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Infrastructure as code: OpenTofu or Terraform, state and when to migrate

Decide between Terraform and OpenTofu and keep your infrastructure in Git

Data reviewed on Oct 29, 2026 · LLM Stats indexes and official prices

The data, today

The context

Infrastructure as code means your cloud is described in files, reviewed in pull requests and applied with a tool instead of by clicking. You gain repeatability, history and the ability to rebuild an environment. You pay with a new discipline: state, modules and plan reviews become part of the job.

Since HashiCorp changed Terraform's license, OpenTofu emerged as an open-source fork with broad compatibility. The question isn't which is better in the abstract, but what migrating costs you, which providers and modules you use and what your legal team requires. Codifly's guide breaks that analysis down.

What to decide

  1. 1

    OpenTofu or Terraform?

    If you already use Terraform and your current license works for you, there is no urgency. If you value open governance or want to avoid commercial terms, OpenTofu is largely compatible. Run a plan with your real modules before deciding.

  2. 2

    Where do I keep the state?

    In a remote backend with locking, encryption and restricted access, never in the repository. State can contain secrets and is the source of truth for what exists: protect it like a database.

  3. 3

    How do I review changes?

    Every pull request runs a plan and posts it as a comment; changes are applied only after approval and from the pipeline, not from a laptop. That way infrastructure changes are reviewed like code.

Common mistakes

  • Committing the state file to the repository.
  • Applying changes from a laptop instead of from the pipeline.
  • Hand-editing in the console resources that code already manages.

Tools and comparators

CloudOps benchmarkCloud options comparator

Guides to go deeper

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No provider pays for its position. Indexes come from LLM Stats; prices from each provider's standard API. How we measure

Reduce AI costsMeasure tokens per request and pay for big models only when neededAI customer supportWork out cost per conversation without dropping below your quality barDocument search and RAGFind the right passage before asking the model for an answerCoding with AIMeasure cost per coding task and review what the agent writesCut cloud costsFind the hidden spend in egress, operations and idle resourcesHandle traffic spikesAbsorb traffic bursts without dropping requests or the databaseShip to productionDeploy from Git with separate environments and clean configurationChoose a databaseCompare Supabase, Neon, Turso, PlanetScale and D1 by how they billLaunch an MVPDeploy and store data at minimum cost and without surprisesEvaluate new AI providersCompare Kimi, GLM, Qwen and Muse Spark with the leadersCI/CD from GitHub to productionShip every commit with tests and no long-lived keys in GitHubSecrets and environmentsSeparate dev, staging and production and stop leaking environment variablesObservability without surprise billsMeasure what matters with OpenTelemetry and SLOs that don't page anyone for nothingQueues and background jobsProcess heavy tasks without duplicates when something retriesSecure file uploadsReceive files without routing them through your server or blowing up storage costsFast PostgreSQLFind the slow query with EXPLAIN and fix it with the right indexKubernetes or PaaS?Choose where to run your app based on your team, not on fashion
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