The document serves as a guide for developers to navigate the complexities of modern IT, emphasizing the evolution of market dynamics and technology. It discusses the historical context of IT, highlighting shifts from structured to complex business environments and the necessity for adaptability in development practices. Key trends include digitization, customer expectations, and emerging disruptive technologies, all of which are reshaping the role and strategies of IT in business.

1. The hitchhiker’s guide for the confused developer
Making sense of an increasingly mad IT
Uwe Friedrichsen – codecentric AG – 2012-2018

2. Uwe Friedrichsen
IT traveller.
Dot Connector.
Cartographer of uncharted territory.
Keeper of timeless wisdom.
CTO and Fellow at codecentric.
https://www.slideshare.net/ufried
https://medium.com/@ufried
@ufried

3. Have you ever felt like (almost) everyone
and everything in IT is going mad?

4. Like everything is getting more and more
complex every week?

5. And you already feel like you hardly can
hold together all the bits and pieces?

6. But you are getting less and less time
to pick up the plethora of new stuff?

7. And all that “Agile” just feels like a big hoax
which makes things worse than better?

8. Do you sometimes feel like you might
miss what is really important?

9. And instead waste your time
in a crazy rat race to nowhere?

10. Will AI replace your job in a few years?

11. And what about IoT, Blockchain
and all those other “disruptions”?

12. Do you sometimes ask yourself
if you are still on the right track?

13. Or that you might focus
on the wrong things?

14. But what are the “right” things?

15. Do you sometimes feel like this?

16. Or like this?

17. Then it might be time for a little
hitchhiker’s guide to the IT of today

18. But first of all ...

20. Understanding IT
A complex structure observed from multiple viewpoints

21. Viewpoint #1
Market evolution

22. 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

23. 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”.
Pre-industrial era
Source: BetaCodex Network Associates, “Organize for complexity”, BetaCodex Network White Paper 12 & 13
Tailor-made
solutions
Mastery
is key to success

24. 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”.
Industrial era
Source: BetaCodex Network Associates, “Organize for complexity”, BetaCodex Network White Paper 12 & 13
Cost-efficiently
scale production
Getting more done with less people
is key to success

25. 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”.
Post-industrial era
Source: BetaCodex Network Associates, “Organize for complexity”, BetaCodex Network White Paper 12 & 13
Continuously respond
to changing demands
Continuous market adaption
is key to success

26. Key drivers
Pre-industrial era
• No clear driver
Industrial era
• Cost-efficiency
• Scalability
• Repeatability
• Stability
• Efficiency & scale
Post-industrial era
• Cycle times
• Adaptability
• Flexibility
• Resilience
• Effectiveness & speed

27. Viewpoint #2
IT evolution

28. 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

29. IT has changed a lot over the decades ...

30. 1960
1970
1980
1990
2000
2010
2020
Complicated
(Business functions)
Complex
(Business processes)
Highly complex
(Business nervous system)
Software crisis
PC
LAN
Internet
Business
Support
of IT
Selective
Holistic
Complicated
Complex
“Moore’s law”
Mobile
IoT
Software engineering
... but still we strive to
control our IT of today ...
... based on the concepts
we developed for an IT
almost 50 years ago

31. 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?
Source: BetaCodex Network Associates, “Organize for complexity”, BetaCodex Network White Paper 12 & 13

32. 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
Also the business we
support with IT today ...
... is very different from
the business we
supported back then

33. What is the role of IT today?

34. IT today is ...
• ... the nervous system of the business
• ... an enabler of (disruptive) new business models
• ... an integral part of the business model (“digitization”)
• ... the medium for the continuous customer communication

35. Viewpoint #3
Technology evolution

36. Disruptive technologies
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
UNIX
Server
Personal
Computer
Notebook

37. Disruptive technologies
Assembly
language
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
High-level
language
Algol
Lisp
Simula
Cobol
UNIX
Server
Personal
Computer
Standard
Software
OSS
Notebook

38. Disruptive technologies
Assembly
language
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
High-level
language
Algol
Lisp
Simula
Cobol
UNIX
Server
LAN
Personal
Computer
Standard
Software
OSS
WWW
Notebook
Mobile
networks
(3G+)
Wi-Fi
Modem
9600+ Baud

39. Disruptive technologies
Assembly
language
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
High-level
language
Algol
Lisp
Simula
Cobol
UNIX
Server
LAN
Personal
Computer
Standard
Software
OSS
WWW
Notebook
Smartphone
Mobile
networks
(3G+)
Tablet
Wi-Fi
Modem
9600+ Baud

40. Disruptive technologies
Assembly
language
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
High-level
language
Algol
Lisp
Simula
Cobol
UNIX
Server
LAN
Personal
Computer
Standard
Software
OSS
WWW
Notebook
Smartphone
Cloud
Mobile
networks
(3G+)
Big Data
Tablet
Wi-Fi
SaaS
Serverless
FaaS +
Managed
services
Modem
9600+ Baud

41. Disruptive technologies
Assembly
language
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
High-level
language
Algol
Lisp
Simula
Cobol
UNIX
Server
LAN
Personal
Computer
Standard
Software
OSS
WWW
Notebook
Smartphone
Cloud
Mobile
networks
(3G+)
Big Data
Tablet
Wi-Fi
SaaS
Serverless
FaaS +
Managed
services
PLC
Industrial
PC
OPC UA
IoT
Modem
9600+ Baud

42. Disruptive technologies
Assembly
language
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
High-level
language
Algol
Lisp
Simula
Cobol
UNIX
Server
LAN
Personal
Computer
Standard
Software
OSS
WWW
Notebook
Smartphone
Cloud
Mobile
networks
(3G+)
Big Data
Tablet
Wi-Fi
SaaS
Serverless
FaaS +
Managed
services
PLC
Industrial
PC
OPC UA
IoT
Modem
9600+ Baud

43. Viewpoint #4
Programming model evolution

44. Programming models
DIY
Do It yourself
Web applications
Enterprise Frameworks
CORBA, SOA, JEE, .net, ...
IoT
Serverless
FaaS +
Managed
services
Cloud native
Microservices
?
Libraries &
Frameworks
Embedded computing
Standard software
customization
HPC
High Performance Computing
Local computing paradigm
Distributed computing paradigm

45. Complementing viewpoints

46. System theory - Cynefin
Source: By Snowded - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=33783436
The simple things
• Do them ad hoc
• Use check lists
• KISS!
• ...
The domain of planning
• Waterfall, V-Model, ...
• Iterative & incremental
• SAFe
• ...
The domain of uncertainty
• Inspect & adapt
• Agile (XP, Kanban, ...)
• Focus on outcome
• ...
Never be here in an IT
project! Never, ever!

47. Source: http://blog.gardeviance.org/2015/02/an-introduction-to-wardley-value-chain.html
WardleyMaps

48. Source: http://blog.gardeviance.org/2015/02/an-introduction-to-wardley-value-chain.html

49. Source: http://blog.gardeviance.org/2015/02/an-introduction-to-wardley-value-chain.html

50. Source: http://blog.gardeviance.org/2015/02/an-introduction-to-wardley-value-chain.html
Pioneer
Settler
Town
Planner

51. More complementing viewpoints
• Evolution of “Make or buy”
• Double Helix
• Local computing vs. distributed computing

52. Understanding current IT trends
Complementing the picture

53. Meta-Trend #1
Digitization (whatever that means ...)

54. Digitization (Definition)
• Blurry and misleading term – yet an important change driver
• Response to market demands and technology evolution
• Core: IT becomes integral part of business offerings
• Consequence: Cross-domain boundaries start to dissolve
and leverage – currently still unknown – business models

55. Digitization (Effect)
• Uncertainty regarding business model viability
• Effect: Short iterations, pervasive metrics (incl. measuring
outcome), A/B testing, smart rollout strategies, ...
• Dissolving domain boundaries
• Effect: API, platforms, ...
• Adaption of persistent requirements to a new context
• Effect: Poor connectivity as a constraint, re-thinking
accessibility, “developer experience” on the API level, ...

56. Meta-Trend #2
Customer expectations

57. Customer expectations
• Great user experience (UX)
• Fast response times
• Multi-device capabilities
• Zero downtime
• Strong Security (regarding data privacy)
• Adapts to customer’s needs and demands

58. Resulting IT trends

59. Moving fast
• Minimize cycle times to accelerate the feedback loop
• Response to business model uncertainty
• Goal is to minimize idle and value-reducing performances
• Massive paradigm shift (“Re-thinking IT”)
That is what DevOps actually is about!

60. Focus on frontends
• The battle for customers gets decided in the frontend
• Backends just need to work and must not get in the way
• UX and UI design become key differentiators
• Backend becomes commodity
• Bear all types of frontends in mind (incl. IoT, API, ...)

61. Cloud-native and serverless
• Reduce vertical integration depth
• Focus on value-creating IT performance to move faster
• Newest incarnation of “make or buy”
• Managed services as successor of standard software
• FaaS to orchestrate managed services
• Managed container and batch jobs for deep business logic

62. Ambient computing
• Shift towards human-centered user interfaces
• Complemented by context-aware computing & UIs
• “Mobile first” is just a transitional step
• New types of human-machine interaction
• Voice, gestures, tactile, ...
• Augmented by AR & VR interface capabilities

63. InfoSec
• Indispensable supplement for most needed technologies
• Cloud
• Wireless
• IoT
• Mobile
• ...
• Must be an integral part of all stages of the IT value chain

64. IT enabled trends

65. IT enabled trends
Artificial intelligence / deep learning
Internet of Things (including industry 4.0)
Maker movement (including 3D printing)
Blockchain
• Currently hyped topics with disruptive potential
• Actual future impact not yet clearly foreseeable

66. Evaluating your position
Finding out where you are and where you want to go

67. Step #1
Create a framework

68. Framework dimensions
• Work model evolution
• Technology evolution
• Programming model evolution

69. Dimension 1: Work model evolution

70. Remember this model?
Pre-industrial era
• No clear driver
Industrial era
• Cost-efficiency
• Scalability
• Repeatability
• Stability
• Efficiency & scale
Post-industrial era
• Cycle times
• Adaptability
• Flexibility
• Resilience
• Effectiveness & speed

71. This model can also be applied to IT

72. Properties
Pre-industrial
Industrial
Post-industrial
Market
Emerging market
Wide & slow market
Narrow & fast market
Strategic goal
None (“Just do it!”)
Cost-efficiency
Short cycle times
System theory
Simple
Complicated
Complex
Work model
Ad hoc
Processes
Collaboration
Organization model
Peer to peer
Hierarchies
Autonomous teams
Practices
“Whatever goes”
ITIL, V-Modell, SAFe
DevOps, Kanban, XP, Agile
Individuals
Experts (Cube-shaped)
Specialists (I-shaped)
Generalists (T-Shaped)
Automation
Low
Medium-high
Very high
Manual work
Ad hoc
Defined and controlled
Avoided
Programming model
Do it yourself
Standard Software,
Enterprise Frameworks
Cloud-native, Serverless,
Managed Services

73. Another, related point of view

74. Taking this “magic triangle” ...

75. Good
Fast
Cheap
Optimizing for quality and cycle times
will result in higher costs
Optimizing for quality and costs
will result in long cycle times
Optimizing for cycle times and costs
will result in reduced quality

76. ... will lead you to this model

77. You may pick
two
Good
Fast
Cheap
Industrial IT
Deliver large batches at minimized
costs towards slow markets
Post-industrial IT
Quickly adapt to ever-changing needs
of dynamic, fast-moving markets
Startup IT
Test hypotheses and pivot as fast as
possible to discover a product-market fit

78. You may pick
two
Good
Fast
Cheap
Industrial IT
Deliver large batches at minimized
costs towards slow markets
Post-industrial IT
Quickly adapt to ever-changing needs
of dynamic, fast-moving markets
Startup IT
Test hypotheses and pivot as fast as
possible to discover a product-market fit
This is not a pre-industrial IT model,
as it comes with a clear strategic
goal (“Discover product-market fit
as fast as possible”), still it usually
shares many of the other properties

79. You may pick
two
Good
Fast
Cheap
Industrial IT
Deliver large batches at minimized
costs towards slow markets
Post-industrial IT
Quickly adapt to ever-changing needs
of dynamic, fast-moving markets
Startup IT
Test hypotheses and pivot as fast as
possible to discover a product-market fit
1
2 3
Product evolution cycle

80. Work model evolution
• You can reason about the work model at different levels
• Company (Market)
• IT department
• Product/Project
• The work model for a given product will change over time
• You will need to figure out your preferred work model

81. Dimension 2: Technology evolution

82. Let us start with the disruptive technologies ...
Assembly
language
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
High-level
language
Algol
Lisp
Simula
Cobol
UNIX
Server
LAN
Personal
Computer
Standard
Software
OSS
WWW
Notebook
Smartphone
Cloud
Mobile
networks
(3G+)
Big Data
Tablet
Wi-Fi
SaaS
Serverless
FaaS +
Managed
services
PLC
Industrial
PC
OPC UA
IoT
Modem
9600+ Baud

83. ... aggregate them in groups ...
Assembly
language
1950
1960
1970
1980
1990
2000
2010
2020
Mainframe
Transistor
Multitasking
High-level
language
Algol
Lisp
Simula
Cobol
UNIX
Server
LAN
Personal
Computer
Standard
Software
OSS
WWW
Notebook
Smartphone
Cloud
Mobile
networks
(3G+)
Big Data
Tablet
Wi-Fi
SaaS
Serverless
FaaS +
Managed
services
PLC
Industrial
PC
OPC UA
IoT
Modem
9600+ Baud
Traditional
software
development
Industrial computing / IoT
Web
centered
Cloud native
Mobile
centered
Mobile centered
(Big & Fast) Data centered

84. ... add the trends ...
• Ambient computing
• Focus on frontends
• InfoSec
• Artificial intelligence / deep learning
• Maker movement (including 3D printing)
• Blockchain

85. ... and distill the major directions

86. Frontends as differentiators
• Mobile centered à Ambient computing
Backends as commodity
• Driven by cloud native (especially managed services)
Smart data
• Big/fast data & machine learning à deep learning à AI
Smart devices
• Industrial computing & IoT ß Maker movement
InfoSec
• Needed everywhere ß Blockchain
Traditional
• including web & mobile centered

87. Technology evolution
• All directions are interconnected
• Still, you will most likely need to focus on one direction
• As mastering all of them is too much for one person
• As architect, you will need to get a grasp of all directions
• Required to help your stakeholders making the best decisions
• Still, you should deep dive at least into one of the directions

88. Dimension 3: Programming model evolution

89. Let us take the programming models ...
DIY
Do It yourself
Web applications
Enterprise Frameworks
CORBA, SOA, JEE, .net, ...
IoT
Serverless
FaaS +
Managed
services
Cloud native
Microservices
?
Libraries &
Frameworks
Embedded computing
Standard software
customization
HPC
High Performance Computing
Local computing paradigm
Distributed computing paradigm

90. ... and aggregate them in groups
DIY
Do It yourself
Web applications
Enterprise Frameworks
CORBA, SOA, JEE, .net, ...
IoT
Serverless
FaaS +
Managed
services
Cloud native
Microservices
?
Libraries &
Frameworks
Embedded computing
Standard software
customization
HPC
High Performance Computing
Local computing paradigm
Distributed computing paradigm
No
paradigm
(random outcomes)
Distributed
computing
paradigm
Local
computing
paradigm
Embedded computing paradigm

91. ... and aggregate them in groups
DIY
Do It yourself
Web applications
Enterprise Frameworks
CORBA, SOA, JEE, .net, ...
IoT
Serverless
FaaS +
Managed
services
Cloud native
Microservices
?
Libraries &
Frameworks
Embedded computing
Standard software
customization
HPC
High Performance Computing
Local computing paradigm
Distributed computing paradigm
No
paradigm
(random outcomes)
Distributed
computing
paradigm
Local
computing
paradigm
Embedded computing paradigm
Transitioning to one of those
paradigms basically means
mostly re-learning how to
develop good software
Most people just do that
in a disguise if they claim
they do “microservices”
Smart device management
including edge computing
usually requires both
paradigms

92. Putting the framework together

93. Pre-industrial
Programming
model
Technology
Work model
Industrial
Startup
Post-industrial
Traditional
Backend
Frontend
Device
Data / AI
InfoSec
Ambient
AR/VR
Cloud native
Serverless
Industrial
IoT/Maker
Big/fast data
ML/DL
Everywhere
(Blockchain)
Random
Local computing
Distributed computing
Embedded computing
Known territory
New territory
C/S, Web
Mobile

94. Step #2
Locate your current position

95. Pre-industrial
Programming
model
Technology
Work model
Industrial
Startup
Post-industrial
Traditional
Backend
Frontend
Device
Data / AI
InfoSec
Ambient
AR/VR
Cloud native
Serverless
Industrial
IoT/Maker
Big/fast data
ML/DL
Everywhere
(Blockchain)
Random
Local computing
Distributed computing
Embedded computing
Known territory
New territory
C/S, Web
Mobile

96. Step #3
Find your desired position

97. Pre-industrial
Programming
model
Technology
Work model
Industrial
Startup
Post-industrial
Traditional
Backend
Frontend
Device
Data / AI
InfoSec
Ambient
AR/VR
Cloud native
Serverless
Industrial
IoT/Maker
Big/fast data
ML/DL
Everywhere
(Blockchain)
Random
Local computing
Distributed computing
Embedded computing
Known territory
New territory
C/S, Web
Mobile

98. Step #4
Define your personal evolution plan

99. Define your personal evolution plan
• Defining the plan is the easy part
• Read the literature, do the trainings, train your skills, ...
• Still, it will require time and discipline
• It’s a combination of personal and company game
• You cannot expect your company to cover all the efforts
• You will usually need to invest some of your private time
• And if your environment does not support you
• “Love it, change it, or leave it”
• Trade-offs are fine, but in the end they are your decision!

100. Staying ahead of the curve
Some general recommendations augmenting your path ahead

101. Understand post-industrial markets
• Speed trumps perfection – Rethink everything!
• Really, really understand the implications of uncertainty!
• Understand the difference between output and outcome
• Understand the ideas of bets and options
• Dismiss cargo-cult agility – learn what “Agile” really means
• It is a revolution in your head!
• But it should be an evolution regarding implementation
• Otherwise you will certainly overstrain your organization

102. Cross-functional teams
(organized by business capabilities)
Autonomy
(incl. E2E responsibility)
Decentralized control
Microservices
Continuous Delivery
Heterogeneity
Cloud and Containers
Resilience
Operations automation
Craftsmanship & mastery
Outcome-driven
Beyond budgeting
Feature flow
Lean EAM
Continuous improvement
T-Shaped people
(being empathic)
DevOps
Quick feedback loops
Curiosity

103. Master the timeless wisdom
• Especially master the foundations of good design
• “Loose coupling, high cohesion” & “separation of concerns”
• “Information hiding” especially with respect to API
• Domain-driven design can be a useful starting point
• Good design skills are more relevant than ever
• Affect understandability, changeability and extensibility
• Affect usability, stability and acceptance at API level
• Affect robustness, availability and scalability at runtime

104. “I would advise students to pay more attention to the
fundamental ideas rather than the latest technology.
The technology will be out-of-date before they graduate.
Fundamental ideas never get out of date.”
-- David L. Parnas (http://www.sigsoft.org/SEN/parnas.html)

105. Become T-shaped
• Generalists trump specialists
• Pure subject matter experts are an industrial concept
• Collaboration requires understanding your collaborators
• Leave your comfort zone once in a while
• Still, have your area of expertise
• Deep knowledge is still needed – but in a inclusive way
• Understand the business domain
• This is what turns you into a “ten times developer”

106. Learn frontend development ...
• Learn JavaScript – really!
• Embrace the concepts of UX and UI design
• Understand CSS at least a bit
• Start picking up the concepts of ambient computing
• Voice-based UI, Video-based UI, AR, VR, etc.

107. ... or embrace cloud native ...
• Understand and learn what “cloud” means today!
• Understand the concepts of “serverless”
• Know the relevant managed service offerings (BaaS/SaaS)
• Automate everything using managed services
• Understand operation needs (especially monitoring) ...
• ... and what existing solutions (managed services) offer
• Abandon DIY and NIH
• Actively reduce vertical integration depth

109. ... or try a different direction
• Smart Data
• Will heavily shape future decision making processes
• Be prepared to refresh your math
• Smart Devices
• Fast and wild evolution at the moment
• Lots of exciting challenges – if you like it
• InfoSec
• Needed everywhere – yet treated often like an unloved chore
• Must become an integral part of development and operations

110. Embrace distributed systems
“(Almost) every system is a distributed system” -- Chas Emerick
“Everything fails, all the time” -- Werner Vogels
• Understand the non-determinism of distributed systems
• “Memory, guesses and apologies” & promise theory
• Understand that infrastructure cannot guarantee robustness

111. Wrap-up

112. Wrap-up
• Moving from an industrial to a post-industrial domain
• Technology and trends revealing new directions
• Programming goes distributed and embedded
• Generalists trump specialists
• Timeless wisdom as a game changer
• Assess where you are and where you want to be
• Love it, change it, or leave it

114. Uwe Friedrichsen
IT traveller.
Connecting the dots.
Attracted by uncharted territory.
CTO at codecentric.
https://www.slideshare.net/ufried
https://medium.com/@ufried
@ufried