Automating a network command is easy. Automating production change safely is the real engineering challenge.
A script can configure hundreds of devices in minutes. But what happens when the inventory is wrong, a policy shifts traffic unexpectedly, only part of a deployment succeeds, telemetry begins to deteriorate, or the same automation removes the management path needed to recover the network?
Network Automation in Production moves beyond one-off scripts and shows network professionals how to build automation that is controlled, observable, repeatable, auditable, and recoverable.
Instead of focusing on syntax alone, this practical guide teaches you how to design the entire system surrounding automated network change-from intent and authoritative data to validation, deployment, monitoring, security, and evidence.
Inside, you will learn how to:
Turn operational intent into structured, testable network changesBuild reliable inventories and source-of-truth modelsSeparate desired, declared, and observed network stateCreate configuration pipelines using structured data, templates, and model-driven interfacesDesign safer workflows with preconditions, invariants, postconditions, canaries, and controlled blast radiusApply infrastructure-as-code principles without forcing inappropriate software patterns onto network devicesIntroduce CI/CD and Git-based review into network operationsDetect configuration drift and turn compliance into a continuous engineering processUse streaming telemetry and observability to verify real outcomes after changesBuild safer rollback, recovery, and partial-failure strategiesProtect automation with machine identities, least privilege, secret management, and approval boundariesDesign reusable automation platforms instead of accumulating disconnected scriptsMeasure automation by reliability, recovery, validation coverage, and business outcomes-not simply by how many tasks are automatedThe book also examines the wider tool and protocol landscape-including Python-oriented orchestration, declarative frameworks, source-of-truth systems, structured data models, NETCONF/RESTCONF-style management, gNMI telemetry, Git pipelines, and infrastructure-as-code approaches-while emphasizing that each tool should have a clearly defined responsibility.
The manuscript's central principle is simple: production automation is a change system, not merely code that sends commands. Mature workflows define intent, validate inputs, calculate the proposed change, constrain execution, observe the outcome, and preserve evidence before expanding their scope.
Whether you are a network engineer, network automation engineer, infrastructure engineer, NetDevOps practitioner, platform engineer, network architect, or operations professional, this book will help you move from scripts that work to automation systems your organization can actually trust.
Build automation that moves faster because it is safer-not automation that simply makes mistakes faster.