Infrastructure as Code (IaC)

Infrastructure, Operations & Emerging Tech

Managing Infrastructure Through Code

1. Overview of IaC: A System That Achieves Automation, Consistency, and Version Control by Defining Infrastructure Configuration as Code

    flowchart LR
    A["Manual infrastructure setup<br/>(human error, inconsistency)"] --"Codify and automate,<br/>version control"--> B["IaC pipeline<br/>Plan → Apply"] --"Consistency, reproducibility,<br/>eliminate drift"--> C["Reliable<br/>infrastructure operations"]

    style A fill:#FFEBEE,stroke:#D32F2F,color:#000
    style B fill:#E3F2FD,stroke:#1976D2,color:#000
    style C fill:#E8F5E9,stroke:#388E3C,color:#000

Definition: An operational approach in which infrastructure configuration — servers, networking, storage, and more — is specified as machine-readable code (definition files) instead of manual work, and infrastructure is provisioned, changed, and decommissioned through version control and automation tools.

Characteristics: (Declarative or imperative) Infrastructure state is defined using either a declarative or an imperative approach. (Environment consistency) The same code reproduces development, staging, and production environments, eliminating drift and ensuring environment consistency. (Change history management) Integration with Git-based version control enables tracking of infrastructure changes, code review, and rollback.

2. How IaC Works and Its Core Tooling

a. IaC Workflow (Provisioning Pipeline)

    flowchart LR
    CODE["Write infrastructure code<br/>(HCL, YAML, JSON)"]
    GIT["Version control<br/>(Git Push)"]
    PLAN["Review the change plan<br/>(Plan)"]
    APPLY["Apply infrastructure<br/>(Apply)"]
    INFRA["Cloud / On-premises<br/>Infrastructure"]

    CODE --> GIT --> PLAN --> APPLY --> INFRA
    INFRA --"State feedback"--> PLAN

    style CODE  fill:#E3F2FD,stroke:#1976D2,color:#000
    style PLAN  fill:#FFF3E0,stroke:#F57C00,color:#000
    style APPLY fill:#E8F5E9,stroke:#388E3C,color:#000
    style INFRA fill:#1E3A5F,stroke:#1E3A5F,color:#fff

Component	Description	Representative Tools
Configuration File	Code file defining the desired infrastructure state	Terraform (.tf), Ansible (.yml), CloudFormation
State File	Records and synchronizes the actual current state of infrastructure	terraform.tfstate, Pulumi state
Plan	Compares code against current state to preview changes	`terraform plan`, `ansible --check`
Apply	Applies the planned changes to actual infrastructure	`terraform apply`, `ansible-playbook`

b. Declarative vs. Imperative Approach Compared

    flowchart TD
    subgraph R1["　"]
        direction LR
        DEC["Declarative approach<br/>Define the desired end state<br/>The tool decides how<br/>Terraform / Kubernetes"]
        IMP["Imperative approach<br/>Define the execution steps<br/>The user controls the process<br/>Ansible / Chef"]
    end
    subgraph R2["　"]
        direction LR
        ADV["Declarative advantages<br/>Idempotency guaranteed<br/>Automatic drift convergence<br/>Safe to reapply"]
        DIS["Imperative advantages<br/>Fine-grained execution control<br/>Complex sequencing logic<br/>Expressing conditional branches"]
    end

    style DEC fill:#E3F2FD,stroke:#1976D2,color:#000
    style IMP fill:#F3E5F5,stroke:#7B1FA2,color:#000
    style ADV fill:#E8F5E9,stroke:#388E3C,color:#000
    style DIS fill:#FFF3E0,stroke:#F57C00,color:#000
    style R1 fill:none,stroke:none
    style R2 fill:none,stroke:none

Comparison Item	Declarative	Imperative
Core question	“What” should be built?	“How” should it be built?
State management	Automatically converges to the desired state	Each step is re-executed sequentially
Idempotency	Re-running the same code guarantees the same result	Re-running may cause side effects
Readability	Easy to grasp the final infrastructure structure	Focused on execution flow and order
Representative tools	Terraform, Pulumi, Kubernetes YAML	Ansible, Chef, Puppet, shell scripts

3. Expected Benefits and Practical Application of IaC

Category	Expected Benefits	Application and Practical Use
Consistency and accuracy	Eliminates drift between environments and prevents human error	The same code guarantees identical dev, staging, and production environments
Operational speed	Automated provisioning shortens deployment time	Modular templates enable servers and networks to be scaled up within minutes
Version control	Tracks infrastructure change history and enables rapid rollback	GitOps pipelines review infrastructure changes through pull requests
Cost optimization	Code-based detection and cleanup of unnecessary resources	Terraform drift detection automatically identifies unused resources

Cloud Adoption Framework IT Asset Management (ITAM)