GENERALIZED METHOD FOR MANAGING THE LIFECYCLE OF TERRAFORM INFRASTRUCTURE ACROSS MULTIPLE ENVIRONMENTS

Abstract

The article examines the challenge of managing the lifecycle of cloud infrastructure, as described using Terraform, across multiple environments (development, staging, and production). In industrial settings, multi-environment infrastructure management gives rise to a set of interrelated challenges: the absence of formalized procedures for promoting changes between environments with explicit source readiness verification, fragmented compliance checking that fails to distinguish code-level syntax validation from plan-level semantic verification, and configuration drift detection that lacks classification by severity, generating false alerts for expected changes such as dynamic IP addresses and rotated certificates. An analysis of existing approaches to environmental isolation, configuration compliance verification, and drift detection reveals that none of the current methods address the full lifecycle in a unified manner. A generalized method is proposed, based on a formalized two-projection lifecycle model: the horizontal projection describes an eight-stage finite automaton of an individual environment (Init, Author, Validate, Plan, Comply, Approve, Apply, Monitor), while the vertical projection defines a partially ordered environment space with a formalized promotion operation. The method introduces a source readiness precondition requiring the source environment to be in the monitoring stage with empty planning and drift deltas, versioned configuration snapshots ensuring code identity across environments, multi-level compliance verification across code, plan, and state levels using hierarchical policy inheritance, and a three-class drift classification (critical, actionable, informational) with an effective delta mechanism that filters expected changes. Experimental verification on a real multi-environment AWS infrastructure (27 managed resources, 3 environments) using the Scalr platform confirms that the proposed method ensures automated detection of 100% of policy violations before the apply stage (compared to 50% for GitOps CI/CD and 0% for Terraform CLI), reduces false drift alerts to zero, and decreases the number of manual promotion steps to a single approval for the production environment.