Infrastructure as code (IaC) lets an SRE team define infrastructure in version-controlled files instead of provisioning it through ad hoc console changes. An IaC tool compares that declared configuration with the resources that exist and proposes or makes changes through provider APIs. The reliability benefit comes from the operating model around the files: reviewed changes, safe state management, drift reconciliation, and measurable recovery—not from automation alone.
What infrastructure as code means for SRE
IaC describes desired infrastructure in configuration files. An engine uses those declarations to work out which resources to create, change, or remove, then interacts with cloud, on-premises, Kubernetes, or SaaS APIs through providers. HashiCorp’s Well-Architected Framework describes IaC as defining infrastructure with declarative configuration files rather than manual processes.
For SRE teams, the key change is operational: infrastructure changes become reviewable artifacts that can be tested and traced, rather than undocumented actions in a console. Git history can show what was intended, who reviewed it, and when it was merged. That does not guarantee a safe change, but it gives a team a consistent path to assess and control one.
How Terraform fits into the workflow
Terraform is a prominent IaC tool. Its human-readable HCL configuration describes resources, providers connect those descriptions to service APIs, and modules package reusable infrastructure patterns. Terraform also maintains state, which helps it understand the relationship between configuration and the resources it manages. HashiCorp’s Terraform documentation defines it as a tool for describing resources and infrastructure in human-readable configuration files.
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- Scope the change. Decide which infrastructure belongs in the change and which team owns it. Keep the change small enough to review and recover from.
- Write or update configuration. Express the desired resources in the appropriate Terraform files. Use established modules, names, and tags where they fit the team’s conventions.
- Initialize the working configuration. Set up the providers needed to connect the configuration to its target APIs.
- Generate a plan. Ask Terraform to compare declared configuration with its recorded state and the available information about actual resources, then produce a proposed change.
- Review the proposed diff. Check additions, updates, removals, replacements, and dependency changes. Treat an unexpected destructive action or replacement as a reason to stop and investigate, not as a routine detail.
- Apply only after approval. Connect the apply step to the team’s approved change process. Record the outcome and verify that the resulting infrastructure is consistent with the intended change.
A plan is a review aid, not a reliability guarantee: reviewers still need to understand the affected resources, dependencies, and operational consequences. The apply should follow the approved plan and ownership process, rather than a separate unreviewed console action.
Build an SRE control path for infrastructure changes
Keep Terraform or equivalent IaC in Git with the review metadata needed to make a change auditable. A pull request can be the control point where engineers, automation, and policy checks assess a proposed change before it reaches infrastructure.
Before a change can be applied
- Require pull requests and code review for configuration changes.
- Run automated formatting and validation so routine defects are caught before apply.
- Add security and policy checks appropriate to the infrastructure and its ownership boundaries.
- Inspect plans for destructive replacements and dependency changes; escalate surprises rather than approving them by default.
- Use staged environments and small, reversible changes where practical, so the team can learn from a limited change before applying a broader one.
Make repeatability an operating standard
Use modules for repeatable infrastructure patterns, and establish naming and tagging conventions so resources can be recognized and managed consistently. These conventions should make ownership and purpose legible to the people reviewing a change and responding to an incident.
Manage Terraform state safely
Terraform state is central to how the tool determines what needs to change. In a team setting, state therefore needs clear ownership and a controlled collaboration model. Prefer remote state with locking so collaborators do not unknowingly work against conflicting state updates. Define ownership boundaries so teams know which configuration and state they are responsible for.
- Protect sensitive data. Keep credentials, provider secrets, and sensitive values out of Git. Follow the tool’s state-security guidance, and treat state storage as security-sensitive rather than as an ordinary source file.
- Make ownership explicit. Document which team owns a state boundary and which changes require that team’s review.
- Use locking for shared work. A lock helps coordinate state operations; it does not replace review, access controls, or a recovery plan.
- Keep change scope manageable. Smaller changes make plan review clearer and limit the amount of infrastructure implicated if recovery is needed.
Remote state and locking reduce collaboration hazards, but they do not make a misconfigured change safe by themselves. Access, secret protection, review, and operational recovery remain separate controls.
Terraform and GitOps are related, but not the same thing
Terraform is an IaC tool; GitOps is an operating approach that treats a Git repository as the source of truth for application and infrastructure configuration. In a GitOps flow, merging a reviewed change can trigger automated plans and deployment, while reconciliation can detect resources changed outside Git. HashiCorp’s Well-Architected Framework describes GitOps in these terms and connects it with an auditable review trail and less manual execution variance.
The distinction matters in practice: Terraform can be used in a Git-based workflow without every part of that workflow being GitOps. A team adopting GitOps must decide how merged changes are applied, how actual resources are reconciled with the repository, and how to handle approved exceptions. A repository can be the declared source of truth only if the team has a process for addressing changes made outside it.
Detect and resolve infrastructure drift
Drift is a mismatch between the infrastructure declared in Git and the resources that actually exist. It can arise when someone changes infrastructure outside the normal IaC path or when the declared configuration no longer reflects an approved operational exception. Drift detection is useful only when the team decides what to do with the mismatch.
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- Classify the difference. Determine whether it is an unauthorized change, an intentional exception, or a needed update to the declaration.
- Choose the source of correction. If the change should not exist, reconcile infrastructure back to the approved declaration. If it is an approved exception or desired change, update and review the Git configuration so the record matches the intended state.
- Record exceptions. Document approved departures from the standard and define who owns them and how they will be revisited.
Do not normalize unexplained drift by simply editing configuration to match whatever is present. First establish whether the live change is safe and authorized; otherwise, that approach can turn an unreviewed change into the new declared standard.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose an IaC approach by operational fit
Terraform, OpenTofu, cloud-native templates, Pulumi, and GitOps controllers are options to evaluate, but the useful decision is not a popularity contest. The team should compare how each approach fits its platforms, ownership model, review process, security requirements, and recovery needs. The following questions make that comparison concrete without assuming that any one tool has the same capabilities or operating model in every deployment.
| Evaluation area | What the team should establish |
|---|---|
| Provider and platform coverage | Does the approach cover the cloud, on-premises, Kubernetes, or SaaS APIs the team needs to manage? |
| Configuration model and reuse | How are desired resources declared, and how are reusable modules or components maintained? |
| State, locking, and drift | Where is state held, how is concurrent work controlled, and how are changes outside Git detected and reconciled? |
| Plan or preview quality | Can reviewers clearly identify proposed changes, destructive replacements, and dependency effects before applying them? |
| Policy and secret handling | Can the team enforce required policy checks and keep credentials and sensitive values out of Git and appropriately protected? |
| Pull-request and automation fit | Can the approach support the team’s validation, review, approval, and deployment flow? |
| Rollback and recovery | How will the team recover from a failed or harmful change, and what operational skills will that recovery require? |
| Licensing and governance | Do the tool’s licensing and governance model fit the organization’s requirements? |
Terraform
Evaluate Terraform where its providers, HCL configuration, modules, state workflow, and plan-and-apply cycle fit the team’s platforms and governance. Its state and plan are central to the workflow, so review state security and the quality of proposed diffs as part of the evaluation.
OpenTofu
Assess OpenTofu against the same practical criteria rather than assuming that a familiar configuration or workflow answers every governance question. Verify the provider and platform coverage, state and locking behavior, review experience, and licensing requirements relevant to your environment.
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Consider cloud-native templates when the team’s infrastructure scope and ownership align with the platforms those templates target. Confirm coverage for any services or environments beyond that scope, and assess how templates fit shared review, policy, and recovery practices.
Pulumi
Evaluate Pulumi by looking at its configuration and component model, platform coverage, preview and review process, policy controls, and the skills the team must operate. The right choice depends on how well those characteristics fit team capabilities and ownership boundaries.
GitOps controllers
Evaluate GitOps controllers as part of a reconciliation model: establish what configuration in Git governs, how changes are applied, and how out-of-band changes are detected and handled. GitOps describes an operating method, so compare it with IaC tools as a workflow and control model rather than treating the labels as interchangeable.
Measure whether the system improves reliability
IaC automation and internal developer platforms can improve how infrastructure work is delivered, but a platform can also harm change stability and throughput if implemented poorly. DORA’s 2024 report identifies infrastructure flexibility as a direct contributor to organizational performance and notes both the potential benefits and risks of internal developer platforms. That is a reason to measure outcomes in your own service and organization rather than promise a universal improvement.
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- Track failed changes and the time needed to roll them back or recover.
- Watch change stability and throughput as infrastructure automation or a platform expands.
- Measure alert load and operational toil removed, not just the number of pipelines or automated applies.
- Review whether engineers can make safe changes through the intended path, and whether exceptions and manual actions are increasing.
Use those measures to adjust controls and platform scope. Automation that makes changes faster but leaves teams slower to detect or recover from failures is not a reliability improvement.
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