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Designing
Events First
Microservices
Jonas Bonér
@jboner
1. Events drive autonomy
2. Events help reduce risk
3. Events help you move faster
4. Events Increase Loose coupling
5. Events increase stability
6. Events increase scalability
7. Events increase resilience
8. Events increase traceability
9. Events allow for time-travel
Why Should you care about Events?
Why Now?
1. Cloud and multicore architectures
2. Microservices and distributed systems
3. Data-centric applications - Data in motion
4. “We want more, of everything, and we
want it now.” -Your Customers
So, you want to do
microservices?
Make sure you don’t end up with
Microliths
Make sure you don’t end up with
Microliths
We can do better than this
Events First
Domain Driven
Design
“When you start modeling events, it
forces you to think about the behaviour
of the system. As opposed to thinking
about the structure of the system.”
- Greg Young
A Decade of DDD, CQRS, Event Sourcing, Greg Young (Presentation from 2016)
✴ Don’t focus on the things
The Nouns
The Domain Objects
✴ Don’t focus on the things
The Nouns
The Domain Objects
✴ Focus on what happens
The Verbs
The Events
What is an
Event?
The Nature of Events
✴Events represent Facts of information
➡ Facts are immutable
➡ Facts Accrue - Knowledge can only grow
The Nature of Events
✴Events represent Facts of information
➡ Facts are immutable
➡ Facts Accrue - Knowledge can only grow
✴ Events/Facts can be disregarded/Ignored
The Nature of Events
✴Events represent Facts of information
➡ Facts are immutable
➡ Facts Accrue - Knowledge can only grow
✴ Events/Facts can be disregarded/Ignored
✴ Events/Facts Can not be retracted (once accepted)
The Nature of Events
✴Events represent Facts of information
➡ Facts are immutable
➡ Facts Accrue - Knowledge can only grow
✴ Events/Facts can be disregarded/Ignored
✴ Events/Facts Can not be retracted (once accepted)
✴ Events/Facts Can not be deleted (once accepted)
➡ Might be needed for legal or moral reasons
The Nature of Events
✴Events represent Facts of information
➡ Facts are immutable
➡ Facts Accrue - Knowledge can only grow
✴ Events/Facts can be disregarded/Ignored
✴ Events/Facts Can not be retracted (once accepted)
✴ Events/Facts Can not be deleted (once accepted)
➡ Might be needed for legal or moral reasons
✴ Events/Facts (new) can invalidate existing Facts
The Nature of Events
Mine the
Facts
Designing Events-first Microservices
Event Storming
Event Driven Design
✴ IntentS
➡ Communication
➡ Conversations
➡ Expectations
➡ Contracts
➡ Control Transfer
Event Driven Design
✴ IntentS
➡ Communication
➡ Conversations
➡ Expectations
➡ Contracts
➡ Control Transfer
Event Driven Design
✴ Facts
➡ State
➡ History
➡ Causality
➡ Notifications
➡ State Transfer
✴ IntentS
➡ Communication
➡ Conversations
➡ Expectations
➡ Contracts
➡ Control Transfer
Event Driven Design
✴ Facts
➡ State
➡ History
➡ Causality
➡ Notifications
➡ State Transfer
Commands
✴ IntentS
➡ Communication
➡ Conversations
➡ Expectations
➡ Contracts
➡ Control Transfer
Event Driven Design
✴ Facts
➡ State
➡ History
➡ Causality
➡ Notifications
➡ State Transfer
Commands Events
Event Driven Design
✴Commands
➡ Object form of method/Action request
➡ Imperative: CreateOrder, ShipProduct
Event Driven Design
✴Commands
➡ Object form of method/Action request
➡ Imperative: CreateOrder, ShipProduct
✴Reactions
➡ Represents side-effects
Event Driven Design
✴Commands
➡ Object form of method/Action request
➡ Imperative: CreateOrder, ShipProduct
✴Reactions
➡ Represents side-effects
✴Events
➡ Represents something that has happened
➡ Past-tense: OrderCreated, ProductShipped
Event Driven Design
Commands Eventsvs
Commands Eventsvs
1. All about intent 1. Intentless
Commands Eventsvs
1. All about intent
2. Directed
1. Intentless
2. Anonymous
Commands Eventsvs
1. All about intent
2. Directed
3. Single addressable
destination
1. Intentless
2. Anonymous
3. Just happens - for
others (0-N) to observe
Commands Eventsvs
1. All about intent
2. Directed
3. Single addressable
destination
4. Models personal
communication
1. Intentless
2. Anonymous
3. Just happens - for
others (0-N) to observe
4. Models broadcast
(speakers corner)
Commands Eventsvs
1. All about intent
2. Directed
3. Single addressable
destination
4. Models personal
communication
5. Distributed focus
1. Intentless
2. Anonymous
3. Just happens - for
others (0-N) to observe
4. Models broadcast
(speakers corner)
5. Local focus
Commands Eventsvs
1. All about intent
2. Directed
3. Single addressable
destination
4. Models personal
communication
5. Distributed focus
6. Command & Control
1. Intentless
2. Anonymous
3. Just happens - for
others (0-N) to observe
4. Models broadcast
(speakers corner)
5. Local focus
6. Autonomy
Let the Events Define the
Bounded Context
Event Driven
Services
1. REceive & react (or not) 

to facts* that are coming its way
Event Driven
Services
1. REceive & react (or not) 

to facts* that are coming its way
2. Publish new facts* asynchronously 

to the rest of the world
Event Driven
Services
1. REceive & react (or not) 

to facts* that are coming its way
2. Publish new facts* asynchronously 

to the rest of the world
3. Invert the control flow

to minimize coupling and increase autonomy
Event Driven
Services
1. REceive & react (or not) 

to facts* that are coming its way
2. Publish new facts* asynchronously 

to the rest of the world
3. Invert the control flow

to minimize coupling and increase autonomy
Event Driven
Services
*Facts == Immutable Events
Mutable State Is Fine
But Needs To Be
Contained
And Non Observable
Publish Facts
To Outside World
✴ Maintains Integrity & consistency
✴ Is our Unit of Consistency
✴ Is our Unit of Failure
✴ Is our Unit of Determinism
✴ Is fully Autonomous
The Aggregate
Event Driven
Services
Event Driven
Services
Event Driven
Services
Command
Event Driven
Services
Command
Event Driven
Services
Command
Event Driven
Services
Command
Event
Event Stream
Event Driven
Services
Command
Event
EventEvent
Event Stream
Event Driven
Services
Command
Event
EventEvent
Event Stream
Event Driven
Services
Command
Event
EventEvent
Event Stream
Event Driven
Services
Command
Event
EventEvent
Event Stream
Event Driven
Services
Command
Event
EventEvent
Event Stream
Event Driven
Services
Eventual
Consistency
Command
Event
EventEvent
Event Stream
Event
Stream
Use The
Event
Stream
Use The
as the communication fabric
Event
Stream
Use The
Event
Stream
Use The
as the integration fabric
Event
Stream
Use The
Event
Stream
Use The
as the replication fabric
Event
Stream
Use The
Event
Stream
Use The
as the consensus fabric
Event
Stream
Use The
Event
Stream
Use The
as the Persistence fabric
The Problem With
CRUD Services
✴ CRUD is fine for totally isolated data
The Problem With
CRUD Services
✴ CRUD is fine for totally isolated data
✴ But, cross CRUD services consistency
The Problem With
CRUD Services
✴ CRUD is fine for totally isolated data
✴ But, cross CRUD services consistency
➡ Is hard ⇨ No Joins
The Problem With
CRUD Services
✴ CRUD is fine for totally isolated data
✴ But, cross CRUD services consistency
➡ Is hard ⇨ No Joins
➡ Has ad-hoc & weak guarantees
The Problem With
CRUD Services
✴ CRUD is fine for totally isolated data
✴ But, cross CRUD services consistency
➡ Is hard ⇨ No Joins
➡ Has ad-hoc & weak guarantees
The Problem With
CRUD Services
“In general, application developers simply
do not implement large scalable applications
assuming distributed transactions”
- Pat Helland
Life Beyond Distributed Transactions - Pat Helland
“Two-phase commit is the
anti-availability protocol.”
- Pat Helland
Standing on Distributed Shoulders of Giants - Pat Helland
STRONG
Consistency
Is the wrong default
In distributed systems
STRONG
Consistency
Is the wrong default
In distributed systems
What can we do?
Eventual
Consistency
We have to rely on
Eventual
Consistency
We have to rely on
But relax—it’s how the world works
Embrace
Reality
We Need to
Embrace
Reality
We Need to
Not Fight it
Information
Has Latency
Information Is Always
From the Past
Welcome To The Wild Ocean Of
Non Determinism
Distributed Systems
“In a system which cannot count on
distributed transactions, the management
of uncertainty must be implemented in the
business logic.”
- Pat Helland
Life Beyond Distributed Transactions, Pat Helland (2007)
We Need To Model
Uncertainty
Events Can Lead To Greater
Certainty
“An autonomus component can only
promise its own behavior.”
“Autonomy makes information local,
leading to greater certainty and stability.”
- Mark Burgess
In Search of Certainty, Thinking in Promises - Mark Burgess
Events Can Help Us Craft
Autonomous Islands
Of Determinism
Data on the inside vs Data on the outside - Pat Helland
Data on the inside vs Data on the outside - Pat Helland
Inside Data
Our current present ⇨ state
Data on the inside vs Data on the outside - Pat Helland
Inside Data
Our current present ⇨ state
Outside Data
Blast from the past ⇨ Events/facts
Data on the inside vs Data on the outside - Pat Helland
Inside Data
Our current present ⇨ state
Outside Data
Blast from the past ⇨ Events/facts
Between Services
Hope for the future ⇨ commands
A system of microservices is a
never ending stream towards convergence
There Is No Now
A system of microservices is a
never ending stream towards convergence
Resilience
is by
Design
Photo courtesy of FEMA/Joselyne Augustino
Events Can Help Us
Manage
Failure
Instead Of Trying To Avoid It
Requirements for a
Sane Failure Model
1. Contained—Avoid cascading failures
2. Reified—as Events
3. Signalled—Asynchronously
4. Observed—by 1-N
5. Managed—Outside failed Context
Failures need to be
Event Based
Persistence
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
Service B
Service A
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
Service B
Service A
CRUD
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Service B
Service A
TABLE A
CRUD
TABLE B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Service B
Service A
TABLE A
CRUD
TABLE B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Service B
Service A
TABLE A
CRUD
TABLE B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Atomic Update & event
Service B
Service A
TABLE A
CRUD
TABLE B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Atomic Update & event
Service C
Service B
Service A
TABLE A
CRUD
TABLE B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Atomic Update & event
Service C
Service B
Service A
TABLE A
CRUD
TABLE B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Atomic Update & event
Service C
Service B
Service A
TABLE A
CRUD
TABLE B
JOINS
Table A
Table B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Atomic Update & event
Service C
Service B
Service A
TABLE A
CRUD
TABLE B
JOINS
Table A
Table B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Read
Only
Atomic Update & event
Service C
Service B
Service A
Eventual
Consistency
TABLE A
CRUD
TABLE B
JOINS
Table A
Table B
You can use CRUD
Together with Event Streams
To get an internally consistent Materialized View
CRUD
Read
Only
Atomic Update & event
“Update-in-place strikes systems
designers as a cardinal sin: it violates
traditional accounting practices that have
been observed for hundreds of years.”
- jim Gray
The Transaction Concept, Jim Gray (1981)
“The truth is the log.
The database is a cache
of a subset of the log.”
- Pat Helland
Immutability Changes Everything, Pat Helland (2015)
Event Logging
The Bedrock
Event Sourcing
A Cure For the Cardinal Sin
Event
Sourced
Services
Happy Path
Event
Sourced
Services
Happy Path
Event
Sourced
Services
1) Receive and verify Command
(“ApprovePayment”)
Happy Path
Event
Sourced
Services
2) Create new Event
(“PaymentApproved”)
1) Receive and verify Command
(“ApprovePayment”)
Happy Path
Event
Sourced
Services
2) Create new Event
(“PaymentApproved”)
1) Receive and verify Command
(“ApprovePayment”)
3) Append Event
to Event Log
Happy Path
Event
Sourced
Services
2) Create new Event
(“PaymentApproved”)
1) Receive and verify Command
(“ApprovePayment”)
3) Append Event
to Event Log
4) Update internal
component state
Happy Path
Event
Sourced
Services
5) Run side-effects
(approve the payment)
2) Create new Event
(“PaymentApproved”)
1) Receive and verify Command
(“ApprovePayment”)
3) Append Event
to Event Log
4) Update internal
component state
SAD Path - recover from failure
Happy Path
Event
Sourced
Services
5) Run side-effects
(approve the payment)
2) Create new Event
(“PaymentApproved”)
1) Receive and verify Command
(“ApprovePayment”)
3) Append Event
to Event Log
4) Update internal
component state
SAD Path - recover from failure
Happy Path
Event
Sourced
Services
5) Run side-effects
(approve the payment)
2) Create new Event
(“PaymentApproved”)
1) Receive and verify Command
(“ApprovePayment”)
3) Append Event
to Event Log
4) Update internal
component state
1) Rehydrate Events
from Event Log
SAD Path - recover from failure
Happy Path
Event
Sourced
Services
5) Run side-effects
(approve the payment)
2) Create new Event
(“PaymentApproved”)
1) Receive and verify Command
(“ApprovePayment”)
3) Append Event
to Event Log
4) Update internal
component state
1) Rehydrate Events
from Event Log
2) Update internal
component state
SAD Path - recover from failure
Happy Path
Event
Sourced
Services
5) Run side-effects
(approve the payment)
2) Create new Event
(“PaymentApproved”)
1) Receive and verify Command
(“ApprovePayment”)
3) Append Event
to Event Log
4) Update internal
component state
1) Rehydrate Events
from Event Log
2) Update internal
component state
Memory Image
Event Sourcing
Event Sourcing
✴ One single Source of Truth with All history
Event Sourcing
✴ One single Source of Truth with All history
✴ Allows for Memory Image (Durable In-Memory State)
Event Sourcing
✴ One single Source of Truth with All history
✴ Allows for Memory Image (Durable In-Memory State)
✴ Avoids the Object-relational mismatch
Event Sourcing
✴ One single Source of Truth with All history
✴ Allows for Memory Image (Durable In-Memory State)
✴ Avoids the Object-relational mismatch
✴ Allows others to Subscribe to state changes
Event Sourcing
✴ One single Source of Truth with All history
✴ Allows for Memory Image (Durable In-Memory State)
✴ Avoids the Object-relational mismatch
✴ Allows others to Subscribe to state changes
✴ Has good Mechanical sympathy

(Single Writer Principle etc.)
✴ Unfamiliar model
✴ Versioning of events
✴ Deletion of events (legal or moral reasons)
Disadvantages
Of Using Event Sourcing
Untangle Your
Read and Write Models
With CQRS
CQRS
CQRS
CQRS
Write Side Model
Commands
CQRS
Write Side Model
Write to Event Log
Commands
CQRS
Write Side Model
Events
Write to Event Log
Commands
CQRS
Write Side Model
Events
Events
Write to Event Log
Commands
CQRS
Read Side Model
Write Side Model
Events
Events
Read Data Store
Write to Event Log
Commands
CQRS
Read Side Model
Write Side Model
Events
Queries
Events
Read Data Store
Write to Event Log
Commands
CQRS
Read Side Model
Write Side Model
Events
Queries
Events
Read Data Store
Write to Event Log
Eventual
Consistency
Commands
✴ Temporal Decoupling
✴ Increased Resilience
✴ Increased Scalability
✴ Allows for Multiple Event subscribers
✴ Allows for Polyglot Persistence
Advantages
Of Using CQRS
✴ More infrastructure to manage
✴ 2 data models (or more) to maintain
✴ Eventual Consistency
Disadvantages
Of Using CQRS
EventsAllow Us To Manage
Time
“Modelling events forces you to have a 

temporal focus on what’s going on in the system.
Time becomes a crucial factor of the system.”
- Greg Young
A Decade of DDD, CQRS, Event Sourcing, Greg Young (Presentation from 2016)
✴ Event is a snapshot in time
✴ Event ID is an index for time
✴ Event Log is our full history
The database of Our past
The path to Our present
Event Sourcing
Allows Us To
Model Time
Event Sourcing
Allows For
Time Travel
Event Sourcing
Allows For
Time Travel
Event Sourcing
Allows For
Time Travel
✴Replay the log for historic debugging
✴Replay the log for auditing & traceability
✴Replay the log on failure
✴Replay the log for replication
We Can Even Fork the Past
...Or Join Two Distinct Pasts
Key Takeaways
Key Takeaways
Events-First design helps you to:
✴ reduce risk when modernizing applications
✴ Move Faster towards a Resilient and Scalable architecture
✴ Design autonomous services
✴ Balance Certainty and Uncertainty
Key Takeaways
Events-First design helps you to:
✴ reduce risk when modernizing applications
✴ Move Faster towards a Resilient and Scalable architecture
✴ Design autonomous services
✴ Balance Certainty and Uncertainty
Event Logging allows you to:
✴ AVOID CRUD and ORM
✴ take control of your system’s history
✴ time-travel
✴Balance Strong and eventual consistency
http://akka.io
Learn More
Download my latest book for free at:
bit.ly/reactive-microsystems

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