the inside
Events at the core with event sourcing
Designing event-centric domain model
@crichardson
What’s an event?
http://www.merriam-webster.com/dictionary/event
@crichardson
Examples of events
@crichardson
Instacart:
event-
driven
grocery
shopping
Who wants to be notified?
Humans via
Email
SMS
Mobile push
…
Applications
Applications that implement
other parts of the business
process, e.g. order fulfillment
system
Analytics dashboards,
monitoring, …
Applications that deliver
notifications to humans: Twilio,
SendGrid, …
…
@crichardson
How: Polling for events
HTTP
Periodically poll for events
AtomPub
Based on HTTP
Head is constantly changing
Tail is immutable and can be efficiently cached
High-latency, inefficient
@crichardson
Using WebSockets
Browser
Web
Socket
STOMP
Client
application
Service
Web
Socket
STOMP
Application
SUBSCRIBE
MESSAGE
MESSAGE
Low latency, more efficient, but what
about past events?
@crichardson
Webhooks = user-defined
HTTP callback
Client Service
register(events, callbackUrl)
POST callbackUrl
POST callbackUrl
…
https://en.wikipedia.org/wiki/Webhook
Low latency, more efficient, but what
about past events?
@crichardson
Github webhooks
https://developer.github.com/webhooks/
Installed on an organization or repository
e.g. POST /repos/:owner/:repo/hooks
Available events:
push - push to a repository
fork - repository is forked
pull_request - assigned, unassigned, …
push - push to a repository
…
Twilio - Telephony and SMS as
a service
REST API
Allocate phone numbers
Make and receive phone calls
Send and receive SMS messages
Pay per use:
Phone calls - per-minute
SMS – per SMS sent or received
Phone number – per month
Examples
OpenVBX is a web-based, open source phone system
StubHub – notifies sellers of a pending sale via phone
SurveyMonkey – interactive polling
Salesforce – SMS-based voting for 19,000 conference
attendees
@crichardson
Using Twilio
Twilio Your
Application
TwiML doc
HTTP GET/
POST
REST API
Manage resources
Send SMS
Initiate voice calls
Webhooks handle incoming SMS and
voice calls
Voice
SMS
Phone number
SMS URL +VOICE URL
@crichardson
Integration hubs - Zapier,
IFTTT
Application abstraction:
Triggers - events published by application: polling or
Webhooks
Action - operation supported by application, e.g. REST
API end points
@crichardson
WebHooks
=
web friendly publish/subscribe
@crichardson
Enterprise integration patterns
http://www.enterpriseintegrationpatterns.com/patterns/messaging/
@crichardson
messaging system
Messaging-based IPC
Sender RecipientChannel
message
@crichardson
Example messaging systems
@crichardson
The event-driven enterprise
App A App BApp X
App Y
Firewall
Message Broker
webhooks
WebSockets
AtomPub
App Z App C
Msg
Broker
Client
Msg
Broker
Client
Msg
Broker
Client
App D
Msg
Broker
Client
Inside the firewallOutside the firewall
@crichardson
Agenda
Events on the outside
Events on the inside
Events at the core with event sourcing
Designing event-centric domain model
@crichardson
Traditional monolithic architecture
Simple to
develop
test
deploy
scale
Shopping
Cart
Customers
Orders
Mobile client
REST
API
Browser
Web
UI
Message
Broker
Adapter
MySQL
Adapter
RDBMS
…
Message Broker
@crichardson
But that leads* to
monolithic hell
For large and/or complex applications…
@crichardson
Today: use a microservice, polyglot
architecture
Orders
Customers
…
Shopping UI
Mobile Client
Browser
API Gateway
Order
management
REST
API
Customer
Management
REST
API
….
REST
API
Order
Database
(MongoDB)
MongoDB
Adapter
Customer
Database
(Sharded
MySQL)
MySQL
Adapter
@crichardson
But now we have
distributed data management
problems
@crichardson
Example: placing an order
Order Service Customer Service
Order
Database
Customer Database
Order #1
Customer #1
No 2PC
No
ACID
NoSQL SQL
@crichardson
Customer management
How to maintain invariants?
Order management
Order Service
placeOrder()
Customer Service
updateCreditLimit()
Customer
creditLimit
...
has ordersbelongs toOrder
total
Invariant:
sum(open order.total) <= customer.creditLimit
?
@crichardson
Use an event-driven
architecture
Services publish events when something important happens,
e.g. state changes
Services subscribe to events and update their state
Maintain eventual consistency across multiple aggregates
(in multiple datastores)
Synchronize replicated data
@crichardson
Event-driven application architecture
Application
Service A Service B
Message Broker
Service C
Msg
Broker
Client
Msg
Broker
Client
Msg
Broker
Client
Service D
Msg
Broker
Client
@crichardson
Order Management
Order
id : 4567
total: 343
state = CREATED
Customer Management
Customer
creditLimit : 12000
creditReservations: {}
Customer
creditLimit : 12000
creditReservations: { 4567 -> 343}
Order
id : 4567
total: 343
state = OPEN
Eventually consistent credit checking
Message Bus
createOrder()
Publishes:
Subscribes to:
Subscribes to:
publishes:
OrderCreatedEvent
CreditReservedEvent
OrderCreatedEvent CreditReservedEvent
@crichardson
Now there are two problems
to solve….
@crichardson
Problem #1: How to design
eventually consistent business logic?
More on that later….
@crichardson
Problem #2: How to atomically update
database and publish an event
Order Service
Order
Database
Message Broker
insert Order
publish
OrderCreatedEvent
dual write problem
?
@crichardson
Update and publish using
2PC
Guaranteed atomicity BUT
Need a distributed transaction manager
Database and message broker must support 2PC
Impacts reliability
Not fashionable
2PC is best avoided
@crichardson
Transaction log tailing
How:
Read the database “transaction log” = single source of truth
Publish events to message broker
LinkedIn databus https://github.com/linkedin/databus
Supports Oracle and MySQL
Publish as events
AWS DynamoDB streams
Ordered sequence of creates, updates, deletes made to a DynamoDB table
Last 24 hours
Subscribe to get changes
MongoDB
Read the oplog
Transaction log tailing: benefits
and drawbacks
Benefits
No 2PC
No application changes
required
Guaranteed to be
accurate
Drawbacks
Immature
Database specific
solutions
Low-level DB changes
rather business level
events = need to reverse
engineer domain events
@crichardson
Use database triggers
Track changes to tables
Insert events into an event table
Use datastore as a message queue
Pull events from event table and write to message broker
Database triggers: benefits
and drawbacks
Benefits
No 2PC
No application changes
required

Drawbacks
Requires the database to
support them
Database specific solutions
Low-level DB changes rather
business level events = need
to reverse engineer domain
events
Error-prone, e.g. missing
trigger
@crichardson
Application created events
Use datastore as a message queue
Txn #1: Update database: new entity state & event
Txn #2: Consume event
Txn #3: Mark event as consumed
Eventually consistent mechanism (used by eBay)
See BASE: An Acid Alternative, http://bit.ly/ebaybase
Application created events
Benefits
High-level domain events
No 2PC
Drawbacks
Requires changes to the
application
Only works for SQL and
some NoSQL databases
Error-prone
@crichardson
Agenda
Events on the outside
Events on the inside
Events at the core with event sourcing
Designing event-centric domain model
@crichardson
Just publish events
Application
Database
Message Broker
update
publish
X
@crichardson
Event sourcing
For each aggregate (business entity):
Identify (state-changing) domain events
Define Event classes
For example,
ShoppingCart: ItemAddedEvent, ItemRemovedEvent,
OrderPlacedEvent
Order: OrderCreated, OrderCancelled, OrderApproved,
OrderRejected, OrderShipped
@crichardson
Persists events
NOT current state
Order
status
….
Event table
101 ACCEPTED
Order table
X
OrderCreated101 901 …
OrderApproved101 902 …
OrderShipped101 903 …
@crichardson
Replay events to recreate
state
Order
state
OrderCreated(…)
OrderAccepted(…)
OrderShipped(…)
Events
Periodically snapshot to avoid loading all events
@crichardson
The present is a fold over
history
currentState = foldl(applyEvent, initialState, events)
@crichardson
Domain logic = event-driven
aggregates
Customer
AggregateOrder
Aggregate
Order Created
Event Check Credit
Command
Credit Reserved
Event
Approve Order
Command
Create Order
Command
External
request
Emits events Event Command
@crichardson
Request handling in an event-sourced application
HTTP
Handler
Event
Store
pastEvents = findEvents(entityId)
Order
new()
applyEvents(pastEvents)
newEvents = processCmd(SomeCmd)
saveEvents(newEvents)
Microservice A
(optimistic locking)
@crichardson
Event Store publishes events -
consumed by other services
Event
Store
Event
Subscriber
subscribe(EventTypes)
publish(event)
publish(event)
Aggregate
CQRS View
update()
update()
Microservice B
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 sourcing
Solves 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
@crichardson
Drawbacks of event sourcing
Weird and unfamiliar
Events = a historical record of your bad design decisions
Handling duplicate events can be tricky
Application must handle eventually consistent data
Event store only directly supports PK-based lookup => use
Command Query Responsibility Segregation (CQRS) to handle
queries
@crichardson
Agenda
Events on the outside
Events on the inside
Events at the core with event sourcing
Designing event-centric domain model
@crichardson
Use the familiar building
blocks of DDD
Entity
Value object
Services
Repositories
Aggregates ⟸ essential
Aggregate design
Graph consisting of a root
entity and one or more other
entities and value objects
Each core business entity =
Aggregate: e.g. customer,
Account, Order, Product, ….
Reference other aggregate
roots via primary key
Often contains partial copy
of other aggregates’ data
Order
OrderLine
Item
quantity
productId
productName
productPrice
customerId
Address
street
city
…
@crichardson
Partition the domain model
into Aggregates
Order
OrderLine
Item
quantity
…
Address
street
city
…
Customer
Product
name
price
@crichardson
Transaction = processing one
command by one aggregate
No opportunity to update multiple aggregates within a
transaction
Aggregate granularity is important
If an update must be atomic (i.e. no compensating
transaction) then it must be handled by a single aggregate
e.g. scanning boarding pass at security checkpoint or when
entering jetway
@crichardson
Aggregate granularity
Consistency
Scalability/
User experience
Customer
Order
Product
Customer
Order
Product
Customer
Order
Product
Designing domain events
Record state changes for an
aggregate
Part of the public API of the domain
model ProductAddedToCart
id : TimeUUID
senderId: UUID
productId
productName
productPrice
…
Required by
aggregate
Enrichment:
Useful for
consumers
Event
metadata
@crichardson
Example event
@crichardson
Designing commands
Created by a service from incoming request
Processed by an aggregate
Immutable
Contains value objects for
Validating request
Creating event
Auditing user activity
@crichardson
Example command
@crichardson
Hybrid OO/FP domain objects
@crichardson
OO = State + Behavior
creditLimit
creditReservations : Map[OrderId, Money]
Customer
List<Event> processCommand (
Command aCommand) { … }
void applyEvent (Event anEvent) { … }
State
Behavior
@crichardson
Aggregate traits
Map Command to Events
Apply event returning
updated Aggregate
Used by
Event Store
to
reconstitute
aggregate
@crichardson
ReflectiveMutableCommand
ProcessingAggregate
@crichardson
Customer - command processing
@crichardson
Customer - applying events
@crichardson
Event Store API
T is a subclass of Aggregate[T]
Rx Observable = Future++
@crichardson
Creating an order
save() concisely specifies:
1.Creates Customer aggregate
2.Processes command
3.Applies events
4.Persists events
@crichardson
Event handling in Customers
1.Load Customer aggregate
2.Processes command
3.Applies events
4.Persists events
Triggers BeanPostProcessor
Durable subscription name
@crichardson
Summary
Events are a central to modern applications
Events integrate applications
Events maintain data consistency in a microservices
architecture
Build events into the core of your application using event
sourcing
@crichardson
@crichardson chris@chrisrichardson.net
http://plainoldobjects.com http://microservices.io
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