The "Why", "What" & "How" of Microservices - short version

The “Why”, “What” and
of Microservices
Jeppe Cramon - @jeppec
Chief Architect - INPAY
“How”

WHY WOULD WE WANT TO USE
MICROSERVICES?

Most feel stuck with a monolith
and are look for a way out
“The” DB
UI
Logic
Data Access

Microservices promise a solution to our problem
Monolith
Microservice Microservice
Microservice MicroserviceMicroservice
Microservice
Microservice

Microservices as an architectural style
5

ARCHITECTURE IS ESSENTIAL
Because it influences how fast we can respond to changes
and what the cost of those changes are

ULTIMATELY WE WANT TO BE
ABLE TO ADAPT TO CHANGES IN
A CONSTANT AMOUNT OF TIME

E.G. IF YOUR PRICING MODEL WAS
WRONG – YOU SHOULD BE ABLE
TO CHANGE AND REDEPLOY IT IN
HOURS/DAYS

SOME ORGANIZATIONS
CALCULATE CHANGE TIMES IN
MONTHS OR YEARS

WE ALL WANT TO MOVE FAST
But can’t always move fast -
for various reasons…

THE MAIN MAIN IMPEDIMENT
TO OBTAINING HIGH VELOCITY
IS

Coupling causes ripple effect –
much like circles in the water
• You want to change a little thing and all of a sudden you need to change 25
other seemingly unrelated things
• Zero coupling is impossible
• Question is what is the right level of coupling?
• This highly depends on how likely the component/system/service is to change and what
parts that change together

The playing field
Zero coupling The monolith (an indivisible unit)

It usually starts simple
“The” DB
UI
Logic
Data Access

Next step is spaghetti in layers

And finally we end up with a
Big Ball Of Mud

MICROSERVICES TELL US TO MAKE
THINGS SMALLER
Adhering to the Single Responsibility Principle (SRP) –
“A Microservice should have one reason – and only one reason – to change”

THERE IS VALUE IN MAKING
THINGS SMALLER
For one thing it is easier to reason about them in isolation
It’s easier to replace them – since coupling is explicit

HOW SMALL SHOULD A
MICROSERVICE BE?

BUT I’VE HEARD THAT A
“MICROSERVICE SHOULD BE NO
LARGER THAN 100 LINES OF CODE!?”

SIZE THIS AND SIZE THAT!
BE CAREFUL
If Microservices are good, then Nanoservices must be even
better?
Why not one-liner services?

AKA SERVERLESS
23
https://www.linkedin.com/pulse/how-i-decided-use-serverlessnanoservices-architecture-benefield

AKA SERVERLESS
24
https://www.linkedin.com/pulse/how-i-decided-use-serverlessnanoservices-architecture-benefield

Nano Services
Unless we have a very good reason for doing so,
we risk building services
that are so fine-grained
that their costs outweigh their utility*
*Read Arnon Rotem-Gal-Oz’s Nano Services Anti Pattern:http://arnon.me/wp-content/uploads/2010/10/Nanoservices.pdf

IS YOUR MICROSERVICE
VALUABLE?
The value of a microservice must
exceed the cost of building &
operating it.
Microservices entail costs for serializations, deserializations,
security, communication, maintenance, configuration,
deployment, monitoring, etc.

Let’s transform our monolith to microservices
“The” DB
UI
Logic
Microservices
Data Access
Microservices
UI-3
MS-3
MS-C
UI-2
MS-D
UI-4
MS-4MS-2
MS-B MS-E
UI-1 UI-5
MS-5MS-1
MS-A

BEWARE…
When we break up big things into small
pieces we invariably push the complexity to
their interaction.
Michael Feathers
https://michaelfeathers.silvrback.com/microservices-until-macro-complexity

Let’s zoom in on the data tier
MS-A
“The” DB
MS-C
MS-D
MS-B
MS-E

IF OUR MONOLITHS CODE IS COUPLED AND MESSY
Chances are that the data(base) model is equally coupled
and messy

It gets more and more complicated

AND WE END UP WITH
ONE DOMAIN MODEL TO RULE THEM ALL

THE MENTAL CAPACITY REQUIRED TO
UNDERSTAND THIS DOMAIN MODEL
IS HUGE

TO UNDERSTAND ANY PART IN
ISOLATION, REQUIRES YOU TO
UNDERSTAND THE ENTIRE MODEL -
AS EVERYTHING IS COUPLED TO EACH
OTHER

Side effect: Our queries get messy

SOA PRINCIPLE
SERVICES ARE AUTONOMOUS
Autonomy means that our service is independent and self-
contained and as far as possible doesn’t directly depend on
other services to be functional.

Service autonomy
Component
B
Component
C
Component
A
System X
Service
A
Component
B
Component
C
System X
Slow/unreliable network
Different SLA
Slow system

For a service to be autonomous is MUST own its data
Shipping
DB

For a service to be autonomous is must NOT share state

Autonomy is essential for
Scalability (scale out clustering)
Reliability (fail over clustering)

Autonomy is essential for
Reusability
Adaptability

Let’s refactor the data tier
MS-C
MS-D
MS-B
MS-E
MS-A A’s
DB
B’s
DB
C’s
DB
D’s
DB
E’s
DB
UI
Logic
Microservices
Data Access
Microservices
UI-3
MS-3
MS-C
UI-2
MS-D
UI-4
MS-4MS-2
MS-B MS-E
UI-1 UI-5
MS-5MS-1
MS-A
A’s
DB
B’s
DB
C’s
DB
D’s
DB
E’s
DB

THIS IS ALSO KNOWN AS A
DISTRIBUTED MONOLITH

Things that are not Services
• A Service with only functionality (and no data) is a FUNCTION
• Like: check if order is valid
• A Service that only has data is a DATABASE
• Like: Entity CRUD
• A database already has a nice API - we don’t need to bubble wrap it with REST or Asynchronous messages
• Don’t split the atom – we need cohesion as well as decoupling!
• If we want datastore abstraction (so we can swap out Postgresql with Mongo or Redis) there this little
pattern called Respository.
This is typically seen in a lot of layered SOA usages where a function calls a
function that calls a function that calls a database

Let’s refactor the “microservices”
UI
Microservices
UI-3
MS-3
UI-2 UI-4
MS-4MS-2
UI-1 UI-5
MS-5MS-1
1’s
DB
2’s
DB
3’s
DB
4’s
DB
5’s
DB

SRP
What about cross Service relationships?
Customer Orders
Products

Microservices == distributed objects?
Service star chart

Reality rears it’s ugly head

WHAT’S WRONG WITH USING
RPC/REST/… BETWEEN
SERVICES?

Synchronous calls lower our tolerance for faults
• When you get an IO error
• When servers crash or restarts
• When databases are down
• When deadlocks occurs in our databases
• Do you retry?
With synchronous style Service interaction we can loose business data, there’s no automatic retry or we risk creating
data more than once because idempotence* often is an after though
53
Client Server
Duplicated
Response
Duplicated Request
Processing
Response
Request Processing
The same message can be
processed more than once
*Idempotence describes the quality of an
operation in which result and state does not
change if the operation is performed more
than 1 time

Also remember: REST isn’t magic!

WITH CROSS SERVICE INTEGRATION
WE’RE BOUND BY THE LAWS OF
DISTRIBUTED COMPUTING

The 8 Fallacies of Distributed Computing
These fallacies are assumptions architects, designers and developers of
distributed systems are likely to make. The fallacies will be proven
wrong in the long run - resulting in all sorts of troubles and pains for
the solution and architects who made the assumptions.
1. The network is reliable.
2. Latency is zero.
3. Bandwidth is infinite.
4. The network is secure.
5. Topology doesn't change.
6. There is one administrator.
7. Transport cost is zero.
8. The network is homogeneous.
See http://www.rgoarchitects.com/Files/fallacies.pdf for a walkthrough of the fallacies and why they’re fallacies

A DISTRIBUTED SYSTEM IS ONE
WHERE A MACHINE I’VE NEVER
HEARD OF CAN CAUSE MY PROGRAM
TO FAIL.
— Leslie Lamport

Essential complexity of 2 way integration
Component
C
Component
B
Component
A
UI
Service Service
B:Service()
call C:Service()
call A:Service()
commit()
Service
Local transaction
between System A, B
and C

B:Service()
call C:Service()
call A:Service()
if (A:Call-Failed:Too-Busy?)
Wait-A-While()
call A:Service()
if (A:Call-Failed:Too-Busy?)
Wait-A-Little-While-Longer()
call A:Service()
if (A:Call-Failed:IO-Error?)
Save-We-Need-Check-If-Call-A-Succeded-After-All
AND We-Need-To-Retry call C:Service and call B:Service
AND Tell-Customer-That-This-Operation-Perhaps-Went-Well
if (A:Call-Went-Well?)
commit()
Accidental complexity from distributed service integration
Component
C
Component
B
System A
UI
Service Service Service
Local transaction
between System B and
C

Consequence: Availability goes down
(without additional instances of each service)
Service
A
Service
B
Service
C
Availability: 99% Availability: 99% Availability: 99%
Combined availability: 97%

DECIDE IF YOU CAN LIVE WITH THE
CONSEQUENCES OF COUPLING
SERVICES TO EACH OTHER USING
REQUEST/RESPONSE
Different situations – different tradeoffs

HOW CAN WE BUILD SERVICES THAT
DON’T EXPERIENCE THESE
PROBLEMS?

GUIDANCE CAN BE FOUND IN
Pat Hellands
“Life Beyond Distributed Transactions? An Apostate ‘s Opinion”
Link: http://www-db.cs.wisc.edu/cidr/cidr2007/papers/cidr07p15.pdf

Life Beyond Distributed Transactions?
According to Pat Helland, we must find the solution to our problem by looking
at:
1. How do we split our data / services
2. How do we identify our data
3. How do we communicate between our services

1. How do we split our data / services
Data must be collected in pieces called aggregates. These aggregates should
be limited in size (but not smaller), so that, after a transaction they are
consistent.
Rule of thumb:
One transaction involves only one aggregate.

DOMAIN DRIVEN DESIGN
The term Aggregate comes from DDD

Aggregates
Invoice
InvoiceLine
*
Account *
What:
• Cluster coherent Entities and Value Objects,
with complex associations into Aggregates
with well defined boundaries.
• Choose one entity to be root and control
access to objects inside the boundary
through the root.
Motivation:
Control invariants and consistency through the aggregate root.
Enables: Loading schemes, coarse grained locking and…
Ensuring consistency & transactional boundaries for Distributed
scenarios
Root
*
*

THE SMALLEST SERVICE
Would be responsible for all logic and data related to a single
Aggregate

WHY?
Because consistency can only be guaranteed within an Aggregate
It cannot span aggregates - due to lack of coordinating transactions

Example of bad aggregate boundaries

RULE OF THUMB
1 use case = 1 transaction = 1 aggregate

2. How do we identify our data
According to Pat Helland we need to be able to uniquely identify each
Aggregate using an ID.
• This ID will usually a UUID/GUID
• Aggregates refer to each other by their ID
• they NEVER use memory pointers, join tables or remote calls
{21EC2020-3AEA-4069-A2DD-08002B30309D}
2122 (approximately 5.3×1036) combinations

WE STILL HAVEN’T CONQUERED
THE TEMPORAL COUPLING
PROBLEM

3. How we communicate between our services
• What do we do when our use case involves more than one aggregate and
therefore likely more than one service?

Synchronous calls are the crystal meth of programming
At first you make good progress but then the sheer horror
becomes evident when you realise the scalability
limitations and how the brittleness holds back both
performance and development flexibility. By then it is too
late to save.
http://www.infoq.com/news/2014/10/thompson-reactive-manifesto-2
We need the reactive properties and then apply
protocols for the message interactions. Without
considering the protocols of interaction this world
of micro-services will become a coordination
nightmare.
Martin Thompson

IF WE WANT TO DECOUPLE OUR SERVICES AS MUCH
AS POSSIBLE
THEN WE NEED TO LOOK TOWARDS
COMPOSITE UI’S
AND
EVENTS

WHAT’S A COMPOSITE UI
A Composite UI is a way to allow different services to
participate an applications UI without revealing their
internals and thereby removing the need for other
services to know the this services internal data
This helps us keep coupling low and encapsulation high

Applications and Services
iOS Homebanking Call center support portal
Bank Backoffice application
Customer information service
Legal and contract information service
Accounts service
Credit card service
Mortgage loans service

Who owns the UI?
• For a service to be fully autonomous
is must be self contained – which
means it must:
• Own its UI
• Own its Business Logic
• Own its Data model
User interface
Business Logic
Data model &
storage
Service
A similar approach is available under the name Self Contained Systems http://scs-architecture.org/

If a Service doesn’t own its UI we often find the need for
a Gateway or Backend For a Frontend (BFF)
• Experience shows if you get
your Service API wrong the
first time around, it is really
expensive to fix it*
• The granularity of APIs
provided by microservices is
often different than what a
client needs*
* See http://thenewstack.io/microservices-calls-robust-api-management-tools/

Gateway or Backend For a Frontend (BFF)
• Unfortunately Gateways & BFF’s
introduce a lot of coupling
between the Gateway and the
underlying services
• If an underlying service changes
its contract in a non-backwards
compatible way the gateway
needs to change
• In these cases the clients of the
gateway may also need to change
since the changes can permeate
upwards (the gateway abstraction is
leaky)
* See http://thenewstack.io/microservices-calls-robust-api-management-tools/

Gateway/BFFGateway/BFF
GATEWAY OR
BACKEND FOR A FRONTEND
UI
Microservices
UI-3
MS-3
UI-2 UI-4
MS-4MS-2
UI-1 UI-5
MS-5MS-1
1’s
DB
2’s
DB
3’s
DB
4’s
DB
5’s
DB
Gateway/BFF

Application UI’s
• An applications is a composition of different services
• The composition can be:
• Resource Oriented Client Architecture (ROCA) style service
integration (http://roca-style.org/)
• Mashup of Service UI components in a dedicated Application –
aka. Composite UI
Both solutions involve
integration via Services
web interfaces to minimize
coupling to other services.
Image from http://scs-architecture.org/

Composite UI - example
Page Context:
{ type: Book, id: ISBN-10 0-321-83457-7 }
ImageService
BookService
ReviewService
PriceService
InventoryService
OthersAlsoBoughtService
PriceService
ReviewService
BookService
ImageService
BookService

Widget Widget
Page
Widget
Service A Service B Service C
Widget
Widget
Widget
Service A
Service B
Service C
Widget
Service C
• Overall structure of the page
is “owned” by the application.
• Each widget is owned and
delivered by the
underlying Service.
Page layout

A SERVICE OWNS ITS UI IN ALL
CONTEXTS AND FOR ALL COMPOSITE
UI’S
Not just for HTML clients

Invoice Composite UI example
InvoiceHeader
Order:ShippingI
nfo
Invoice:
InvoiceNumber
Invoice:
Data and Due
date
Order:
RelationInformation
Order:Item-
Qty
Product:Ite
m
Product:
Description
Order:
Item-Unit-Price
Order:
Item-
Total-
Price
Order:Total
Billing:Balance
All Services
participate at
the UI level for
each individual
Item in the
Order

Coupling matrix*
* Modified version of Ian Robinson’s matrix: http://iansrobinson.com/2009/04/27/temporal-and-behavioural-coupling/
Behavioral
coupling
Temporal
coupling
Low High
Low
High
Event oriented Command oriented
Emergency services Distributed 3 layer

TO BREAK TEMPORAL COUPLING &
BEHAVIORAL COUPLING
SERVICES NEEDS TO COMMUNICATE
ASYNCHRONOUSLY USING BUSINESS EVENTS
Services communicate facts without making
assumptions about what other services intend
to do with the events

Let’s make the implicit explicit!
Old wisdom seems to have been forgotten. Let’s introduce:
Business/Domain Events
Which:
• Signal that something has happened
• Closely aligned to the Domain Model
• Are handled by a messaging system
• They are in the past tense:
• CustomerBilled
• ParcelShipped
• CustomerCreated
• ReviewCreated
• CommentAdded
• CommentDeleted

Events are often the side effect of Commands
A Command message is prescriptive of what should happen. This is a stronger form of coupling than Events.
A Command’s primary goal is to capture USER INTENT
A Command supports a single usecase and targets a single Aggregate
Commands always carry a name in its imperative form: CreateOrder, ShipOrder, CancelOrder, ReimburseCustomer, etc.
“A command describes a Task that you want someone else to
carry out for you and the recipient can reject the Command”

Commands & Events
Commands mutate Aggregate state –
and if succesful – will result in one or more Events being published
Command Event(s)
AcceptOrder OrderAccepted
ShipOrder OrderShipped
AddComment CommentAdded
QuarantineReview ReviewQuarantined
UnquarantineReview ReviewUnquarantined

WE NEED TO CHANGE FOCUS FROM
SHORT TECHNICAL TRANSACTIONS
To long running business transactions
supporting business processes

Using Business Events to drive Business Processes
Sales Service
Shipping
Billing
Sales
Customers
MessageChannel
Online Ordering System
Web Shop
(Composite UI)
Billing Service
Shipping Service
Order
Accepted
Event
AcceptOrder
Command
The sales
fulfillment
processing
can now
begin…

Choreographed Event Driven Processes
Sales Service
Order
Accepted
Invoicing Service
Order Fulfilment
(Saga/
Process-Manager)
Shipping Service
Online Ordering System
MessageChannel(e.g.aTopic)
Order
Accepted
Order
Accepted
Customer
Billed
Customer
Billed
Order
Approved
Order
Approved
Works as a Finite
State Machine
(WorkFlow)
handling the life
cycle of Shipping
and thereby forms
a very central new
Aggregate in the
System

Choreography is very different from the classical
orchestrated integration process

The INPAY approach to Microservices

Different perspectives on data
With in a given Domain, e.g. Retail, there will exist multiple bounded contexts/sub-domains/business
capabilities such as:
• Product management
• Purchase
• Sales
• Pricing
• Inventory
• Shipping
• Support
• Accounting
• Management
Each of these lines of business have very specific and unique needs which are relevant for them alone in order
to conduct their business. They might use the same name for the entities they’re interested in or they might use
different names for the same logical entity.

Many perspectives on data
Online Retail System
Product
Unit Price
Promotional Price
Promotion End Date
Stock Keeping Unit (SKU)
Quantity On Hand (QOH)
Location Code
Price
Quantity Ordered
Name
The lifecycle of the data is VERY important!
Customer
Pricing
Inventory
Sales
Management Reporting

Smaller models & clear data ownership
Retail System
Pricing
Product
ProductID
Unit Price
Promotional
Price
…
Pricing
Inventory
Product
ProductID
SKU
QOH
Location Code
…
Inventory
Sales
Product
ProductID
Name
Description
Quantity
Ordered
…
Sales
Shared Entity identitySOA:
Service

Billing
Product
Catalogue
Shipping
Sales
Inventory
Pricing
Retail domain split into a Macro architecture
Usually contains
more than one
aggregate 

What’s a macro architecture
• It’s the static/stable(r) parts of your architecture
• Which are very costly to refactor and change
• Business capabilities are stable
• Therefore we should strive to align services with business
capabilities / bounded contexts (DDD)

Service and Business Capability alignment
“The advantage of business capabilities is their remarkable level
of stability. If we take a typical insurance organisation, it will likely
have sales, marketing, policy administration, claims management,
risk assessment, billing, payments, customer service, human
resource management, rate management, document management,
channel management, commissions management, compliance, IT
support and human task management capabilities. In fact, any
insurance organisation will very likely have many of these
capabilities.”
See http://bill-poole.blogspot.dk/2008/07/business-
capabilities.html

A Service is
• The technical authority for a given business capability
• It is the owner of all the data and business rules that support this business
capability – everywhere (including the UI)
• It forms a single source of truth for that capability
• This form of business and IT alignment ensures that we can maintain service
Autonomy & Encapsulation

Services/Business-capabilities in INPAY
Currency
Service
Finance
Service
Banking
Service
Identity
Management
Service
Sales
Service
PSP
Service
3rd party
Providers
Service
Virtual
Banking
Service
IT
Operations

Applications in INPAY
Identity
Management
Application
Contract
Manager
Application
Treasury
Application
Compliance
Application
Operations
Application
CRM
PSP
Gateway
PSP
Merchant
Application
ERP

Services, Applications and code
• Each Service and Application is maintained in separate Git repositories
• Common IT Operations libraries and infrastructure are maintained in other
separate Git repositories

So what’s inside a Service source repository?
• Autonomous Components
• Libraries
• Adapters
• Front-end UI components
• API contracts (mainly Events)
• DB Schemas
• Build file(s)

Service and deployment
• A Service represents a logical responsibility
boundary
• Logical responsibility and physical deployment of a Service DOES
NOT have to be 1-to-1
• It’s too constraining
• We need more degrees of freedom
• Philippe Krutchen 4+1 views of architecture: Logical and Physical designs
should be independent of each other
A service needs to be deployed everywhere its data is needed

Service deployment
• Many services can be deployed to the same physical server
• Many services can be deployed in the same application
• Application boundary is a Process boundary which is a physical boundary
• A Service is a logical boundary
• Service deployment is not restricted to tiers either
• Part of service A and B can be deployed to the Web tier
• Another part of Service A and B can be deployed to the backend/app-service
tier of the same application
• The same service can be deployed to multiple tiers / multiple applications
• ie. applications and services are not the same and does not share the
same boundaries
• Multiple services can be “deployed” to the same UI page (service mashup)
• Multiple services can cooperate to fulfill a larger use-case (e.g. a workflow or a
business process)

Service
Autonomous
Component
1..*
Is implemented by
A Service is the technical authority
of a specific Business Capability
e.g. Sales, Shipping, Billing
Services support business processes.
Business processes naturally span multiple services, but
there will always be a single service that is the actual
authority on the business process.
Service vs Autonomous Components

Also known as Microservices
Service
Autonomous
Component
1..*
Is implemented by
Service vs Autonomous Components
Autonomous-Components/Microservices are a division of Services along Transactional
boundaries (a transaction stays within the boundary of a Microservice)
Microservices are the individually logical deployable units of a Service with their own
Endpoints. Could e.g. be the split between Read and Write models (CQRS) - each would be
their own Microservice

Services are the corner stone
• We talk in terms of Services/business capabilities and the processes/use-
cases they support
• Autonomous-Components/Microservices are an implementation detail
• They are much less stable (which is a good thing – it means they’re easier to replace)
• With regards to other Services
• subscribe to events from
• send commands to (less common)
• call operations (in rare occasions)

Services/Bounded Contexts and Aggregates
Sales
Service
PSP
ServiceVirtual Banking
Service
Finance
Service
Customer
customerId
…
Contract
contractId
customerId
…
VBFeeSchedule
contractId
…
PSPFeeSchedule
contractId
…
BillingTemplate
contractId
…

INPAY Autonomous Component design principles

Commands and Events
Events
Identifiers
Commands

Commands and Events
public class RegisterBankCmd extends AbstractCommand {
@TargetAggregateIdentifier
public final BankId bankId;
public final String name;
public final Country countryOfOperation;
public RegisterBankCmd(BankId bankId, String name, Country countryOfOperation) {
Objects.requireNonNull(bankId, "bankId");
Objects.requireNonNull(name, "name");
Objects.requireNonNull(countryOfOperation, "countryOfOperation");
this.bankId = bankId;
this.name = name;
this.countryOfOperation = countryOfOperation;
}
}

Commands and Events
The generic business event interface includes the
name of the topic that subscribers must use
public class BankRegistered extends AbstractEvent implements BankEvent {
@AggregateIdentifier
public final BankId bankId;
public final String name;
public final Country countryOfOperation;
public BankCreated(BankId bankId, String name, Country countryOfOperation) {
this.bankId = bankId;
this.name = name;
this.countryOfOperation = countryOfOperation;
}
}
public interface BankEvent extends Serializable {
TopicName TOPIC_NAME = BankingServiceId.ID.topicName("bank-events");
}

CQRS
A single model cannot be
appropriate for reporting,
searching and transactional
behavior
Greg Young, 2008

Commands, Events and Query Models
Read model
Read model
Events
UI
Domain modelQuery/Read model
”AcceptOrder”
command
”OrderAccepted”
event
”Find all
Accepted Orders”
Query
Commands are Imperative: DoStuff
Events are Past tense: StuffDone

Event Sourcing
Aggregates track their own Domain Events
and derive state from them
Time
07:39
Time
07:40
Time
07:41
Time
07:45
Time
07:46
Time
07:50

Full CQRS
With EventSourcing
UI Domain
Event
Store
(can e.g. be a real
EventStore DB or
a Relational DB)
Commands – Change data
Commands Events
SQL DB Document DB Graph DB
UI Data
Queries – Ask for data
Events
Query Build
Our single
source of truth

Aggregate
public class Bank extends InPayEventSourcedAggregate {
@AggregateIdentifier
private BankId bankId;
@EventSourcedMember
private Map<BankAccountId, BankAccount> bankAccounts = new HashMap<>();
public Bank(BankId bankId, String name, Country countryOfOperation) {
apply(new BankRegistered(bankId, name, countryOfOperation));
}
public void addBankAccount(BankAccountId bankAccountId, …) {
if (!bankAccounts.containsKey(bankAccountId)) {
apply(new BankAccountAdded(bankId,
bankAccountId,
…));
}
}
@EventSourcingHandler
private void on(BankRegistered e) {
bankId = e.getBankId();
}
@EventSourcingHandler
private void on(BankAccountAdded e) {
BankAccount bankAccount =
bankAccounts.put(e.getBankAccountId(), new BankAccount(e.getBankId(), e.getBankAccountId(), …));
}
}

Service project structure sales_service
sales_api
sales_contract_ac
sales_customer_ac
frontend
sales_contract_manager_adapters
contract
adapters
sales/modules
customer
psp_service
psp_api
psp_fees_ac
…
frontend
psp_contract_manager_adapters
fees
adapters
psp/modules
fx
Legend:
Service/Business-Capability
External Event/Command Contracts
Autonomous Component
Autonomous Component Adapter
Angular.js Module
Builds into a Java JAR
Uses Spring MVC/REST
All Java 8 artifacts are built
using Gradle

Autonomous Component Library
• Can be deployed alone or co-located
• Usually deployed together with one or more adapters
• Works transparently in a clustered environment
• Completely Spring free 
• Only depends on our Core infrastructure library
• Common types and Id’s
• Bus infrastructure
• Service lookup
• CQRS building blocks (backed by Axon framework)

Client handled subscriptions
• Highly resilient pattern for an Event Driven Architecture that’s backed by AC’s that
use EventSourcing.
• In this model the publisher of the Events is responsible for the durability of all its
Events, typically to an EventStore/EventLog.
• Each client (subscriber) maintains durable information of the last event it received
from each publisher.
• When ever the client starts up it makes a subscription to the publisher where it
states from which point in time it wants events published.
• This effectively means that publisher can remain simple and the client (subscriber)
can remain simple and we don’t need additional sophisticated broker infrastructure
such as Kafka+ZooKeeper.

Client handled subscriptions
Publisher
Subscriber
A
Local storage
EventStore
Subscriber
B
Local storage
Topic
Subscription
Topic
Subscription
TopicSubscriptionHandler
TopicSubscriptionHandler
EventEvent
Event Event
EventBus
Event
Event

psp_fees_ac
(deployed on 10.25.26.102)
psp_fees_ac
(deployed on 10.25.26.101)
Bus Bus
Bus Bus
sales_contract_ac
(deployed on 10.25.26.104)
sales_contract_ac
(deployed on 10.25.26.103)
Federated Bus

Distributed
Bus
Topic
Queue
Topic
Publisher
side
Topic
Subscriber
side
Queue
Sender
side
Queue
Receiver
side
Local
Topic
Publisher
Local
Topic
Subscriber
Local
Queue
Sender
Local
Queue
Receiver
Distributed per Service
EventBus
Local
Topic
Subscriber
Local
Topic
Subscriber
Local
Queue
Sender
Distributed
Notifications
Distributed
Broadcast
Distributed
SingleInstance
Task

AUTONOMOUS-COMPONENTS/
MICROSERVICES ARE LOGICAL
DEPLOYABLE UNITS
That doesn’t mean they HAVE to be deployed individually.
Design for Distribution
But take advantage of locality

Logical Architecture Building Blocks

Autonomous Components can be co-deployed together
with Application backends
contract_manager (Spring Boot fat–jar)
sales_contract_ac
sales_customer_ac
sales_contract_manager_adapters
psp_api
psp_fees_ac
psp_contract_manager_adapters
frontend
sales_api
app
libs
contract
customer
fees

Application in code
@Configuration
@ComponentScan(basePackages = { "com.inpay.contractmanager",
"com.inpay.adapters",
"com.inpay.itops.spring" })
public class Application extends InpaySpringBootApplication {
public Application() {
super();
}
@Override
protected String getApplicationName() {
return "ContractManager";
}
@Override
protected Collection<AutonomousComponent> getAutonomousComponentsHostedInThisApplication() {
CurrencyExchangeRateAc currencyExchangeRateAc = new CurrencyExchangeRateAc();
return list(
new IDMCoreAc(),
new PSPFeeScheduleAc(currencyExchangeRateAc.getCurrencyConverter()),
new VBFeeScheduleAc(currencyExchangeRateAc.getCurrencyConverter()),
new ContractAc(),
new CustomersAc(),
currencyExchangeRateAc
);
}
public static void main(String[] args) {
SpringApplication.run(Application.class, args);
}
}

AC in code public class PSPAgreementAc extends HzBackedAutonomousComponent {
public static AutonomousComponentId SERVICE_AC_ID = PSP_SERVICE_ID.ac("psp_agreement_ac");
…
public PSPAgreementAc(CurrencyConverter currencyConverter) {
this.currencyConverter = currencyConverter;
}
@Override
public void onInitialize(IConfigureACEnvironment acSetup) {
acSetup.withAutonomousComponentId(SERVICE_AC_ID).usingServiceDataSource()
.withBusConfiguration(cfg -> {
cfg.getAxonContext()
.subscribeAnnotatedCommandHandler(new TemplateCmdHandler(
cfg.getAxonContext().eventSourcedRepository(PSPTemplate.class),
currencyConverter));
….
manageLifecycleFor(templateViewRepository = new TemplateViewRepository(cfg, currencyConverter));
})
.runOnBusStartup((bus, axonContext) -> {
bus.registerAxonReplayableTopicPublisher(InternalTemplateEvents.TOPIC_NAME,
replayFromAggregate(PSPTemplate.class)
.dispatchAggregateEventsOfType(InternalTemplateEvents.class));
bus.subscribeTopic(SERVICE_AC_ID.topicSubscriber("ContractEvents"),
ExternalContractEvents.TOPIC_NAME,
new SalesTopicSubscription(bus));
});
}
public TemplateViewRepository getTemplateViewRepository() { return templateViewRepository; }
}

AC, autonomy and “shared” service data
Service
DB
DB
Autonomous
Component
Autonomous
Component
Autonomous
Component
Autonomous
Component DB

50 shades of inter service AC Autonomy*
Endpoint Process Database Storage
Shared Shared Shared Shared
Own Shared Shared Shared
Own Own Shared Shared
Own Shared Own Shared
Own Own Own Shared
Own Own Own Own
Lower Autonomy
Higher Autonomy
* No RPC in use!

The "Why", "What" & "How" of Microservices - short version

Recommended

Recommended

More Related Content

What's hot

What's hot (19)

Similar to The "Why", "What" & "How" of Microservices - short version

Similar to The "Why", "What" & "How" of Microservices - short version (20)

Recently uploaded

Recently uploaded (20)

The "Why", "What" & "How" of Microservices - short version