Platform Engineering in Practice : Build internal Developer Platform from Empty Clusters to Self-Service Delivery, Observability, and AI-Assisted Operations
Language: English
Published by Gitforgits, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
US$ 98.52
Quantity: 2 available
Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - At some point, every software engineering organisation hits a point where shipping software feels like it's taking longer than writing it. So, developers are waiting days for a database, environments are drifting apart, and every team is deploying in its own way. This book shows you how to do that, one working layer at a time.In this book, you'll get to build a complete internal developer platform using tools you can run on a single Linux workstation. The plan is to provision multi-cluster infrastructure with OpenTofu, wire GitOps delivery with Argo CD, design a self-service component API with Kubebuilder and Crossplane, enforce policy with Kyverno and Cilium, and add observability and a Backstage portal that cuts onboarding from weeks to minutes. Then you'll adopt OpenChoreo and use it with custom component types, promotion pipelines, multi-cluster data planes, and AI agents connected through MCP.Out of the book, about 40% is about the thinking behind it, and the rest is all about putting it into practice. The idea is to make you capable and skilled to design, build, secure, measure and grow a platform that developers will actually use.Key LearningsProvision multi-cluster Kubernetes foundations with OpenTofu modules, gateways, and shared secret stores.Deliver change through GitOps with Argo CD, ApplicationSets, and progressive rollouts.Design single-file component API that hides Kubernetes detail from developers.Provision databases on demand with Crossplane compositions and a custom operator.Enforce security baselines through Kyverno policies, signed images, and zero-trust network rules.Instrument services with OpenTelemetry, and reuse dashboards, SLOs, burn-rate alerts.Speedup onboarding using Backstage templates, catalog entities, and TechDocs.Operate OpenChoreo with custom component types, traits, and promotion pipelines.Run dedicated production data planes across clusters using outbound cluster agents.Grow adoption voluntarily, score platform maturity, and prove ROI to leadership.Table of ContentWhy Platform Engineering ExistsThinking Like a Platform TeamArchitecting Internal Developer PlatformBuilding Foundation LayerGitOps and Delivery PipelinesSelf-Service and Platform APIsGuardrails, Security and GovernanceObservability and Developer PortalsOpenChoreo as Reference OutcomeOperating OpenChoreoScaling Platform AdoptionTarget AudienceIf you know to ship software, and have worked around Git, containers and the Linux command line, then this book is well-suited for you. No prior work with the platform tools is expected, although some knowledge of Kubernetes helps.…
Seller Inventory # 9788117136034
- Title
- Platform Engineering in Practice : Build internal Developer Platform from Empty Clusters to Self-Service Delivery, Observability, and AI-Assisted Operations
- Author
- Zebb Wright
- Publisher
- Gitforgits
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 8117136031
- ISBN 13
- 9788117136034
- Item weight
- 643 grams
- Dimensions
- 235x191x19 mm
At some point, every software engineering organisation hits a point where shipping software feels like it's taking longer than writing it. So, developers are waiting days for a database, environments are drifting apart, and every team is deploying in its own way. This book shows you how to do that, one working layer at a time.
In this book, you'll get to build a complete internal developer platform using tools you can run on a single Linux workstation. The plan is to provision multi-cluster infrastructure with OpenTofu, wire GitOps delivery with Argo CD, design a self-service component API with Kubebuilder and Crossplane, enforce policy with Kyverno and Cilium, and add observability and a Backstage portal that cuts onboarding from weeks to minutes. Then you'll adopt OpenChoreo and use it with custom component types, promotion pipelines, multi-cluster data planes, and AI agents connected through MCP.
Out of the book, about 40% is about the thinking behind it, and the rest is all about putting it into practice. The idea is to make you capable and skilled to design, build, secure, measure and grow a platform that developers will actually use.
Key Learnings
- Provision multi-cluster Kubernetes foundations with OpenTofu modules, gateways, and shared secret stores.
- Deliver change through GitOps with Argo CD, ApplicationSets, and progressive rollouts.
- Design single-file component API that hides Kubernetes detail from developers.
- Provision databases on demand with Crossplane compositions and a custom operator.
- Enforce security baselines through Kyverno policies, signed images, and zero-trust network rules.
- Instrument services with OpenTelemetry, and reuse dashboards, SLOs, burn-rate alerts.
- Speedup onboarding using Backstage templates, catalog entities, and TechDocs.
- Operate OpenChoreo with custom component types, traits, and promotion pipelines.
- Run dedicated production data planes across clusters using outbound cluster agents.
- Grow adoption voluntarily, score platform maturity, and prove ROI to leadership.
Table of Content
- Why Platform Engineering Exists
- Thinking Like a Platform Team
- Architecting Internal Developer Platform
- Building Foundation Layer
- GitOps and Delivery Pipelines
- Self-Service and Platform APIs
- Guardrails, Security and Governance
- Observability and Developer Portals
- OpenChoreo as Reference Outcome
- Operating OpenChoreo
- Scaling Platform Adoption
Target Audience
If you know to ship software, and have worked around Git, containers and the Linux command line, then this book is well-suited for you. No prior work with the platform tools is expected, although some knowledge of Kubernetes helps.
"Synopsis" may belong to another edition of this title.
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