Infrastructure as Code (IaC): What, Why and some best practices
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Infrastructure as Code (IaC) brings a shift in how we provision, manage, and maintain cloud infrastructure. Rather than manually configuring servers, networks, and services through web consoles or command-line interfaces, IaC treats infrastructure as software—defined through code, version-controlled, and deployed through automated processes.
At its core, IaC transforms infrastructure management from a manual, error-prone process into a repeatable, reliable, and scalable practice.
This approach enables teams to define their entire infrastructure stack using high-level programming languages or domain-specific languages, creating a single source of truth that can be tested, reviewed, and deployed consistently across environments.
Modern IaC solutions can manage everything from basic virtual machines to complex multi-cloud architectures with hundreds of interconnected services.
Why do we need IaC?
The traditional approach to infrastructure management—often called "ClickOps"—involves manual configuration through graphical interfaces or scripts. While this might work for simple setups, it quickly becomes unsustainable as infrastructure complexity grows.
Manual processes introduce human error, make it difficult to replicate environments, and create undocumented "snowflake" systems that are hard to maintain or troubleshoot.
IaC addresses these challenges by bringing software development practices to infrastructure management. Version control allows teams to track changes, collaborate effectively, and roll back problematic deployments.
Automated testing can validate infrastructure configurations before they reach production. Code reviews ensure that changes are scrutinized by multiple team members, reducing the likelihood of misconfigurations.
The business benefits are equally compelling. IaC dramatically reduces the time required to provision new environments, enabling faster development cycles and quicker time-to-market.
It also improves disaster recovery capabilities, as entire environments can be recreated from code in minutes rather than hours or days. For organizations with compliance requirements, IaC provides an auditable trail of all infrastructure changes and ensures consistent application of security policies.
Perhaps most importantly, IaC enables true DevOps practices by breaking down silos between development and operations teams. When infrastructure is defined as code, developers can better understand the systems their applications run on, while operations teams can apply software engineering practices to infrastructure management.
Popular IaC Tools
The IaC ecosystem has evolved rapidly over time, with tools emerging to address different use cases, cloud providers, and organizational preferences. Understanding the landscape helps teams choose the right tool for their specific needs.
Let’s discuss some of the widely adopted tools ind the industry today.
1. Terraform
Terraform has become the de facto standard for multi-cloud infrastructure management. Created by HashiCorp (now part of IBM), Terraform uses its own domain-specific language (HCL) to define infrastructure across hundreds of providers. Its provider ecosystem is vast, covering not just major cloud platforms but also services like DNS providers, monitoring tools, and even SaaS applications.
2. AWS CloudFormation
AWS CloudFormation remains the go-to choice for AWS-centric organizations. As a native AWS service, it offers deep integration with AWS services and receives immediate support for new features. CloudFormation templates can be written in JSON or YAML, and the service handles the complexity of resource dependencies and rollback scenarios.
3. Pulumi
It takes a unique approach by allowing infrastructure to be defined using general-purpose programming languages like Python, TypeScript, Go, and C#. This appeals to developers who prefer familiar programming constructs and want to leverage existing language ecosystems for infrastructure code.
4. AWS CDK (Cloud Development Kit)
brings a similar programming language approach to AWS infrastructure, generating CloudFormation templates from high-level programming language code.
5. Azure Resource Manager (ARM) templates
It serve a similar role in the Microsoft ecosystem, providing native Azure integration with JSON-based template definitions. Microsoft has also introduced Bicep as a more user-friendly domain-specific language that compiles to ARM templates.
7. AWS Serverless Application Model (AWS SAM)
AWS SAM allows to build, test, deploy serverless application on AWS. It is one of my favorite to build serverless applications on AWS.
8. SST
SST (Serverless Stack Toolkit) is a framework designed to make building and deploying serverless applications easier, particularly on AWS. It helps developers build full-stack serverless applications using familiar tools and patterns. It handles the complexity of configuring AWS services like Lambda, API Gateway, DynamoDB, and others, while letting you write your application code in JavaScript/TypeScript.
9. Google Cloud Deployment Manager
It offers Google Cloud Platform users a native IaC solution, though it has seen less adoption compared to multi-cloud alternatives such as Terraform.
Ansible and Chef represent configuration management tools that have expanded into infrastructure provisioning, offering a more imperative approach to IaC.
More on IaC tools, in-depth will be in our coming issue. Don’t forget to subscribe.
State of IaC Tools
The IaC trends in 2025 shows remarkable maturity of IaC adoption in the industry. Terraform claims its position as the most widely adopted multi-cloud IaC tool, but popularity of the community forked version of Terraform — Open Tofu is also growing.
As managing cloud infrastructure is getting more complex without IaC than ever. Cloud-native tools are experiencing a growth as organizations seek deeper integration with their chosen platforms.
AWS CDK has gained significant traction among development teams, with its ability to generate CloudFormation templates from familiar programming languages such as TypeScript, Python, Go etc.
The trend toward programming language-based IaC is accelerating. This shift reflects that we are going toward treating infrastructure more like application code, with all the associated benefits of familiar tooling, testing frameworks, and development practices.
I am curious, what Infrastructure as Code (IaC) tools are your organization using?
Advantages of doing IaC
The advantages of Infrastructure as Code is more than simple automation. Fundamentally it transforms how organizations approach infrastructure management and enabling new levels of reliability, speed, and collaboration.
Here are some of the benefits I see practicing Infrastructure as Code in your organizations:
Consistency and Reproducibility stand out as perhaps the most immediate benefits. When infrastructure is defined as code, teams can guarantee that development, staging, and production environments are identical. This eliminates the "it works on my machine" problem at the infrastructure level and ensures that applications behave consistently across all environments.
Version Control and Collaboration bring software development best practices to infrastructure management. Every change is tracked, attributed to a specific person, and can be reviewed before implementation.
Automation and Speed transform infrastructure provisioning from a time-consuming manual process to a rapid, automated workflow. Complex environments that might take days to set up manually can be provisioned in minutes.
Cost Management becomes more predictable and controllable when infrastructure is managed through code. Teams can easily spin down development environments when not in use, implement consistent tagging strategies for cost allocation, and use infrastructure templates to enforce resource limits and optimize configurations.
Disaster Recovery capabilities improve dramatically with IaC. Instead of maintaining complex disaster recovery documentation that quickly becomes outdated, organizations can simply re-run their infrastructure code in a different region or cloud provider. This approach provides confidence that disaster recovery procedures actually work, as they use the same code that builds production environments daily.
Documentation and Knowledge Sharing become important benefits rather than separate activities. Well-written infrastructure code serves as living documentation of system architecture and dependencies. New team members can understand complex systems by reading the code, and architectural decisions are preserved in commit messages and code comments.
Testing and Validation can be applied to infrastructure changes before they impact production systems. Teams can run infrastructure code against test environments, validate configurations, and even perform integration testing to ensure that infrastructure changes don't break existing applications.
Types of Approach
Infrastructure as Code implementations fall into several distinct approaches, each with specific characteristics that make them suitable for different use cases and organizational contexts.
Procedural Approach
It defines infrastructure through a series of explicit steps that must be executed in order. It’s more like traditional scripting methodologies, where each action builds upon the previous one. Tools like Ansible is this approach, allowing administrators to define playbooks that execute tasks sequentially. The procedural approach offers granular control over the provisioning process and can be easier to understand for teams transitioning from manual processes. However, it requires careful consideration of execution order and can become complex when managing dependencies between resources.
Declarative Approach
It focuses on describing the desired end state of infrastructure rather than the specific steps to achieve it. Tools like Terraform and CloudFormation use this approach, allowing users to define what they want their infrastructure to look like and letting the tool figure out how to make it happen. This abstraction simplifies infrastructure management by handling dependency resolution, resource ordering, and change detection automatically. The declarative approach typically results in more maintainable and predictable infrastructure code.
Push vs Pull Models
It represent different strategies for applying infrastructure configurations. Push-based systems require an external orchestrator to deploy changes to target systems, while pull-based systems have agents running on target systems that periodically check for and apply updates. Push models, common in tools like Terraform, offer immediate feedback and centralized control. Pull models, used by tools like Chef and Puppet, can be more resilient in distributed environments but may have delayed change propagation.
Immutable and Mutable Infrastructure
Immutable infrastructure components as immutable artifacts that are replaced rather than modified. This approach, popularized by containerization and cloud-native architectures, eliminates configuration drift and simplifies troubleshooting. When changes are needed, entirely new infrastructure components are created and old ones are destroyed. While this can increase resource churn, it provides exceptional consistency and reliability.
Mutable infrastructure allows in-place modifications to existing infrastructure components. This approach can be more resource-efficient and faster for certain types of changes, but it introduces the risk of configuration drift over time. Traditional configuration management tools often use this approach, applying changes to running systems rather than replacing them entirely.
Best Practices
Successful Infrastructure as Code implementation requires more than just choosing the right tool—it demands adherence to proven practices that ensure maintainability, security, and reliability over time.
Version Control Everything. All infrastructure code should be stored in version control systems with meaningful commit messages that explain not just what changed, but why. This includes not only the primary infrastructure definitions but also supporting scripts, configuration files, and documentation. Branching strategies should align with infrastructure change management processes, with production changes requiring code review and approval processes.
Environment Separation. Ensures that changes can be tested safely before affecting production systems. This goes beyond simply having separate environments—it requires that environments are truly isolated, with separate state files, credentials, and access controls.
State Management. It represents one of the most critical aspects of IaC implementation, particularly for tools like Terraform that maintain explicit state files. State should be stored remotely in secure, centralized locations with appropriate backup and versioning strategies. State locking prevents concurrent modifications that could corrupt infrastructure, while state encryption protects sensitive information. Teams should never commit state files to version control and should implement processes for state recovery in case of corruption.
Modularization and Reusability. It become increasingly important as infrastructure code bases grow. Well-designed modules encapsulate related resources and provide clean interfaces for customization. This reduces code duplication, improves maintainability, and enables teams to build libraries of tested, reusable infrastructure components.
Security Integration. It must be built into IaC workflows from the beginning rather than bolted on later. This includes scanning infrastructure code for security vulnerabilities, implementing least-privilege access controls, and ensuring that sensitive information is never stored in plain text within code repositories.
Testing and Validation. It should apply the same rigor to infrastructure code that development teams apply to application code. This includes syntax validation, policy compliance checking, and functional testing in non-production environments. Automated testing can catch many issues before they reach production, while manual testing validates that infrastructure actually supports the intended workloads.
Documentation and Communication ensure that infrastructure decisions are preserved and accessible to future team members. This includes both inline code comments that explain complex logic and higher-level architectural documentation that describes system design decisions. Change logs should connect infrastructure modifications to business requirements, making it easier to understand the evolution of systems over time.
Monitoring and Observability should be integrated into infrastructure code rather than configured separately. This ensures that new infrastructure automatically includes appropriate monitoring, logging, and alerting capabilities. Infrastructure changes should be correlated with system performance metrics to identify issues quickly and validate that changes have the intended effect.
Disaster Recovery Planning benefits enormously from IaC practices, but requires explicit planning and testing. Infrastructure code should be regularly tested in disaster recovery scenarios to ensure that systems can actually be rebuilt from scratch. This includes not just the infrastructure itself but also the processes for accessing backups, configuring applications, and restoring data.
Conclusion
Infrastructure as Code has evolved from a niche practice adopted by forward-thinking organizations to an essential capability for any team serious about cloud infrastructure management. The benefits—improved consistency, faster deployment times, better collaboration, and reduced operational risk—are no longer theoretical advantages but proven outcomes demonstrated across countless organizations.
For organizations beginning their IaC journey, the key is to start small and focus on building sustainable practices rather than trying to automate everything immediately. Choose tools that align with existing expertise and grow with organizational needs. Invest in training and establish clear governance practices early, as these foundational elements will determine long-term success.
The cloud infrastructure industry will continue to evolve rapidly, but the fundamental principles of Infrastructure as Code—treating infrastructure as software, applying rigorous development practices, and maintaining systems through automated processes—will remain constant. Organizations that master these principles will be well-positioned to adapt to whatever changes the future brings, maintaining agility and reliability even as their infrastructure requirements grow in complexity and scale.