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Conway’s law revisited
Architectures for an effective IT

Uwe Friedrichsen, codecentric AG, 2012-2015
@ufried
Uwe Friedrichsen | uwe.friedrichsen@codecentric.de | http://slideshare.net/ufried | http://ufried.tumblr.com
Why should we change?
Formal part of
value creation
Solution:
machine
Dynamic part
of value
creation
Solution: man
sluggishness/low dynamic high dynamichigh dynamic
The historical course of market dynamics
and the recent rise of highly dynamic and complex markets
The dominance of high dynamics and complexity is neither good nor bad. It‘s a historical fact.
t1970/80 today
Age of
crafts manu-
facturing
Age of
tayloristic
industry
Age of
global
markets
1850/1900
Spacious markets,
little competition
Local markets,
high customi-
zation
Outperformers exercise
market pressure over
conventional companies
We call the graph shown here the “Taylor Bathtub”.
The “bathtub” curve
Source: BetaCodex Network Associates, “Organize for complexity”, BetaCodex Network White Paper 12 & 13
Economic Darwinism
Economic Darwinism

Everyone is affected by Economic Darwinism

•  All sectors
•  Growing globalization on all levels
•  Internet business
•  More competitors per customer
•  Higher customer expectations
•  Lower customer loyalty

à In the long run only those will survive who
meet the customer needs and demands best
Nice, but how does this relate to IT?
IT is the nervous system

IT is vital

•  All companies
•  IT is not just supporter or „cost center“ …
•  … but it is the central nervous system
•  Even short IT outages considered critical
•  No business change without IT
•  No new products without IT

à IT limits the maximum possible

adaption rate of a company
IT is a key success factor for belonging to
the survivors of the economic darwinism
What business needs from IT …
Conway's law revisited - Architectures for an effective IT
Responsiveness
 Reliability
Throughput
 Flexibility
How IT serves business …
Conway's law revisited - Architectures for an effective IT
What’s wrong with IT?
1960
 1970
 1980
 1990
 2000
 2010
 2020
Complicated

(Business functions)
Complex

(Business processes)
Highly complex

(Business nervous system)
Software crisis
Software engineering
PC
LAN
Internet
Business
Support
of IT
Selective
Holistic
Complicated
Complex
“Moore’s law”
Mobile
IoT
1960
 1970
 1980
 1990
 2000
 2010
 2020
Complicated

(Business functions)
Complex

(business processes)
Highly complex

(Business nervous system)
Software crisis
Software engineering
PC
LAN
Internet
Business
Support
of IT
Selective
Holistic
Complicated
Complex
“Moore’s law”
Mobile
IoT
We are
here …
1960
 1970
 1980
 1990
 2000
 2010
 2020
Complicated

(Business functions)
Complex

(business processes)
Highly complex

(Business nervous system)
Software crisis
Software engineering
PC
LAN
Internet
Business
Support
of IT
Selective
Holistic
Complicated
Complex
“Moore’s law”
Mobile
IoT
… but we still base most of
our decisions on that
We are
here …
Formal part of
value creation
Solution:
machine
Dynamic part
of value
creation
Solution: man
sluggishness/low dynamic high dynamichigh dynamic
The historical course of market dynamics
and the recent rise of highly dynamic and complex markets
The dominance of high dynamics and complexity is neither good nor bad. It‘s a historical fact.
t1970/80 today
Age of
crafts manu-
facturing
Age of
tayloristic
industry
Age of
global
markets
1850/1900
Spacious markets,
little competition
Local markets,
high customi-
zation
Outperformers exercise
market pressure over
conventional companies
We call the graph shown here the “Taylor Bathtub”.
Remember the bathtub curve?








This adds an additional twist …
1960
 1970
 1980
 1990
 2000
 2010
 2020
Complicated

(Business functions)
Complex

(business processes)
Highly complex

(Business nervous system)
Software crisis
Software engineering
PC
LAN
Internet
Business
Support
of IT
Selective
Holistic
Complicated
Complex
“Moore’s law”
Mobile
IoT
… but we still base most of
our decisions on that
We are
here …
Business is very different today …
… than it was back then
We need to rethink IT!
Economic
Darwinism
Business-related
Change Drivers
IT
Technology-related
Change Drivers
But there is more …
Lean Enterprise
Product

shaping/optimization
Innovation
Measure & analyze
 Accelerating
OODA loop
Quick customer
feedback cycles
Economic
Darwinism
Business-related
Change Drivers
Lean
Enterprise
IT
Technology-related
Change Drivers
IT as a Product
(“Digitization”)
Virtualization
of products
IT-centric
business models
Disruptive new
business models
Economic
Darwinism
Business-related
Change Drivers
Lean
Enterprise
IT as a Product
IT
Technology-related
Change Drivers
Pay-per-Use
Business Case
Self-Service
Cloud
Elasticity
Unreliable

COTS Hardware
Provisioning
Speed
Economic
Darwinism
Business-related
Change Drivers
Lean
Enterprise
IT as a Product
Cloud
IT
Technology-related
Change Drivers
Zero Downtime
Peer
Multiplication 
Mobile & IoT
Deep Process
Integration
Unreliable

Communication
Unpredictable
Load Patterns
Economic
Darwinism
Business-related
Change Drivers
Lean
Enterprise
IT as a Product
Cloud
IoT
Mobile
IT
Technology-related
Change Drivers
… and more
Big Data
Analysis
Amplifiers
Social
Economic
Darwinism
Business-related
Change Drivers
Lean
Enterprise
IT as a Product
Cloud
IoT
Mobile
IT
Big Data
Analytics
Social
Technology-related
Change Drivers
We really need to rethink IT!
Process
 People
Organization
 Governance
Agile
 Lean
DevOps
 Flow
Decentralization
Autonomy
End2End Responsibility
Craftsmanship
Mastery
Curiosity
Beyond Budgeting
(BetaCodex)
Systemic Optimization
It would be fascinating to discuss them all
and to see how they fit into each other …
… but right now we want to focus on
architecture
So, what does that mean for architecture?
Architectural drivers

•  Need for quick change and extension
•  Replace over reuse
•  Need for quick releases
•  Unpredictable load patterns
•  Distributed, highly interconnected systems
•  Extreme high service availability
•  Diverse front-ends and devices
•  Cost efficiency
Architectural requirements

•  Easy to understand
•  Easy to extend
•  Easy to change
•  Easy to replace
•  Easy to deploy
•  Easy to scale
•  Easy to recover
•  Easy to connect
•  Easy to afford
Architectural requirements

•  Easy to understand 
à Understandability
•  Easy to extend 
à Extensibility
•  Easy to change 
à Changeability
•  Easy to replace 
à Replaceability
•  Easy to deploy 
à Deployability
•  Easy to scale 
à Scalability
•  Easy to recover 
à Resilience
•  Easy to connect 
à Uniform interface
•  Easy to afford 
à Cost-efficiency


(for development & operations)
Hey, what about Conway’s law?
Conway’s law: Organizations which design systems [...] are constrained to produce designs
which are copies of the communication structures of these organizations
Conway’s law reversed: You won’t be able to successfully establish an efficient organization

structure that is not supported by your system design (architecture)
Monolith
Example: Multiple teams working on a monolith usually end up in tightly coupled teams
with excessive communication overhead
But what kind of organizational structure
does our architecture need to support?
Process
 People
Organization
 Governance
Agile
 Lean
DevOps
 Flow
Decentralization
Autonomy
End2End Responsibility
Craftsmanship
Mastery
Curiosity
Beyond Budgeting
(BetaCodex)
Systemic Optimization
Our architecture needs to support
decentralized, autonomous* teams




* Autonomy in this context means to have the teams working as autonomous as possible, yet making sure they share

* the same overall vision. This means a certain amount of communication between the teams is always needed but it

* should be made sure that it happens as efficient as possible.
Architectural requirements

•  Easy to separate 
à Autonomy
•  Easy to understand 
à Understandability
•  Easy to extend 
à Extensibility
•  Easy to change 
à Changeability
•  Easy to replace 
à Replaceability
•  Easy to deploy 
à Deployability
•  Easy to scale 
à Scalability
•  Easy to recover 
à Resilience
•  Easy to connect 
à Uniform interface
•  Easy to afford 
à Cost-efficiency


(for development & operations)
What are the appropriate solutions?
Let’s check a few trending topics …
µServices






•  Built for replacement (not reuse)
•  Self-dependent, loosely coupled services
•  Should be aligned with business capability
•  Size should not exceed what one brain can grasp
µServices
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
REST







•  Uniform access interface to resources
•  Closely related to the HTTP protocol
•  HATEOAS (Hypermedia as the engine of application state)
REST
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
Event/Message-driven






•  Asynchronous communication paradigm
•  Technical decoupling of communication peers (isolation)
•  Location transparency in conjunction with MOM
•  Call-stack paradigm replaced by (complex) message networks
Event/Message-driven
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
CQRS






•  Command Query Responsibility Segregation
•  Separate read and write interfaces including underlying models
•  Separation can be extended up to the data store(s)
•  Allows for optimized data representations and access logic
READ
WRITE
CQRS
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
READ
WRITE
Autonomy
Reactive






•  Message-driven – asynchronous and non-blocking
•  Scalable – scaling out and embracing the network
•  Resilient – isolation, loose coupling and hierarchical structure
•  Responsive – latency control and graceful degradation of service
Reactive
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
Functional Programming






•  Alternative programming paradigm
•  Functional languages (Erlang, Haskell, Clojure, …)
•  Hybrid languages (Scala, …)
•  Languages with functional extensions (Python, JavaScript, Java, …)
Functional Programming
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
NoSQL






•  Augments the data store solution space
•  Different sweet spots than RDBMS
•  Key-Value Store – Wide Column Store – Document Store
•  Graph Database
NoSQL
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
Continuous Delivery






•  Automate the software delivery chain
•  Build – Continuous Integration, …
•  Test – Test Automation, …
•  Deploy – Infrastructure as Code, …
Continuous Delivery
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
Cloud provisioning model






•  On-demand provisioning and de-provisioning
•  Instant availability
•  Self-service
•  Pay-per-use
Cloud provisioning model
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
Docker






•  Build, ship, run on container-basis
•  Process-level isolation
•  Declarative communication path configuration
•  Cambrian explosion of ecosystem at the moment
Docker
Cost-efficiency
UniformInterface
Resilience
Scalability
Deployability
Replaceability
Changeability
Extensibility
Understandability
Autonomy
… and there are many more
What can we learn from this?
Findings






•  There is not a simple solution and no “one size fits all”
•  Some of the topics evaluated bear a high potential
•  Some of the topics evaluated are more of a side note
•  A mutually reinforcing combination of concepts is needed
How could an architectural style look like?
µServices

•  Conway’s law
•  Built for replacement
•  Aligned with business capabilities
•  Bounded Context (Domain-Driven Design)
•  Separate UI and service
Bounded
Context
Bounded
Context
Bounded
Context
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
UI

e.g., B2C-Portal
UI

e.g., embedded in
Partner-Portal
UI

e.g., Mobile App
UI

e.g., Clerk Desktop
REST interfaces

•  Use as API gateway for client access
•  Encapsulate dynamics and complexity of service landscape
•  Provide client-driven, coarse-grained service calls

behind a uniform API based on a proven protocol
•  Should be provided on bounded context level
•  Decouple speed of evolvement (services vs. API)
Bounded
Context
µS
µS
µS
µS
µS
REST API Gateway
µS
Bounded
Context
Other
Client
User Interface
Bounded
Context
Message-based API

also okay,

but requires clear and
stable, client-oriented
contract
Event-driven communication

•  Use for inter-service communication
•  Decoupling and isolation
•  Vertical slicing of functionality
•  Easier evolution of flows and processes
•  Configuration-visualization-monitoring support required
µS
Request/Response : Horizontal slicing
Flow / Process
µS
 µS
µS
 µS
 µS
µS
Event-driven : Vertical slicing
µS
 µS
µS
µS
 µS
Flow / Process
Resilient (reactive) software design

•  Resilience and responsiveness are mandatory
•  Elastic design for scalability
•  Start with isolation and latency control
•  Separate control and data flow
•  Many new challenges for developers
Event/data flow
 Event/data flow
Resource access
Error flow
 Control flow
µS
Isolation
Cloud/container provisioning model

•  Basis for elasticity at runtime
•  Basis for speed and flexibility at development time
•  Private, hybrid or public
•  Should be combined with container approaches (e.g., Docker)
•  “Natural” infrastructure for µService architecture
Container Manager
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
µS
Container
Explicitly declared communication paths
µService
Production-readiness

•  Configuration
•  Discovery, Routing
•  Choreography, Orchestration
•  Observability
•  Monitoring, Measuring, Logging
Configuration
•  Netflix Archaius

Orchestration
•  Apache Aurora on Apache Mesos
•  Marathon
•  Kubernetes
•  Fleet

Discovery
•  Netflix Eureka
•  Apache ZooKeeper
•  Kubernetes
•  Etcd
Routing
•  Netflix Zuul & Ribbon
•  Twitter Finagle

Monitoring
•  Hystrix
•  Twitter Zipkin (Distributed Tracing)

Measuring
•  Dropwizard Metrics

Logging
•  ELK
•  Graylog2
•  Splunk
Automation

•  Automate everything
•  Build, test & deployment (Continuous Delivery)
•  Resource provisioning (Cloud API)
•  Restart, failover, error handling (Resilience)
•  Starting and tearing down instances (Scalability)
5 + 2 style


•  µServices
•  REST interfaces
•  Event-driven communication
•  Resilient (reactive) software design
•  Cloud/container provisioning model

•  Production-readiness
•  Automation
One more thing …
Side note

Enterprise architecture management

•  Should not impact team autonomy
•  No interference with team responsibilities

•  Focus on shared vision
•  Provide common vision for all teams

•  Makes communication efficient
•  To follow common vision teams need to communicate
•  Minimal set of joint technical collaboration standards
required for efficient communication

•  Not a separate team
•  Use representatives from the teams
•  Add a person in charge if required

à Very different from traditional EAM
Wrap-up



•  Business & technological driven change
•  IT as a whole must respond to the drivers
•  Architecture must support the drivers
•  Architecture must support the organization
•  The new architectures are different
•  New challenges for developers (& ops)
We need to rethink IT






Join the most disruptive and exciting change
we have seen in IT for many years
@ufried
Uwe Friedrichsen | uwe.friedrichsen@codecentric.de | http://slideshare.net/ufried | http://ufried.tumblr.com
Conway's law revisited - Architectures for an effective IT

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Conway's law revisited - Architectures for an effective IT