When UX (guy) Meets Operations
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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.
When UX (guy) Meets Operations
- 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 鍖ctitious 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 dont 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 dont help much. 16 Kyle, tell me about the system. System
- 19. Before I understand the jargon, descriptions dont 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 Kyles 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 Kyles 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 speci鍖c 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 鍖nal 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 26
- 32. //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 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%
- 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 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%
- 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 30 30 30 40 45 45 40 30 30 30 30 40 45 45 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 鍖rst 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. De鍖ne learning objectives for each prototype or iteration 2. Use the lowest 鍖delity 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