Team Topologies: Organizing Business and Technology Teams for Fast Flow

Team Topologies: Organizing Business and Technology Teams for Fast Flow

by Matthew Skelton, Manuel Pais, Ruth Malan

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In Team Topologies DevOps consultants Matthew Skelton and Manuel Pais share secrets of successful team patterns and interactions to help readers choose and evolve the right team patterns for their organization, making sure to keep the software healthy and optimize value streams.

Team Topologies will help readers discover:

• Team patterns used by successful organizations.

• Common team patterns to avoid with modern software systems.

• When and why to use different team patterns

• How to evolve teams effectively.

• How to split software and align to teams.

Product Details

ISBN-13: 9781942788829
Publisher: IT Revolution Press
Publication date: 09/17/2019
Sold by: Barnes & Noble
Format: NOOK Book
Pages: 240
Sales rank: 477,586
File size: 6 MB

About the Author

MATTHEW SKELTON has been building, deploying, and operating commercial software systems since 1998. Head of Consulting at Conflux, he specializes in Continuous Delivery, operability and organization design for software in manufacturing, ecommerce, and online services, including cloud, IoT, and embedded software. He currently lives in the UK.

MANUEL PAIS is a DevOps and Delivery Coach and Consultant, focused on teams and flow first. He helps organizations adopt test automation and continuous delivery, as well as understand DevOps from both technical and human perspectives. Manuel has been in the industry since 2000, having worked in Belgium, Portugal, Spain, and the UK. He currently lives in Madrid, Spain.

Table of Contents

Figures & Tables
Case Studies & Industry Examples
Foreword by Ruth Malan

Chapter 1: The Problem with Org Charts
Communication Structures of an Organization
Team Topologies: A New Way of Thinking about Teams
The Revival of Conway's Law
Cognitive Load and Bottlenecks
Summary: Rethink Team Structures, Purpose, and Interactions
Chapter 2: Conway's Law and Why It Matters
Understanding and Using Conway's Law
The Reverse Conway Maneuver
Software Architectures that Encourage Team-Scoped Flow
Organization Design Requires Technical Expertise
Restrict Unnecessary Communication
Beware: Naive Uses of Conway's Law
Summary: Conway's Law Is Critical for Efficient Team Design in Tech
Chapter 3: Team-First Thinking
Use Small, Long-Lived Teams as the Standard
Good Boundaries Minimize Cognitive Load
Design “Team APIs” and Facilitate Team Interactions
Warning: Engineering Practices Are Foundational
Summary: Limit Teams' Cognitive Load and Facilitate Team Interactions to Go Faster

Chapter 4: Static Team Topologies
Team Anti-Patterns
Design for Flow of Change
DevOps and the DevOps Topologies
Successful Team Patterns
Considerations When Choosing a Topology
Use DevOps Topologies to Evolve the Organization
Summary: Adopt and Evolve Team Topologies that Match Your Current Context
Chapter 5: The Four Fundamental Team Topologies
Stream-Aligned Teams
Enabling Teams
Complicated-Subsystem Teams
Platform Teams
Avoid Team Silos in the Flow of Change
A Good Platform Is “Just Big Enough”
Convert Common Team Types to the Fundamental Team Topologies
Summary: Use Loosely Coupled, Modular Groups of Four Specific Team Types
Chapter 6: Choose Team-First Boundaries
A Team-First Approach to Software Responsibilities and Boundaries
Hidden Monoliths and Coupling
Software Boundaries or “Fracture Planes”
Real-World Example: Manufacturing
Summary: Choose Software Boundaries to Match Team Cognitive Load

Chapter 7: Team Interaction Modes
Well-Defined Interactions Are Key to Effective Teams
The Three Essential Team Interaction Modes
Team Behaviors for Each Interaction Mode
Choosing Suitable Team Interaction Modes
Choosing Basic Team Organization
Choose Team Interaction Modes to Reduce Uncertainty and Enhance Flow
Summary: Three Well-Defined Team Interaction Modes
Chapter 8: Evolve Team Structures with Organizational Sensing
How Much Collaboration Is Right for Each Team Interaction?
Accelerate Learning and Adoption of New Practices
Constant Evolution of Team Topologies
Combining Teams Topologies for Greater Effectiveness
Triggers for Evolution of Team Topologies
Self Steer Design and Development
Summary: Evolving Team Topologies
Conclusion: The Next-Generation Digital Operating Model
Four Team Types and Three Interaction Modes
Team-First Thinking: Cognitive Load, Team API, Team-Sized Architecture
Strategic Application of Conway's Law
Evolve Organization Design for Adaptability and Sensing
Team Topologies Alone Are Not Sufficient for IT Effectiveness
Next Steps: How to Get Started with Team Topologies

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