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Terraform in 2025: relevance, challenges and alternatives
Even if you're not a Terraform fan, there's a good chance you'll have to support it—especially on projects with a history. Terraform starts to “creak” when the infrastructure becomes really large and multilevel.: **There is no built-in support for multiregionality and multienvironment**. **Managing dependencies between parts of the infrastructure is inconvenient**. **State files without an external backend (S3, GCS, etc.) are a pain**. **It is difficult to share resources between teams without Enterprise solutions**. … - They support a **limited number of cases**, and are often incompatible with existing configs. - They require a separate CLI utility for signing manifests. Opinions in the industry are divided: some find them useful, while others consider them a “crude solution with a good idea.” ... … Positive: - You can use familiar data structures, loops, and conditions. - They are better suited for developers than DevOps engineers. Minuses: - Steep learning curve for ops teams. - Difficulties with typing (especially in CDK). - Not all clouds and resources are supported on par with Terraform. Many teams, having tried the CDK, then return to Terraform due to the inability to easily delegate maintenance to DevOps engineers.
Related Pain Points3件
Local state files without remote backends cause team collaboration and disaster recovery issues
8State files stored locally (default) instead of on remote backends (S3, GCS) prevent team collaboration, create single points of failure, and make disaster recovery impossible. Developers must manually manage state file access.
Resource sharing between teams requires paid Enterprise Terraform solutions
6Terraform community edition lacks built-in mechanisms for cross-team resource sharing, forcing organizations without Terraform Enterprise to build custom state management solutions or invest in expensive enterprise licensing.
Workspace-based multi-environment management requires excessive conditional logic
6Using Terraform workspaces to manage multiple environments (dev, staging, prod) requires heavy use of count parameters and conditional expressions, making code difficult to read and understand. Scaling across environments becomes increasingly complex as interconnections multiply.