Model-Driven DevOps: Increasing agility and security in your physical network through DevOps

Description

Develop Network Infrastructure More Rapidly, and Operate It More Effectively

Using model-driven DevOps and the Infrastructure as Code (IaC) paradigm, teams can develop and operate network infrastructure more quickly, consistently, and securely--growing agility, getting  to market sooner, and delivering more value. Now, two leading practitioners walk you step by step through successfully implementing model-driven DevOps for infrastructure. In this practical guide, they share lessons learned, help you avoid common pitfalls, and illuminate key differences between DevOps for infrastructure and conventional application-based DevOps.

You'll learn why network infrastructure operations must change, what needs to change, and how to work together to change it. The authors guide you through creating consistent data models to manage massive numbers of network elements, organizing huge quantities of network data, and applying DevOps to infrastructure repeatably and consistently. Your journey includes a complete, hands-on reference implementation, detailed use cases, many examples based on open source tools, and sample code downloadable at GitHub.

* Normalize and organize network infrastructure data consistently, to gain the same benefits from DevOps as cloud operators do
* Replace legacy command lines with APIs, then leverage and scale them
* Use configuration management, templates, and other tools to program infrastructure without coding
* Safely implement Continuous Integration/Continuous Deployment for infrastructure
* Succeed with key human factors: break down silos, change culture, and address skills gaps

Whether you're a network or cybersecurity engineer, architect, manager, or leader, this guide will help you suffuse all your network operations with greater efficiency, security, responsiveness, and resilience.

Sample Content

Sample Pages

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Table of Contents

Chapter 1: A Lightbulb Goes Off
Enterprise IT as a Source of Risk to the Business
    Observations of a Train Wreck
DevOps Seems Like a Better Way
    What Is DevOps?
    Automation
    Infrastructure as Code
    CI/CD
    Apps vs. Infrastructure
    Harnessing Automation-at-Scale
Why Are Enterprise IT Departments Not Adopting DevOps?
    Human Factors
    Business Factors
Summary
Chapter 2: A Better Way
The Goal: Business Transformation
    Constraints-Based IT
    Business Transformation
    DevOps in Action
Why Model-Driven DevOps?
    Network Infrastructure Is Different
    What Is Model-Driven DevOps?
    What Is a Data Model?
    Source of Truth
    DevOps as a Framework
DevSecOps: Baked-In Security
Summary
Chapter 3: Consumable Infrastructure
APIs
    Why API over CLI?
Platforms
    Physical Hardware Provisioning
    Consolidated Control Point
    Northbound vs. Southbound APIs
    API and Feature Normalization
    Fabricwide Services
    Scalability
Summary
Chapter 4: Infrastructure as Code
Why Infrastructure as Code?
Source of Truth
    Data Models
    Common IaC Tools
    Organization
    Types of Source of Truth
Code
    Data Flow
Summary
Chapter 5: Continuous Integration/Continuous Deployment
CI/CD Overview
    Applications vs. Infrastructure
    CI/CD in Action
Source Code Management
    Core Features
    Collaboration Features
    SCM Summary
Continuous Integration Tools
    CI Engines
    How They Work
    Sample Workflow
Infrastructure Simulation Tools
    Cisco Modeling Labs
Test and Validation
    Linting
    Schema/Model Validation
    Functional Testing
    Test and Validation Summary
Continuous Deployment
Continuous Monitoring
Summary
Chapter 6: Implementation
Model-Driven DevOps Reference Implementation
The Goal
DevOps Roadmap
Architecture
    Network as an Application
    Consistency
Simulation
Automation
    Creating a Source of Truth
    Moving Data
    MDD Source of Truth
    Automation Tooling
    MDD Data
    Automation Runner
    Cisco Network Services Orchestrator
Testing
    Linting
    Snapshotting the Test Network
    Data Validation and State Checking
    Data Validation
    Pushing Data to the Devices
    State Checking
    Restore
    Continuous Integration Workflow Summary
Deployment
    Scale
    Starting Workflows
Summary
Chapter 7: Human Factors
Culture and the Need for Change
Start with the Why
Organization
    Leadership
    Role Models
    Building a Team
    Break Down the Silos
    Community
    New Tools
    Summary of Organization-Level Changes
Individual
    Programming vs. Automation
    Version Control Tools
    Data Formats
    APIs
    Templating
    Linux/UNIX
    Wait! Where Do I Fit In?
Summary

9780137644674    TOC   6/23/2022

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