Steven Carter has more than 25 years of industry experience working in large universities, government research and development laboratories, and private sector companies. He has been a speaker at several industry conferences and written blogs and articles in technical journals. He has spent time as a system administrator running some of the world’s largest supercomputers and a network engineer building out the world’s first SDN network for the Department of Energy. In addition, Steven has a wide range of experience in networking, including operations, embedded software development, and sales. He has spent the past 5 years working for Red Hat Ansible and Cisco Systems consulting and coding for many of the world’s largest organizations as they modernize and secure their operations by incorporating DevOps. He currently works as a principal DevOps engineer for Cisco Systems creating CI/CD pipelines for deploying cloud applications and network infrastructure in secure and classified environments. He holds a BS in computer engineering, an MS in computer science, an MBA, and a CCIE in routing and switching.

Jason King is a solutions architect at Cisco, supporting the public sector community. In his 11 years at Cisco, he has focused on cloud, automation, programmability, and HPC. Prior to joining Cisco, he spent 10 years building and tuning some of the world’s largest HPC clusters at Lawrence Livermore National Laboratory. He holds an MS in computer science and a CCIE in routing and switching.

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