Organizations are rapidly building AI applications, deploying AI agents, and scaling Azure environments faster than ever before.
As AI initiatives accelerate and the volume of code expands, many organizations discover they have lost visibility into the infrastructure supporting those workloads.
Resources created outside standard workflows, unmanaged environments, and infrastructure drift create governance, security, and operational challenges that become increasingly difficult to control at scale.
The challenge is no longer simply adopting infrastructure as code (IaC). It is continuously discovering, governing, and bringing Azure infrastructure back into alignment as cloud and AI environments evolve.
»The hidden drift: How unmanaged infrastructure emerges
Infrastructure drift rarely happens because teams ignore best practices. It happens because real-world operations rarely follow clean architectural plans.
A developer provisions a resource directly in the Azure portal to test an idea. A proof-of-concept AI application is deployed quickly and later promoted into production. A late-night incident leads to a manual fix that never gets codified. A newly acquired team brings Azure subscriptions that were never managed with Terraform.
Each decision is reasonable in isolation, and none of them stem from malice, but collectively, they create a growing layer of shadow infrastructure that exists outside Terraform.
Over time, organizations find themselves operating in two parallel worlds: one that is version-controlled and governed, and another that is opaque, manually managed, and difficult to reason with.
»Why AI makes drift worse
AI workloads introduce a new layer of infrastructure complexity at a rapid pace. As AI adoption accelerates, infrastructure surface area and churn increases. Without a consistent operating model, organizations can lose visibility into what exists, who created it, and whether it complies with organizational standards.
Discover AI and cloud infrastructure at scale
Terraform query enables teams to identify resources across Azure environments, including resources that were never provisioned through Terraform, helping organizations discover unmanaged infrastructure, identify shadow IT, and establish a complete inventory of cloud assets.
»Discovering unmanaged Azure resources
Terraform's declarative import workflows and configuration generation capabilities help organizations rapidly onboard unmanaged Azure infrastructure into version-controlled workflows, with equal support for human and agentic operators.
For example, teams can search for specific resource types across subscriptions: list "azurerm_nat_gateway" "unmanaged" {
provider = azurerm
}
list "azurerm_network_security_group" "unmanaged" {
provider = azurerm
}
Terraform can then enumerate matching resources:
terraform query
This allows platform teams to:
Discover unmanaged infrastructure
Identify shadow IT environments
Locate AI experimentation environments
Establish a more complete inventory of cloud assets
Rather than relying on periodic audits, teams gain continuous visibility into infrastructure across Azure environments.
»Govern with policy as code
Using Sentinel, organizations can evaluate infrastructure changes in real time and enforce standards for security, compliance, cost management, and operational consistency before changes are deployed.
Sentinel enables teams to define policy as code and evaluate infrastructure changes before they are deployed.
For example, organizations can enforce tagging standards:
import "tfplan/v2" as tfplan
# target resources that are being created or updated (ignore deleted resources and data sources)
relevant_resources = filter tfplan.resource_changes as address, rc {
rc.mode is "managed" and
(rc.change.actions contains "create" or
rc.change.actions contains "update")
}
violations = []
for relevant_resources as address, rc {
tags = rc.change.after.tags else {}
owner = tags.owner else null
if owner is null {
append(violations, address + " is missing `owner` tag")
}
}
# print any violations in the output
for violations as v {
print(v)
}
# policy will pass ONLY when there are no violations
main = rule {
length(violations) is 0
}
»Governance extends beyond infrastructure
HashiCorp Vault helps organizations secure machine identities, secrets, API credentials, and access to AI workloads through dynamic credentials, short-lived secrets, and identity-based access controls.
»From drift to control: a continuous lifecycle
When discovery, management, and governance operate together, they form a continuous system that continuously brings infrastructure back into alignment with organizational standards.
»Why this matters now
Azure environments are becoming more dynamic, more distributed, and more complex. Terraform helps organizations bring infrastructure back into alignment with code, while Vault helps ensure access remains governed, auditable, and secure. Ready to improve visibility and governance across your Azure environment? Learn how Terraform and Vault help organizations discover unmanaged infrastructure, enforce policy-driven governance, and establish a scalable operating model for cloud and AI workloads.
