Events on the outside, on the inside and at the core - Chris Richardson
1. @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
5. @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)
11. 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, …
…
12. @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
14. @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?
16. 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
18. @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
23. @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
24. @crichardson
Agenda
Events on the outside
Events on the inside
Events at the core with event sourcing
Designing event-centric domain model
27. @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
29. @crichardson
Example: placing an order
Order Service Customer Service
Order
Database
Customer Database
Order #1
Customer #1
No 2PC
No
ACID
NoSQL SQL
30. @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
?
31. @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
33. @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
36. @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
?
37. @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
38. @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
39. 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
40. @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
41. 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
42. @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
46. @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
47. @crichardson
Persists events
NOT current state
Order
status
….
Event table
101 ACCEPTED
Order table
X
OrderCreated101 901 …
OrderApproved101 902 …
OrderShipped101 903 …
48. @crichardson
Replay events to recreate
state
Order
state
OrderCreated(…)
OrderAccepted(…)
OrderShipped(…)
Events
Periodically snapshot to avoid loading all events
50. @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
51. @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)
52. @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
…
53. 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
54. @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
55. @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
56. @crichardson
Agenda
Events on the outside
Events on the inside
Events at the core with event sourcing
Designing event-centric domain model
57. @crichardson
Use the familiar building
blocks of DDD
Entity
Value object
Services
Repositories
Aggregates ⟸ essential
58. 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
…
59. @crichardson
Partition the domain model
into Aggregates
Order
OrderLine
Item
quantity
…
Address
street
city
…
Customer
Product
name
price
60. @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
62. 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
64. @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
74. @crichardson
Event handling in Customers
1.Load Customer aggregate
2.Processes command
3.Applies events
4.Persists events
Triggers BeanPostProcessor
Durable subscription name
75. @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