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Architecture as Code (Understanding Qualitative Trade-Offs)

List Price: $69.99
SKU:
9798341640382
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25 unit(s)
Expected release date is Dec 1st 2026
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  • Product Details

    Author:
    Neal Ford, Mark Richards
    Format:
    Paperback
    Pages:
    550
    Publisher:
    O'Reilly Media (December 1, 2026)
    Imprint:
    O'Reilly Media
    Release Date:
    December 1, 2026
    Language:
    English
    ISBN-13:
    9798341640382
    Weight:
    16oz
    Dimensions:
    7" x 9.19"
    File:
    TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20260330163216-20260330.xml
    Folder:
    TWO RIVERS
    List Price:
    $69.99
    Country of Origin:
    United States
    Pub Discount:
    60
    Case Pack:
    16
    As low as:
    $60.19
    Publisher Identifier:
    P-PER
    Discount Code:
    C
  • Overview

    Most software architectures are still expressed in static diagrams and documents that can't be tested or automatically verified. As organizations grow, this gap between design and implementation leads to drift, manual governance, and mounting complexity. Architecture as Code offers a new approach: defining architecture itself in executable form.

    Acclaimed software architects Neal Ford and Mark Richards present a practical framework for treating architecture like source code—using fitness functions and automated feedback to define structure, constraints, governance, security, and communication across the entire organization. By capturing these intersections in code, teams can continuously validate alignment with technical and business goals, reduce risk, and evolve systems with confidence.

    This is your go-to guide for making architecture measurable, verifiable, and adaptable at scale. With clear examples and proven practices, this book shows you how to:

    • Define architectural decisions and constraints as code
    • Continuously test and validate architecture across implementation, infrastructure, and teams
    • Align architecture with business objectives and compliance requirements
    • Establish a governance mesh that unifies constraints across multiple intersection points
    • Leverage generative AI to help craft and evolve fitness functions