1 What is Platform Engineering?

Interest in platform engineering has surged, but definitions vary. This chapter frames it as a product-minded, cross-disciplinary craft whose purpose is to help organizations deliver software rapidly and safely despite expanding technology, governance, and security demands. Dedicated platform teams build an internal engineering platform that gives development teams self-service access to the tools and infrastructure needed to create, release, and operate software, reducing non-development toil and cognitive load. Success is measured by business outcomes and observable metrics, with impacts including faster time-to-market, better quality and security, lower cost, and an improved developer experience—benefits that apply to enterprises and startups alike.

The chapter argues this approach goes beyond tool-centric DevOps rollouts that often recreate silos and bottlenecks. Treating internal capabilities as products—accessible through clear APIs and designed for self-service—replaces ticket queues with autonomous workflows while still meeting compliance needs. Platform principles should be adopted as soon as strategically valuable software work emerges, and used more selectively when custom software is not core to value creation. A product delivery model and domain-driven design organize the platform into coherent domains with well-designed boundaries so multiple teams can evolve the platform independently while maintaining a consistent developer experience.

Seven engineering principles guide every capability: make everything software-defined; deliver self-serve, API-first experiences; design for evolutionary architecture; prove value with metrics across the end-to-end flow; build in security, compliance, and resiliency through a shared responsibility model; automate governance with compliance at the point of change; and ensure deep observability. Enablers include a clear Developer Experience focus, DevOps as a culture of end-to-end ownership (not a team), and Site Reliability Engineering as a time-boxed reliability improvement practice, with generative AI accelerating but not replacing expert judgment. A running case study introduces a company mired in handoffs and fragmented pipelines, setting up how a well-designed platform can consolidate requirements, restore developer autonomy, and sustainably improve delivery.

Companies adopting a DevOps culture often start by enabling development teams to deploy their own infrastructure.

Platform engineers, working as unified product teams, build and deliver a product that provides internal development teams with the things they need to do their job.

Platform engineering depends on the disciplined application of a Product Delivery Model. Product management drives decisions about the product’s capabilities, features, and experiences. Effective platform engineering principles enable us to deliver capabilities, features, and experiences more successfully. Identifying and architecting around the internal Product Domains of our platform is how we successfully sustain the user experience as the product evolves and scales.

Eight principal product domains within an engineering platform. The numbers by the domain indicate an underlying dependency ordering when launching a new platform.

Software Defined is placed in the middle because it is a core attribute of everything the platform engineer delivers. The rest of the principles share a connection because they continuously evolve, and decisions made in applying these surrounding principles can impact the requirements of the others.

There is a direct connection between each of these enablers and the resulting quality and impact of a platform.

Infrastructure-oriented changes can go through as many as four handoffs by the time they reach the team that actually does the work. Each of these teams is only allowed to optimize a process within its own team’s scope of responsibilities.

The application deployment process is fragmented, with multiple teams owning various requirements. A pipeline has been created to automate several steps, but a separate team also owns this process. A release can sometimes take weeks to complete.

• Platform Engineering is a craft composed of the architectural, engineering, and product delivery disciplines applied by dedicated engineering teams in an Engineering Platform's ideation, creation, delivery, and evolution.
• Effective platform engineering teams will work to deliver engineering platforms that provide internal software development teams with self-managed and seamless access to the tools and technologies they need to innovate, create, release, and operate their software without the usual toil, delays, and cognitive load.
• Applied well, there is significant waste that can be removed from the development lifecycle by providing developers with an effective engineering platform.
• Platform engineering principles and practices should be adopted as early as possible once an organization identifies strategic business value in custom software development.
• Platform engineering teams are software engineering teams that deliver internal products to stakeholders and users throughout the organization.
• Platform engineering requires a strategic approach with a product mindset to differentiate it from developing automation that can improve productivity.
• The development and delivery of engineering platforms should follow domain-driven design principles.
• Implemented correctly, platform engineering is neither a buzzword nor a replacement for the cultural paradigm of DevOps or the principles of Developer experience or the practice of Site reliability engineering.
• Generative AI helps identify critical areas for platform strategy improvement (planning, design, testing, etc.) and accelerates these phases through automation and prediction.

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