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The Platform Engineer's Handbook

The Platform Engineer's Handbook

By : Ajay Chankramath
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The Platform Engineer's Handbook

The Platform Engineer's Handbook

By: Ajay Chankramath

Overview of this book

The Platform Engineer’s Handbook equips senior engineers and DevOps professionals to deliver developer-friendly infrastructure with automation, speed, AI acceleration, and intelligence. Starting with a blank slate, you’ll build a complete, modern platform that runs locally on your laptop, learning real-world patterns as you go. In this handbook, you’ll follow a structured, progressive journey, beginning with source control governance and branching strategies, then deploying a Kubernetes-based runtime, embedding observability, and securing platform access. You’ll implement self-service onboarding, CI/CD as a service, and developer portals with Backstage. Later chapters introduce infrastructure blueprints, policy as code, FinOps observability, and AI-augmented platform services such as agent-based onboarding and copilots for pipeline creation. Each chapter combines core concepts, lab-based exercises, and production-ready best practices to provide a comprehensive understanding of the subject matter. By the end, you'll have a working MVP platform and the skills to adapt and scale it for your team or organization.
Table of Contents (21 chapters)
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1
Part 1: Designing, Building, and Deploying the Core Engineering Platform
7
Part 2: Enhancing Productivity Through Self-Service Functions
13
Part 3: Scaling, Maturing, and Evolving Your Platform
20
Index

14

Agentic and AI-Augmented platforms

Over the past several chapters, we have discussed everything from setting up the foundations, focusing on the building blocks and scaling our engineering platforms to the best possible outcome for all the consumers. As the last step in that process, we will explore how Agentic and AI-Augmented platforms are reshaping platform engineering by reducing the cognitive load of the consumers and the ability of the platform engineers to build them more effectively. For example, the transition from observability-driven operations to AI-Augmented platforms represents a significant maturation of the outcomes, but the end goals do not change while doing so. At NewTech, Maria's team had a challenge that highlighted this transition. Even with the tremendous amount of data her team was collecting and harnessing, critical issues were still creeping through. This was a challenge mainly because of the sheer volume of data as well as the lack of ability...

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The Platform Engineer's Handbook
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