Optimizing the Delivery Pipeline for Flow

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The document discusses optimizing the software delivery pipeline using lean principles. It defines the delivery pipeline as a subset of the overall value stream. Key aspects covered include identifying types of waste, establishing base performance metrics like deployment frequency and change failure rate, 12 specific devops flow metrics, and techniques for enabling smooth flow like transparency, pull-based flows, and on-demand resources. It emphasizes the importance of measurement for management but cautions against the myth that what can't be measured can't be managed.

Software

@antweiss
Framing
In social theory, framing is a schema of
interpretation, a collection of anecdotes
and stereotypes, that individuals rely on
to understand and respond to events.

@antweiss
The Delivery Pipeline
Is Just a Subset
Of Our Value Stream

@antweiss
APPLYING Lean Principles
• Make Work Visible
• Limit WIP
• Reduce Batch Sizes
• Reduce the Number of Handoffs
• Continuously Identify and Elevate Constraints
• Eliminate Waste

@antweiss
Types Of Waste in Software Delivery
• Partially Done Work
• Extra Processes
• Extra Features
• Task Switching (Up to 50% loss in productivity)
• Waiting
• Motion
• Defects
• Non-standard or Manual Work
• Heroics

@antweiss
Base Performance Metrics
1. Deployment Frequency
2. Lead Time for Changes
3. Mean time To Restore Service
4. Change Failure Rate

@antweiss
12 Devops Flow Metrics
http://devopsflowmetrics.org

@antweiss
VELOCITY METRICS
1. MLT - Mean Lead Time
2. DCR - Daily Change Rate
3. MTTE - Mean Time To Environment
4. MTTD - Mean Time To Detect
5. MTTR - Mean Time To Resolve
6. MTTA - Mean Time To Approve

@antweiss
QUALITY METRICS
1. BFR - Build Failure Rate
2. DFR - Deployment Failure Rate
3. IRFR - Infrastructure-Related Failure Rate
4. RWR - ReWork Rate
5. ADR - Automated Detection Rate
6. UWR - Unplanned Work Rate

@antweiss
Flow-Enabling Techniques
● Transparency (O11y)
● Self-service infrastructure
● Pull-based ﬂows
● Asynchronous Communication & Execution
● Event Driven
● On-Demand Resources + Resource Pooling

@antweiss
WARNing
It is wrong to suppose that
if you can’t measure it, you can’t
manage it
– a costly myth.
W.E.Deming

@antweiss
Thank You!
@antweiss
@otomato_sw
https://otomato.link
https://devopstrain.pro

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Optimizing the Delivery Pipeline for Flow

1. @antweiss Optimizing the delivery Pipeline for Flow Anton Weiss, Otomato Software Delivery @antweiss http://otomato.link

2. @antweiss

3. @antweiss Framing In social theory, framing is a schema of interpretation, a collection of anecdotes and stereotypes, that individuals rely on to understand and respond to events.

8. @antweiss The Delivery Pipeline Is Just a Subset Of Our Value Stream

9. @antweiss Where do we start?

10. @antweiss Where do we end?

11. MEASUREMENTS?

12.

13. @antweiss FLOW

14. @antweiss APPLYING Lean Principles • Make Work Visible • Limit WIP • Reduce Batch Sizes • Reduce the Number of Handoffs • Continuously Identify and Elevate Constraints • Eliminate Waste

15. @antweiss Types Of Waste in Software Delivery • Partially Done Work • Extra Processes • Extra Features • Task Switching (Up to 50% loss in productivity) • Waiting • Motion • Defects • Non-standard or Manual Work • Heroics

16. @antweiss Base Performance Metrics 1. Deployment Frequency 2. Lead Time for Changes 3. Mean time To Restore Service 4. Change Failure Rate

17. @antweiss 12 Devops Flow Metrics http://devopsflowmetrics.org

18. @antweiss VELOCITY METRICS 1. MLT - Mean Lead Time 2. DCR - Daily Change Rate 3. MTTE - Mean Time To Environment 4. MTTD - Mean Time To Detect 5. MTTR - Mean Time To Resolve 6. MTTA - Mean Time To Approve

19. @antweiss QUALITY METRICS 1. BFR - Build Failure Rate 2. DFR - Deployment Failure Rate 3. IRFR - Infrastructure-Related Failure Rate 4. RWR - ReWork Rate 5. ADR - Automated Detection Rate 6. UWR - Unplanned Work Rate

20. @antweiss Example

21. @antweiss Flow-Enabling Techniques ● Transparency (O11y) ● Self-service infrastructure ● Pull-based ﬂows ● Asynchronous Communication & Execution ● Event Driven ● On-Demand Resources + Resource Pooling

22. @antweiss WARNing It is wrong to suppose that if you can’t measure it, you can’t manage it – a costly myth. W.E.Deming

23. @antweiss WARNing It is wrong to suppose that if you can’t measure it, you can’t manage it – a costly myth. W.E.Deming

24. @antweiss Thank You! @antweiss @otomato_sw https://otomato.link https://devopstrain.pro

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