Domain Driven Design 기반의 마이크로서비스 도출 방법론과 사례를 소개드립니다. Pivotal의 컨설팅 서비스에서 사용하는 기존의 Monolith 애플리케이션을 분석하고 전환하는 여러가지 방법론을 공유드립니다.

2. 마이크로서비스 전환 방법론과 사례
김영태

3. • Cloud Native Applications Journey
• Domain Driven Design
• AppTx Methodology
• Liberty Mutual Case
Agenda

4. Part 1
Cloud Native Applications Journey
© Copyright 2017 Pivotal Software, Inc. All rights Reserved.

5. Technical Filter
Type (ex. COTS, ISV), Suitability Factors, etc.
Application Portfolio
Business Filter
Criticality, Risk Tolerance, Change Frequency, etc.
Prioritized Backlog
App Tx Iterative Process
App Patterns PCF
App
Measurement &
Learning
Select top
app in
migration
backlog
Continued
iteration
Create / update patterns,
provide feedback to enhance
filtering and backlog velocity
Application
Transformation
Funnel
Use of tooling and templates
to quickly make effective
candidate selection,
constantly prioritize work
and continuously share
feedback to accelerate
future efforts

6. Technical Triage:
App Foundry
Automated suitability assessment
and decisioning framework.
Currently a closed beta, targeting
GA this fall.
Upload binary or map
to source control Parsers for most common
languages (Java, .NET,
PHP, Ruby, etc.)
Extensible rules (100s
available currently)
UI dashboard to help
triage decisioning

7. Understanding Your Application Portfolio
TECHNICALCONDITION
BUSINESS VALUEWORSE BETTER
WORSEBETTER
Tolerate Invest
MigrateEliminate
Focus here and start with the most
impactful custom apps built 0 to 7
years ago with supported tech
Understand:
● Technical condition (Y-Axis), e.g.
○ Scalability
○ Performance
● Business value, (X-Axis)e.g.
○ Criticality
○ Competitive advantage
● Operational cost (Size), e.g.
○ License
○ Hardware
● Risk (Color), e.g.
○ Compliance
○ Skill set

8. Methodology and Techniques
• Portfolio level
goals definition
• Cloud suitability
assessment and
education
• Define OKRs
• Discuss
timeline, staffing,
risk,
dependencies,
etc.
• One-week iterations
• Hands-on code within 2-3 days
• 1s to 10s of apps moved in 1s of
weeks
• Working code used to inform a
cookbook of patterns
Product Backlog
(Pivotal Tracker)
Boris
Event
Storming
OKRs
Slice
Analysis
Snap /
SnapE
Patterns
ScopingDiscovery
Ongoing Delivery Cycle
Value
Stream
Fixed Timeline Engagement
Supported by a Paired Team

9. Part 2
Domain Driven Design
© Copyright 2017 Pivotal Software, Inc. All rights Reserved.

10. “...the real breakthrough of object
design comes when the code expresses
the concepts of a model.”
“Anyone responsible for changing code
must learn to express a model through
the code. Every developer must be
involved in some level of discussion
about the model and have contact with
domain experts.”
- Eric Evans, Domain-Driven Design
Domain-Driven Design

11. “In the end the code is the model and the
model is the code.” - Vaughn Vernon,
Domain-Driven Design Distilled
As opposed to:
1. Business Overview
1.1 Requirement
This interface is used to send Sched CGO
messages from SHIP-PRO to ODS. SHIP-PRO will
send the SyncSCHD_CGO BO to MBS and MBS
will push the data to ODS as
SCHD_CGO_WRAPPER BO.
This interface will also be added to the AMS view
for monitoring.
Domain Driven Design

12. Aggregates
AGGREGATES mark off the scope
within which invariants have to be
maintained at every stage of the
lifecycle
● Transactional Boundary
● Public access only via the
Aggregate Root

13. “Generally speaking, there is a correspondence of one team per BOUNDED CONTEXT. One team can maintain
multiple BOUNDED CONTEXTS, but it is hard … for multiple teams to work on one together.” - Evans
Bounded Context

14. Vaughn Vernon, Domain-Driven Design Distilled
Event Driven Architecture

15. Part 3
AppTx Methodology
© Copyright 2017 Pivotal Software, Inc. All rights Reserved.

16. Working Code
Slices
Patterns
OKRs
Event Storming
Boris
SnapE
Implementation
rinse&repeat

17. OKRs

18. Ambitious
Where to?
Objectives
Key Results
+
-increase
decrease%
#
Are we going
the right
way?
AppTx
70 - 80%

19. Config Customer Test
Environment Quicker
Incrementally Handle
PROD traffic
Create Guidance for App
Transformation
1 Process state migrated
to PCF
1 State transition from
PCF to legacy env.
Reduce manual steps by
25%
Setup & complete
< 2 day
Reduce # of tools used
by 1/3
1 Central cookbook of
transformation recipes
5 Testing guidelines
10 Spring Boot templates
Mission: Reduce time to onboard new customers

20. Could Measure Should Measure
Objectives Key Results
brainstorm
brainstorm decide
order
define
Objective
Objective
Objective

21. Monitor by Status and Confidence

22. OKRs
Event Storming

23. Simple Tools

24. Discount
Bounded Context
Show
Payment
Payment
Movie
Venue
Movie
Chosen
Date
Chosen
Venue
Chosen
Seat
Chosen
Payment
Started
Discount
Code
Entered
Card
Payment
Chosen
Payment
Complet
ed
Ticket
Purchas
ed
!
Domain
Event
Relevant Business Event
“Seat Chosen”, “Ticket Purchased”
Aggregate
Brains
Accepts Actions / Generates “Events”
Partner
Venue
Chosen
3rd
Party
Coupon
Entered
Mobile
Payment
Chosen
3rd
Party
Payment
Chosen
Slice candidate
?

26. OKRs
Event Storming
Boris

27. More Tools

28. Service
Service based on Context
Payment Service”
Queue
Message Queue
“Seat Request”
UI External
Link to External
System
Service
Service
Service
Service
Service
Service
Ext
Ext
Q
Q
Q
UI
UI

30. Inform Architecture Event Flow
Contexts to µService API Discovery
Scenario Modeling Orchestration to
Choreography
Validate Slice
Candidate
Fill the Backlog

31. OKRs
Event Storming
Boris
SnapE

32. SnapE
API
Data Source /
Storage
UI Risks
Stories
Rabbit
MQ
REST /
JSON
CICS
GW
Other
Purchase
History
AdminUI
Dependent
On...
GET
/purchasesGET
/purchasesGET
/purchases

34. OKRs
Event Storming
Boris
SnapE
Implementation

35. Pivotal Tracker
© Copyright 2018 Pivotal Software, Inc. All rights reserved.
Requirements from Snap-E are managed in Pivotal
Tracker
Everyone on the team has access to the tool and can
at any time see what the team is working on.
We break work down into small, granular user stories
that have user value.
We stack rank the stories so that the highest priority
and highest value things are at the top.
We release frequently to keep feedback loops short in
order to learn if our product is on the right track.

36. Commit Code Change
Automate Build, Test,
Deploy
Store Binaries & Build
Artifacts
Deploy, UAT, Stage App
Zero Downtime
Upgrade to Production
SampleTool
Chain
Gitlab ArtifactoryConcourse
Pivotal HA
Services
(API
Driven)
Build pipeline that automates
smoke, acceptance, unit and
integration tests as feasible
SDLC space
promotion driven by
automated process
Patching and
upgrades fulfilled on a
rolling basis with zero
downtime
</>
Clean up SCC,
dependency and config
mgmt, tweak code and
address other 12-factor
concerns as needed
Automate the Release Pipeline

37. Various Patterns for Microservices
API Gateway, Edge
Server, B4FFInverse Conway
Event Shunting ACL, Context
Mapping, Strangler
Bridge, Router,
Proxy, Facade
Eventual
Consistency, Sagas,
ESB >> microservices
Tool Case by icons producer is licensed under CC 3.0

38. Cookbooks
Reusable patterns are documented as cookbooks to
be reused by other developers
Learn techniques for identifying problem areas,
decomposing monolithic apps, and organizing code for
continuous delivery.
Introduce technologies that help you build more
maintainable, adaptable systems.
Get access to playbooks and blueprints used by
dozens of enterprises to build a long-lasting practice
around app transformation.

39. Working Code
Slices
Patterns
OKRs
Event Storming
Boris
SnapE
Implementation
rinse&repeat
Direction / Stay on Track Business Flow / Potential Slices
Event Flow/ Inform Architecture
Size / Risk
Repeatable Recipes

40. Part 4
Liberty Mutual Case
© Copyright 2017 Pivotal Software, Inc. All rights Reserved.

41. Liberty Mutual’s Experiences with...
• Conway’s Law
• Entropy
• Breaking Down Monoliths for real
• MSA w/DDD to API-First

42. Conway’s law holds true
Source: https://martinfowler.com/articles/microservices.html#CharacteristicsOfAMicroserviceArchitecture
“Any organization that designs a system
(defined broadly) will produce a design
whose structure is a copy of the
organization's communication structure.”
- Conway’s Law
Source: http://melconway.com/Home/Conways_Law.html

43. Entropy always tends to increase within monoliths
Source: http://facstaff.gpc.edu/~mkim/C1211&1212Lec/C1212_Lecture.htm

44. Logical Separation Physical Separation

45. Decoupled UI

46. Microservices
Architecture

47. Before After *
* one aggregate
Deconstructing monolithic databases

48. API-First

49. Thank you.