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Dennis Doomen | @ddoomen | Aviva Solutions | The Continuous Improver
Also known as the Microservices Premium
Hybrid of
Front-end
Technologies
Multiple
patterns for the
same problems
Long compile
time
Large source
control
repositories
Long-running
unit tests
Too much
coupling
Limited
team scalability
Devs need to
know everything
NoIsolationProductivity
drops over time.
• The network is reliable
• Latency is zero
• Bandwidth is infinite
• The network is secure
• Topology doesn't change
• There is one administrator
• Transport cost is zero
• The network is homogeneous.
https://en.wikipedia.org/wiki/Fallacies_of_distributed_computing
The First Law of Distributed Computing
Very scalable,
very reliable
Very difficult to
debug
distributed
problems
Unreliable
network
requires
complicated
techniques
Requires
message
bus/broker
End-to-end
testing very
unpractical
Very mature
DevOps culture
is a prerequisite
Advanced
monitoring and
visualization is a
must
Security can not be an
afterthought
High operational
maintenance.
Can be
deployed/upgraded
independently.
Explosion of
network activity
Monolith
Microservice
Microservice
Microservice
HTTP API
HTTP API
HTTP API
OWIN component
released through
MyGet/Nuget
No network I/O at all
Can have its own database
instance, shared with monolith,
or shared storage service
Microservice owns
the schema
Separate repos with
distinct owners.
Runs in-process, thus
easier debugging
New version
requires
redeployment of
the monolith.
Loose coupling
through HTTP
Less scalability
options
HTTP is not the
fastest
serialization
format
Designed for
minimum
dependencies
Client
IIS
Console
WinSvc
Unit Test
HTTP
request
HTTP
response
Middleware
environment
handler
next
Middleware
IDictionary<string, object>
Func<IDictionary<string, object>, Task>
Task
Func<
Func<IDictionary<string, object>, Task>,
Func<IDictionary<string, object>, Task>
>
Monolith
Microservice
HTTP API
Service Registry
Contract
documented through
Swagger
Webhooks
Microservice
Microservice
Provides OWIN-
aware HttpClient to
connect to service
Event payload
exposed as Swagger
(e.g. SwaggerHub)
Subscribers register
URLs or in-process
OWIN message
handler
API/payload
consumers use liberal
JSON interpretation
Circuit Breaking to
handle unreliable
(future) consumers
At-least-once payload
delivery
Subcribers can
request replays.
Payload includes ID
to help idempotency
Each request requires
correlation ID that flows
through all APIs, webhooks
and services
Aggregates
Command
Handlers
Queries
Commands
Events
Upconverters
Value Objects
Query
Handlers
Schema
Migrations
Projectors
Data
Importers
Query API
Projections
HTML
CSS JS
API
Controllers
Projectors
Projections
Registrations
Webhook API
Command
API
Event
Storage
Domain
Services
Payload
Definitions
Outer layers depend
on inner layers
Domain is persistency
ignorant
Can be tested
independentlyFor eventual
consistent business
rules
Master data
For microservices
that provide a
(partial) UI or
management screen
Based on Domain
Driven Design
To persist the domain
To support domain
queries
UI / HTTP API
Command
Service
CorrectUser
EmailHandler
User
User
Projector
DAL
Read DB
Write DB
CorrectUserEmailCommand
Execute query
Get<User>(identity)
CorrectEmail
Event Store
Load(events)
Apply Changes
Get changes
Dispatcher Events
Handle(UserEmailCorrectedEvent)
Submit changes
Dennis Doomen | @ddoomen | The Continuous
Improver
History
Monolith
Microservice
HTTP API
Event Store
Events
Payload
Projector
Subscription
Request
Payload
‘event store’
Have their own
checkpoints
Projects fine-grained
events into payload
projections
Projector
Payload schema is
documented using
Swagger
Projector
Projector
Webhook Projectors
Separate
instance per
subscription
Subscriber
HTTP API
‘Project’ payload
‘events’ into
HTTP calls
Projected Data
Uses the incoming
payloads as an ‘event
store’
Payload
Use Circuit Breakers
to handle
slow/unavailable
subscribers
SQL DB Schema
changes using
FluentMigrator
or using NoSQL
DB
Subscription
Request
Domain
Event Store
Events
App
RDBMS
Events
Projection
EventsProjection
Projection
Projector
Optimized for
specific queries
Separate
projections
database NoSQL
Projector
Projection-specific
storage
Projector
HTML
Raw SQL or
Dapper
Run
asynchronously
Great for
sharding
Dennis Doomen | @ddoomen | The Continuous Improver
Events
Transaction 6
Transaction 5
Transaction 4
Transaction 3
Transaction 2
Transaction 1
Temporal
Projector
Read
Store
Time
Projected until
this point
Immutable, thus
auditable and SOX
compliance
Dennis Doomen | @ddoomen | The Continuous Improver
Domain
Event Store
Events
App
Events
Projection
EventsProjection
Projection
Projector
Application
projections
RDBMS
Reporting
Projector
Traditional
reporting model
Asynchronous
OLAP
Dennis Doomen | @ddoomen | The Continuous Improver
Dennis (v4)
Persisted State Changes
Dennis (v3)
Role Granted
PasswordChangedEvent
Dennis (v4)
Dennis (v3)
User Created
Role Granted
Phone Number Added
Password Changed
Dennis (v5)
Role Revoked
Dennis (v6)
Role Granted
Time
Dennis (v7)
Password Changed
Dennis Doomen | @ddoomen | The Continuous Improver
Events
1
2
3
6297
6298
6298
Projections
Documents
Groups
Users
Objects
Folders
Microservice
V2
Changes Queries
Events
1
2
3
6299
6300
6301
Projections
Documents
Groups
Users
Objects
Folders
Microservice
V1
ChangesQueries
Migration Process
Dennis Doomen | @ddoomen | The Continuous
Improver
Events
Aggregate
Root
Entity
Entity
Value
Object
Aggregate
Root
Aggregate
Root
Aggregate
Root
Entity
Value
Object
Value
Object
Dennis Doomen | @ddoomen | The Continuous Improver
Designing your domain
based on ownership
Relying on eventual
consistent projections
Bad choice in
functional keys (e.g.
username vs ID)
Running business logic
after an domain event
is raised
Domain-specific value
types in events
Ask questions about
consistency
Understand the real world
Driven by invariants, not
composition
Only consistent within
aggregate
Small aggregates
Reference by identity
• Column constraints (e.g. data truncation)
• Changes in data invariants (null vs non-
null in event versions)
• Unexpected projection dependencies
• Partial replays.
• Causing duplicate child records
• Causing large event streams
• Incorrect caching strategy (e.g. on
lookups)
• Identity case-sensitivity
• Incomplete SQL-backed event store
reads.
• Side by side rebuilding
• Functional archivability and archiving
• Projection tracking and ETAs
• Prioritization
• Partitioning.
• After bugs, schema changes, etc
• Manual or automatic (e.g. hashes)
Prerequisites
- Microservice owns ‘schema’
- Supports upgrading and downgrading
- NoSQL preferred, but RDBMS can
work too.
Rebuild schema in-place
– Rebuilding using event store
– Requires tracking API
– Involves down-time.
Disallow breaking changes
– Only new ‘columns’ and ‘tables’
– Partial rebuilding using event store
– Requires forwards compatibility.
Rebuild side-by-side
– Rebuilding using event store
– Requires tracking API
– Requires compatibility with
previous ‘schema’
– Previous ‘schema’ is removed in the
next release.
Microservice
Bunch of classes that
should be used directly
X
No inheritance
Uses composition
over inheritance
internally
Convenience classes
that don’t hide the
magic
Library
Abstract Package
Interfaces
Delegates
DTOs
Only depend
on abstract
packages…
Stable Package
…or depend on more
stable packages
Auxiliary
Package
Classes that are not
used together do not
belong togetherOptional
Dependency
Dependency
Package
Consumers should
not be faced with
optional
dependencies
public interface IEventStore
{
IDisposable Subscribe(
long? lastCheckpoint,
Func<Transaction[]>, Task> handler,
string subscriptionId);
}
public delegate IDisposable CreateSubscription(
long? lastCheckpoint,
Func<Transaction[]>, Task> handler,
string subscriptionId);
e.g. LibLog, TinyIoc, FluidCaching
Aggregates
Command
Handlers
Queries
Commands
Events
Upconverters
Value Objects
Query
Handlers
Schema
Migrations
Projectors
Data
Importers
Query API
Projections
HTML
CSS JS
API
Controllers
Projectors
Projections
Registrations
Webhook API
Command
API
Event
Storage
Domain
Services
Payload
Definitions
Liquid
Projections
RavenDB +
LiquidProjections.RavenDB NHibernate +
LiquidProjections.NHibernate
WebAPI / Nancy
Swashbuckle /
Nancy.Swagger Logging w/ Liblog
Composition w/ TinyIocNEventStore +
LiquidProjections.NEventStore
EventStore / SqlStreamStore
Fluent Migrator
JSFOTD +
Embedded Resources
OWIN Middleware.
Library
Consumer
LiquidProjections
LiquidProjections.Abstractions
Transaction
Delegates
LiquidProjections.
NEventStore
NHibernate
LiquidProjections
NHibernate
RavenDB
LiquidProjections
RavenDB
LiquidProjections.
Testing
Monolith
Microservice
Microservice
Microservice
HTTP API
HTTP API
HTTP API
Apply routing
conventions
Versioning
using Accept Headers,
Response Headers or
Routes
Optimize body using
AVRO or Protobuf
Cross-service tracing
using OpenTracing
Replace OWIN with
(upcoming) in-
process gRPC
Common contracts
for diagnostics,
monitoring
Add KPI dashboards,
e.g. Sumologic
1 Build a (container-based) cloud
capability.
2 Deploy monolith to the cloud.
3 Automate your delivery pipeline.
4 Full end-to-end responsibility
5 Break-up delivery teams and code
6 Evaluate status-quo on micro-services
(products, platforms, etc)
7 Slide-and-dice microservices one-by-
one.
• Liquid Projections – The Example
https://github.com/liquidprojections
• Bliki: MonolithFirst
https://dzone.com/articles/martin-fowler%E2%80%94bliki
• In-process gRPC
https://github.com/grpc/grpc-go/issues/906
• Protobuf in WebAPI
http://www.infoworld.com/article/2982579/application-
architecture/working-with-protocol-buffers-in-web-api.html
• Ingredients for well-design OWIN components
http://www.continuousimprover.com/search/label/OWIN%20Recip
es
• The good, the bad and the ugly of Event Sourcing
http://www.continuousimprover.com/search/label/event%20sourci
ng

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