How deeply does Effective Platform Engineering cover standard?

Explains Kubernetes APIs, IDP templates, and standardized configurations, without detailing their implementation.

Standard

As explained in Effective Platform Engineering

Standardization is the adoption of common interfaces, behaviors, and processes so that components can interoperate consistently.

Standardization establishes shared APIs, configurations, templates, and policies so teams can operate consistently. In platform engineering, it can reduce infrastructure complexity while supporting compliance and interoperability. section 2.3.5 section 10.2.5 section 10.6.1

Platform standardization appears in several forms:

Kubernetes provides agreed-upon APIs for orchestration and extensibility. section 2.3.5
IDPs use templates and policies to promote best practices, compliance, and consistent deployments. section 10.6.1
Standardized configurations can align teams with security and governance requirements, reducing vulnerabilities and human error. section 10.2.5

Standardizing microservice deployment

A developer configures and deploys a microservice through an IDP portal. Templates and policies promote consistent, compliant setup, while automation handles build, testing, and deployment. section 10.6.1

How Effective Platform Engineering covers it

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Also explained in

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Shipping Go: Develop, deliver, discuss, design, and go againStandardization is the process of making work methods and outputs uniform through defined practices.
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Deep Learning with Python, Third EditionThe preprocessing step that normalizes text before tokenization, such as lowercasing.
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Deep Learning with R, Third EditionStandardization is the normalization of text through transformations such as case conversion, punctuation removal, or encoding normalization.
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Architecture Modernization: Socio-technical alignment of software, strategy, and structureStandardization is the practice of making technologies, processes, or interfaces consistent across teams or systems.
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Pandas Workout: 200 exercises to make you a stronger data analystValue standardization is the transformation of inconsistent categorical labels into a consistent set of labels.

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Related concepts

measurementused by · Measurement is the systematic assessment of a property, behavior, or outcome that produces an observed value, score, or judgment.
tokenizationpart of · Tokenization is the process of dividing text or other sequential input into discrete units called tokens for computational processing.
preprocessingpart of · Preprocessing is the preparation or transformation of data, content, or other inputs into a form suitable for a subsequent computational operation.
MCPaddresses · The Model Context Protocol is an open standard protocol that defines how AI applications connect with external tools, data sources, and other contextual resources.
rulecontrasts with · A rule is an explicitly specified condition, procedure, or directive that governs behavior, decisions, or outcomes in a defined domain.

This explainer was generated by Manning's knowledge graph from the text of Effective Platform Engineering. The section links point to the parts of the book it draws on.