This document summarizes Tim Sheiner's presentation on how a UX designer can apply their design process to understand DevOps teams and help solve their problems. The UX designer uses personas, mental models, analogies and prototypes to communicate effectively with operations teams. They learn about the teams' perspectives through interviews and observation. Prototypes help establish a shared understanding of problems and iterate on solutions collaboratively and at low risk. The goal is for the UX designer to become a modeler who can effectively communicate and work with operations teams using models.

1. When UX (guy) Meets Operations
Tim Sheiner
Velocity Conference
27 May 2015

2. When UX guy meets DevOps
2

3. ?
When UX guy meets DevOps
2
DevOps
, he has a lot to learn

4. He uses a time-tested design process
1. Personas
2. Mental Model
3. Analogy
4. Prototype
3

5. What are personas?
Personas are fictitious characters that are used to help teams design products.
• Personas are as fake and as real as the characters in your favorite TV show.
• They don’t actually exist, and yet, you learn to care about them and have many of the
same expectations about them as the real people in your life.
4

6. Why personas?
Personas were created to address a too common product design communication
problem.
5
Users want
feature x.
Nope.

7. Why personas?
The human instinct for empathy means we know how to share ideas about the behavior of
people we know in common.
6
Kyle wants
feature x.
Yup.

8. We use personas to tell product stories
To help us create an accountable connection between the needs we gather during
research and the agile stories we implement.
7
Mental Model
validate
iterate
Features
Prototypes
validate
iterate

9. DevOps Persona
8
Customers
System
Increase capacity and resilience of
the System
Protect the System
Use the System to deliver
features to customers
Future System
Thomas - The Architect
Kyle - The Ops Guy
Jenny - The Dev Gal

10. What is their
mental model of the
system?
9
System
Thomas - The Architect
Kyle - The Ops Guy
Jenny - The Dev Gal

11. Mental models help us understand the world.
10
Illustration and argument from Hugh Dubberly, Models of Models, 2009

12. Mental models help us make sense of things.
11
Illustration and argument from Hugh Dubberly, Models of Models, 2009

13. We use mental models to make decisions.
12
Illustration and argument from Hugh Dubberly, Models of Models, 2009

14. Mental models are the basis for learning.
13
Illustration and argument from Hugh Dubberly, Models of Models, 2009

15. Mental models are the basis for learning.
13
Illustration and argument from Hugh Dubberly, Models of Models, 2009

16. We learn relative to our existing models.
14
Illustration and argument from Hugh Dubberly, Models of Models, 2009

17. We communicate by telling stories about models.
15
Illustration and argument from Hugh Dubberly, Models of Models, 2009

18. Before I understand the jargon, descriptions don’t help much.
16
Kyle, tell me about
the system.
System

19. Before I understand the jargon, descriptions don’t help much.
16
Blah blah data center blah blah
microservices blah blah high
availability blah blah ipsec mesh
blah blah horizontal duplication
blah blah…
System

20. Stories about challenges are the thing.
17
Kyle, tell me a story
about what happens
when you get an
alert?
System

21. In Kyle’s model the ops space has 3 dimensions!
18
1. Who is being affected?
2. How are they being affected?
3. How long have they been
affected?
Services - Logical
Hardware - Physical
Time
Customers

22. In Kyle’s model the ops space has 3 dimensions!
18
1. Who is being affected?
2. How are they being affected?
3. How long have they been
affected?
Services - Logical
Hardware - Physical
Time
Customers
Keep going, what
happens next?

23. Stories in this space are about nested operation sequences.
19
Log In Stream MediaMedia Query
1. Applications

24. Stories in this space are about nested operation sequences.
19
Log In Stream MediaMedia Query
Parse Optimize
Build Execution
Plan
Run Plan
Syntax Check
Semantic
Check
Shared Pool
Check
SC 1 SC 2 SC 3
Services - Logical
Hardware - Physical
1. Applications
2. Nested Services &
sub-services
3. Steps are
transactions
4. Logical to Physical
Return Results

25. To me, the model is sensible but novel.
20
Hmm.
Services, steps,
transactions…

26. I find a familiar model by analogy.
21
Oh!
I see. Like Fedex!
Sure.

27. I need to validate that I understand the model.
22
Illustration and argument from Hugh Dubberly, Models of Models, 2009

28. The Power of Analogy
Analogy is a critical design thinking method.
• A way to validate congruence in mental models
• A method to bring past experience to bear on present
circumstances
• A source of inspiration for developing solutions
23
Design by Analogy - Georgia Tech - KBAI:

29. This is inspiration for a prototype.
24

30. What is a prototype?
Prototypes are simple, focused, tools for testing
ideas visually.
• every prototype has a specific learning
objective
• prototype scope is the simplest thing you can
create to achieve that objective
• a series of prototypes can be used to iterate
towards a final solution
25
http://zurb.com/word/prototyping
http://boltgroup.com/product/work-product/studies-product/kobalt-
tools-product#.VWXzi1xVhBc
https://www.behance.net/gallery/4323339/iPhone-App-ConceptPrototype
http://www.infoq.com/articles/guest-simon-sketchflow

31. I want to test an experience based on this model
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32. //jut.io
Dashboard
Last 24 hours
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Blog Community Documentation 27
Service Monitor
Hardware Health
Customer KPIs
Service Monitor
Visitors
TotalVisitors(x1000)
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TotalStreams(x1000)
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06:00 10:00 14:00 18:00 22:00 02:00 06:00
Login Success Rate
99%
Media Query Execution Time
800ms
Stream Lag Ratio
2%

33. //jut.io
Dashboard
Last 24 hours
Canvas Admin
Blog Community Documentation 27
Service Monitor
Hardware Health
Customer KPIs
Service Monitor
Visitors
TotalVisitors(x1000)
0
5
11
16
06:00 10:00 14:00 18:00 22:00 02:00 06:00
Streams
TotalStreams(x1000)
0
5
9
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06:00 10:00 14:00 18:00 22:00 02:00 06:00
Login Success Rate
99%
Media Query Execution Time
800ms
Stream Lag Ratio
2%

34. //jut.io
Dashboard
Last 24 hours
Canvas Admin
Blog Community Documentation 28
Service Monitor
Visitors
TotalVisitors(x1000)
0
5
11
16
06:00 10:00 14:00 18:00 22:00 02:00 06:00
Streams
TotalStreams(x1000)
0
5
9
14
06:00 10:00 14:00 18:00 22:00 02:00 06:00
Login Success Rate
99%
Media Query Execution Time
800ms
Stream Lag Ratio
2%
Service Monitor
Hardware Health
Customer KPIs

35. //jut.io
Canvas Admin
Last 24 hours
Dashboard
Blog Community Documentation 29
Service Monitor > Query ServiceService Monitor
Login Service
Query Service
Streaming Service
Hardware Health
Customer KPIs
Query Steps/Time (ms) by Region
Step Americas EU APAC
Parse 120 1200 130
Optimize 120 120 100
Build Plan 100 100 100
Run Plan 90 90 90
Return Results 60 60 80
Query Steps = average for last month
Optimize Run Plan Return ResultsBuild Execution PlanParse

36. //jut.io
Canvas Admin
Last 24 hours
Dashboard
Blog Community Documentation 29
Service Monitor > Query ServiceService Monitor
Login Service
Query Service
Streaming Service
Hardware Health
Customer KPIs
Query Steps/Time (ms) by Region
Step Americas EU APAC
Parse 120 1200 130
Optimize 120 120 100
Build Plan 100 100 100
Run Plan 90 90 90
Return Results 60 60 80
Query Steps = average for last month
Optimize Run Plan Return ResultsBuild Execution PlanParse

37. //jut.io
Canvas Admin
Last 24 hours
Dashboard
Blog Community Documentation 30
Service Monitor > Query ServiceService Monitor
Login Service
Query Service
Streaming Service
Hardware Health
Customer KPIs
Query Steps/Time (ms) by Region
Step Americas EU APAC
Parse 120 1200 130
Optimize 120 120 100
Build Plan 100 100 100
Run Plan 90 90 90
Return Results 60 60 80
Query Steps = average for last month
Optimize Run Plan Return ResultsBuild Execution PlanParse

38. //jut.io
Canvas Admin
Last 24 hours
Dashboard
Blog Community Documentation 31
Service Monitor > Query Service > ParseService Monitor
Login Service
Query Service
Parse
Optimize
Build Plan
Run Plan
Return
Streaming Service
Hardware Health
Customer KPIs
Parsing Service Steps = average for last month
Syntax Check Semantic Check Shared Pool Check
Syntax Check Shared Pool CheckPOP Semantic Check
ENG1
ENG2
FR1
GER1
IR1
ITA2
SPA1
SPA2
40
30
3500
30
30
40
45
45
Physical location
London, England
Bristol, England
Paris, France
Berlin, Germany
Dublin, Ireland
Milan, Italy
Madrid, Spain
Barcelona, Spain
40
30
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EURegion

39. //jut.io
Canvas Admin
Last 24 hours
Dashboard
Blog Community Documentation 31
Service Monitor > Query Service > ParseService Monitor
Login Service
Query Service
Parse
Optimize
Build Plan
Run Plan
Return
Streaming Service
Hardware Health
Customer KPIs
Parsing Service Steps = average for last month
Syntax Check Semantic Check Shared Pool Check
Syntax Check Shared Pool CheckPOP Semantic Check
ENG1
ENG2
FR1
GER1
IR1
ITA2
SPA1
SPA2
40
30
3500
30
30
40
45
45
Physical location
London, England
Bristol, England
Paris, France
Berlin, Germany
Dublin, Ireland
Milan, Italy
Madrid, Spain
Barcelona, Spain
40
30
30
30
30
40
45
45
40
30
30
30
30
40
45
45
EURegion

40. //jut.io
Canvas Admin
Last 24 hours
Dashboard
Blog Community Documentation 32
Service Monitor > Query Service > ParseService Monitor
Login Service
Query Service
Parse
Optimize
Build Plan
Run Plan
Return
Streaming Service
Hardware Health
Customer KPIs
Parsing Service Steps = average for last month
Syntax Check Semantic Check Shared Pool Check
Syntax Check Shared Pool CheckPOP Semantic Check
ENG1
ENG2
FR1
GER1
IR1
ITA2
SPA1
SPA2
40
30
3500
30
30
40
45
45
Physical location
London, England
Bristol, England
Paris, France
Berlin, Germany
Dublin, Ireland
Milan, Italy
Madrid, Spain
Barcelona, Spain
40
30
30
30
30
40
45
45
40
30
30
30
30
40
45
45
EURegion

41. //jut.io
Dashboard
Last 24 hours
Canvas Admin
Blog Community Documentation 33
Hardware Health > By POP
CPU
%Load
0
4
7
11
06:00 10:00 14:00 18:00 22:00 02:00 06:00
host 1 host 2 host 3 host 4 host 5 host 6
host 7 host 8
Memory
%Used
0
33
67
100
06:00 10:00 14:00 18:00 22:00 02:00 06:00
host 1 host 2 host 3 host 4 host 5 host 6
host 7 host 8
FR1POP
Service Monitor
Hardware Health
By Pop
By Host
Customer KPIs

42. The prototype moves the conversation forward.
34
Hmmm. OK.
Interesting.
Not entirely plausible.

43. Why prototype?
Prototypes improve communication.
• They produce a shared reference for communication
• They encourage thinking in terms of stories
• They bring attention to interaction
35
Beginning Middle End

44. The design process creates a conversation around value.
By iterating models, the UX guy learns how to build tools for the Ops guy.
36
Features
validate
iterate
validate
iterate

45. How can you use this process?
1. Learn about your customers
2. Understand their perspectives
3. Find a shared understanding of the problem
4. Use a low risk, collaborative method to get to a solution
38

46. Learn about your customers
1. Ask to interview them
1. Ask about their role
2. Ask about the background on their need
3. Ask them to describe success
2. Observe
1. Ask them to show you how they work
2. Pay attention to the difference between what they say and what they do
39

47. Understand their perspective
1. Be humble
2. There are no dumb questions
3. Get them telling stories about their work, about challenges
4. Visualize your understanding
40

48. Find a shared understanding of the problem
1. Focus on understanding the problem first
2. Search for analogous problems
3. Use analogy to restate the problem
4. Validate that your customer agrees with the restatement
41

49. Use a low risk, collaborative method to get to a solution
1. Define learning objectives for each prototype or iteration
2. Use the lowest fidelity approach that captures the detail you need to understand
3. Tell stories with and about your prototype
4. Share your prototypes and encourage feedback
42

50. Be a modeler!
Use models to communicate.
• Recognize models
• Build models
• Draw models
• Share models
• Talk about models
43

51. At Jut these we are using these design practices
to build an operations data hub for unified
analytics on logs, metrics and events.
Check it out at www.jut.io and let me know what
you think.
Tim Sheiner
@tsheiner
44