Platform Engineering for Architects 1st Edition by Max Korbacher ISBN 1836203594 9781836203599 by Max Körbächer, Andreas Grabner, And Hilliary Lipsig instant download after payment.

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ISBN 10: 1836203594 
ISBN 13: 9781836203599
Author: Max Korbacher

Key Features
Comprehensive guide to designing platforms that create value and drive user adoption
Expert insights on shifting to a product-centric mindset for architects and platform teams
Best practices for managing platform complexity, reducing technical debt, and ensuring continuous evolution
Book Description
As technology evolves, IT talent shortages and system complexity make it essential to have structured guidance for building scalable, user-focused platforms. This book provides platform engineers and architects with practical strategies to develop internal development platforms that enhance software delivery and operations. You’ll learn how to identify end users, understand their needs, and define platform goals with a focus on self-service solutions for cloud-native environments. Using real-world examples, the book demonstrates how to build platforms within and for the cloud, leveraging Kubernetes. It also explores the benefits of a product-centric approach to platform engineering, emphasizing early end-user involvement and flexible design principles that adapt to future requirements. Additionally, the book covers techniques for maintaining a sustainable platform while minimizing technical debt. By the end, you’ll have the knowledge to design, define, and implement platform capabilities that align with your organization’s goals.
What you will learn
Make informed decisions aligned with your organization's platform needs
Identify missing platform capabilities and manage that technical debt effectively
Develop critical user journeys to enhance platform functionality
Define platform purpose, principles, and key performance indicators
Use data-driven insights to guide product decisions
Design and implement platform reference and target architectures
Who this book is for
This book is for platform engineers, architects, and DevOps professionals responsible for designing and managing internal development platforms. It is also useful for decision-makers involved in optimizing software delivery and operations in cloud-native environments. Familiarity with cloud computing, Kubernetes, and CI/CD concepts is helpful but not required, as the book provides practical guidance on platform engineering, self-service solutions, and managing technical debt.

Platform Engineering for Architects 1st Table of contents:

Part 1 – An Introduction to Platform Engineering and Architecture
Chapter 1: Platform Engineering and the Art of Crafting Platforms
The demand for platforms as a product
Companies and developers benefit from platforms in an equal manner
Platform case studies and success stories
Projects versus products
Platform as a product
Do you need a platform?
Do we need yet another abstraction layer?
Declutter the abstraction layers
The cognitive load for software engineers and other IT professionals
Implementing developer- and product-focused solutions
The pervasive cloud
Focusing on developer experience
Attributes of platforms
Understanding the socio-technical aspects
Understand user needs in platform design
Foster and enhance collaboration
Cultivating an open, platform-centric culture
Summary
Further reading
Chapter 2: Understanding Platform Architecture to Build Platform as a Product
Understanding platform principles and defining the purpose of your platform and team
Introducing principles as guardrails for decision-making
Developing the purpose of your platform as a product
Exploring platform architecture – layers, components, and meta-dependencies
Platform component model
Platform composability
Dependencies and the hidden glue
Reference architectures
Opinionated platforms and the cost of quality
Creating your own architecture
Exploring platform as a product – use cases and implementations
Finding the experts and the bottlenecks they cause
Centralizing expertise as a self-service use case
Understanding TVPs
Finding your TVP use case
Good enough versus perfectly done!
TVP – validating our hypothesis
Build, measure, and learn
Looking at the relevant KPIs to make adoption transparent
Defining platform adoption KPIs
Using performance metrics
Summary
Further readings
Chapter 3: Building the Foundation for Supporting Platform Capabilities
Financial One ACME – our fictitious company
Overcoming platform complexity by finding the right perspective
Applying basic product management – “Don’t give your users a faster horse”
Avoiding the “sunk cost fallacy”
Steps to building the thing that users need – a real-life example
Considering existing processes and integrating a new implementation
Understanding the existing SDLC – “the life cycle of an artifact”
Introducing life cycle events – measuring and improving the efficiency of the SDLC
Presenting the value proposition for improving the existing SDLC/DORA
Designing the infrastructure architecture
Avoid the ivory tower approach – we own the platform!
Organizational constraints – existing infrastructure requirements?
Connectivity constraints – interoperability requirements?
Resiliency constraints – SLAs and other non-functional requirements?
Exploring multi-cloud, multi-SaaS, and the fragmentation of capabilities
Multi-tenancy and ownership as a capability of our platform
The considerations for running on multi-X
Centralized and decentralized platform capabilities
Exploring a reference architecture for our platform
The purpose – self-service for your end users
User interface/dev experience
Core platform components
A platform that’s available, resilient, and secure
Success KPIs and optimization
Summary
Further reading
Part 2 – Designing and Crafting Platforms
Chapter 4: Architecting the Platform Core – Kubernetes as a Unified Layer
Why Kubernetes plays a vital role, and why it is (not) for everyone
Kubernetes – a place to start, but not the endgame!
Would Financial One ACME pick Kubernetes?
Benefits of picking Kubernetes as the core platform
Global community and CNCF
Leveraging and managing Kubernetes Infrastructure Capabilities
Integrating infrastructure resources
Enable cluster scalability
Network capabilities and extensions
Kubernetes as part of the platform control plane
The problem of external versus internally defined resources
Designing for flexibility, reliability, and robustness
Optimize consumption versus leaving enough head space
Summary
Further Reading
Chapter 5: Integration, Delivery, and Deployment – Automation is Ubiquitous
An introduction to Continuous X
High-level definition of Continuous X
Continuous X for infrastructure
Continuous X as a system-critical component in our platform
GitOps – Moving from pushing to pulling the desired state
Phase 1 – from source code to container image
Phase 2 – from container image to metadata-enriched deployment artifact
Phase 3 – GitOps – keeping your desired deployment state
Understanding the importance of container and artifact registries as entry points
From container to artifact registry
Building and pushing artifacts to the registry
Managing uploaded artifacts
Vulnerability scanning
Subscribing to the life cycle events of an artifact in the registry
Retention and immutability
Monitoring our registries
Defining the release process and management
Updating deployment to a new version
Batching changes to combat dependencies
Pre- and post-deployment checks
Deployment notifications
Promotions between stages
Blue/green, canary, and feature flagging
Release inventory
Release management – from launch to mission control
Achieving sustainable CI/CD for DevOps – application life cycle orchestration
Artifact life cycle event observability
Working with events
Subscribing to events to orchestrate
Analyzing events
IDPs – the automation Kraken in the platform
Providing templates as Golden Paths for easier starts!
Abstractions through Crossplane
Everything Git-flow-driven
Software catalog
Summary
Further reading
Chapter 6: Build for Developers and Their Self-Service
Technical requirements
Software versus platform development – avoiding a mix
The platform life cycle versus the software life cycle
Reliability versus serviceability
The conclusion
Reducing cognitive load
Utilizing a platform while balancing cognitive load
Pre-production versus production
Authentication and tenancy
RBAC
Noisy neighbor prevention
Rate limiting and network health
Cluster scaling and other policies
Enabling self-service developer portals
Enforcing quota
Simple repeatable workflows
Landing, expanding, and integrating your IDP
Enforcement of platform-specific standards
Maturity models
Expanding a platform with common platform integrations
Architectural considerations for observability in a platform
Observability in a platform
Centralized observability – when and why you need it
Important metrics
Observability in service for developers
Opening your platform for community and collaboration
Planning in the open
Accepting contributions
Summary
Part 3 – Platforms as a Product Best Practices
Chapter 7: Building Secure and Compliant Products
Reconciling security to the left and Zero Trust
Understanding platform security – how to build a secure yet flexible and open system
Breaking down the problem into consumable chunks
Common security standards and frameworks
Asset protection
Secret and token management
Secure access
Audit logs
Looking at SBOM practices
How to use an SBOM
Keeping on top of vulnerabilities
Understanding pipeline security – what you have to consider to secure your CI/CD pipelines
Securing your repo
Securing GitOps
Understanding application security – setting and enforcing policies
Foundational application security
FOSS for platform security and how to use it
Patterns and tools for managing security
What would our fictitious company do?
Summary
Chapter 8: Cost Management and Best Practices
Understanding the cost landscape – is the cloud the way to go?
To cloud or not to cloud – that’s the question
When we opt for the cloud – we have to consider its hidden costs
Where to find transparency
FinOps and cost management
Implementing a tagging strategy to uncover hidden costs
Using tags for a purpose
Tag and label limitations
Defining a tagging strategy
Tagging automation
Consolidated versus separated cost and billing reports
Looking at cost optimization strategies
Streamlining processes
Finding the best deals for the best prices
Designing for the highest utilization and lowest demands
Autoscaling, cold storage, and other tricks for cost optimization
Many shades of autoscaling
Cost-aware engineering
Summary
Further reading
Chapter 9: Choosing Technical Debt to Unbreak Platforms
Taking technical debts consciously
Moving beyond the thinnest viable platform (TVP) sustainably
Avoid over-engineering
Build versus buy – building a decision tree
The criticality of team buy-in
Using data to drive design decisions
Observability is key
Data retention is technical debt
Maintaining and reworking technical debt
Own your technical debt
Platform composability
Dependencies
Security
Not all technical debt has equal weight
Rewriting versus refactoring data – a practical guide
Determining whether a rewrite is necessary
Examining the external influences on refactoring with an example
Examining a famous rewrite
Transitioning after rewrite
Architectural decision records – document for the Afterworld
Why document software architecture?
What does good technical documentation look like?
Our fictitious company – a final look
Summary
Chapter 10: Crafting Platform Products for the Future
Continuous changes – learning to age and adapt
The imperative of change
Fostering a culture of change
Iterative evolution and an evolving strategy
Considering sustainable and lightweight architectures and approaches
Enable lightweight architectures
Providing support for the users to adapt
The Golden Path for changes
Providing feedback channels
Golden Paths are the features of our platforms
Start small, expect growth, and don’t become a bottleneck
Golden Paths to Build Golden Paths
A glimpse into the future
The replacement of hypervisors
AI for platforms
OCI Registry as Storage and RegistryOps
Containerized pipelines as code
Platforms – a better future with them?
Summary
Further reading
Index
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Tags: Max Korbacher, Engineering, Architects