Infrastructure as Code (IaC)

Infrastructure as Code describes servers, networks, and cloud resources in versioned configuration files from which environments are created automatically. This article explains declarative and imperative approaches, dealing with drift, and security scans for templates, including how it differs from configuration management.

Anyone who builds an environment by hand creates a one-off: hard to reproduce, and after two years no one can explain why a particular firewall rule exists. Infrastructure as Code (IaC) ends this model. Infrastructure is described in configuration files and created automatically, using the same methods that have proven themselves in software development, above all versioning and review. The approach became established with the cloud, but its effect now reaches far beyond that, into network and security policies.

What is Infrastructure as Code?

Infrastructure as Code refers to the practice of defining infrastructure in machine-readable files and provisioning it automatically through tools. This covers virtual machines and Kubernetes clusters as well as networks, firewall rules, or DNS records. The definitions reside in a version control system and pass through a review before every change. Identical environments are created from the same description, whether a test or production environment. This makes infrastructure auditable like source code: every change has an author and a timestamp, and faulty states can be rolled back to an earlier one. The code thus becomes reliable documentation: it does not describe yesterday's intent, it is the source from which the environment was actually created.

How it works

Declarative or imperative: Declarative tools describe the target state, and the tool itself determines the necessary steps. Imperative approaches define the steps explicitly, for example as a sequence of scripts. For infrastructure, declarative approaches have largely prevailed because they work idempotently: running them repeatedly leads to the same result.
Versioning as the foundation: Every change runs as a pull request with review. The history documents who changed what, when, and why.
Plan before execution: Common tools show, before they are applied, which resources will be created, changed, or removed. This plan is the last checkpoint before intervening in real environments.
Drift detection: If the real environment deviates from the definition, for example through manual changes in a cloud console, the comparison makes this visible. Drift is either rolled back or deliberately incorporated into the code.
Security scans for templates: Specialized scanners check IaC definitions for misconfigurations before rollout, for example open network access or overly broad permissions. Errors are stopped before they reach an environment.

Why it matters

Reproducibility: environments are created from code instead of from memory. An additional test environment or a new site becomes a routine task, not a project of its own.
Fewer manual errors: automated processes avoid typos and forgotten steps that inevitably happen with manual work.
Traceability for audits: the version history answers auditors' questions directly. Who initiated the change, who approved it, when did it take effect?
Fast recovery: after an outage, the environment is rebuilt from the definition instead of being reconstructed from backups and recollection.
Security before rollout: scans check configurations before they go live. This works earlier and more reliably than any after-the-fact review of running systems.
A foundation for more: GitOps and automated compliance checks build on cleanly defined infrastructure.

Typical scenarios

The most common entry point is cloud migration: new environments are built as code from the start, because clicking together hundreds of resources neither scales nor can be documented. A second scenario is keeping several environments in sync: test and production should differ only in defined parameters, so that test results stay meaningful. Third, disaster recovery: rebuilding at a failover site succeeds within a reliable timeframe when the entire environment exists as code. And finally the network itself: as code, firewall rules and segmentation policies benefit from mandatory review and history, precisely because manual rule changes are known to be error-prone. The approach also pays off in acquisitions and carve-outs, because defined environments can be cleanly duplicated or separated out.

IaC and configuration management: the distinction

Both disciplines automate, but they start at different points. IaC provisions resources: it creates networks, virtual machines, load balancers, or databases and manages their lifecycle. Configuration management sets up systems that already exist: it installs software and keeps configuration files consistent. In traditional environments the two complement each other, IaC provides the machine, configuration management makes it operational. Containers shift this boundary, because configuration moves into the image and systems are run immutably. The distinction still matters, because forcing both tasks through the same tool often leads to constructs that are hard to maintain.

How KAEMI helps

KAEMI applies IaC principles where they have the greatest leverage for secure enterprise networks: in connectivity and segmentation. Connections to cloud environments are created with Cloud Connectivity in a reproducible and traceable way, instead of as an organically grown one-off configuration. Segmentation policies are maintained as declarative policies within microsegmentation : they describe permitted communication, enforcement is automated, and every change stays documented. As a managed service provider, KAEMI takes over ongoing operations, from maintaining the definitions to monitoring for deviations. Changes to the network thus become far less daunting, because they are checked before rollout and remain reversible. If you want to bring your network and security configuration into an auditable, versioned form, talk to us via contact .

Frequently asked questions about Infrastructure as Code (IaC)

What distinguishes declarative from imperative IaC?

Declarative approaches describe the desired end state, and the tool calculates the necessary steps and repeatedly reconciles against reality. Imperative approaches define the steps themselves, for example as a script that creates resources in a fixed order. Declarative has prevailed for infrastructure because runs are idempotent and the code also serves as documentation of the target state.

What is configuration drift and how do I deal with it?

Drift occurs when the real environment deviates from the defined code, usually through manual intervention in consoles or on systems. This makes environments unpredictable and devalues the documentation. What helps against it: regular automatic comparisons that report deviations, clear rules for emergency intervention and for returning it to the code, and restrictive permissions for direct changes to production resources.

How can IaC be secured?

Treat infrastructure code like application code: mandatory reviews, scans for misconfigurations before every rollout, and secret checks so that no credentials end up in templates. The executing pipeline is given tightly limited permissions, separated per environment. The state of the tools, such as state files, contains sensitive data and should be stored encrypted and with restricted access.

Is IaC relevant only for cloud environments?

No. The approach originated in the cloud, but it works anywhere resources can be controlled through interfaces. In the data center, too, network configurations, firewall rules, and segmentation policies can be maintained as code. Security policies in particular gain mandatory review and history this way, something that manual rule management on individual devices can neither provide nor should.

How does IaC differ from configuration management?

IaC creates and manages resources: networks, virtual machines, or clusters are created from declarative definitions. Configuration management handles the inner workings of systems that already exist, such as installed software and services. The two complement each other in traditional environments. On container platforms, configuration management loses weight, because configuration moves into the image and systems are run immutably.