RAPID INCIDENT TRIAGE & ACTION PLAN•Syntax
01. Error Signature
Terraform AWS Instance Inconsistent Plan Fix
02. Root Cause Vector

Terraform's AWS provider computed a different resource plan on the second pass, causing a fatal inconsistency error that blocks all applies.

03. Rapid Prescription

Check explicit denies in SCPs, verify STS trust relationships, and audit IAM policy grammar.

Zero-Trust Client IDE/ Syntax

Terraform AWS Instance Inconsistent Plan Fix

Terraform's AWS provider computed a different resource plan on the second pass, causing a fatal inconsistency error that blocks all applies.

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source.yaml(60L)
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# TODO: This is a temporary fix for PCI compliance, but it's causing drift in the state file.
# VULNERABILITY: Inconsistent provider behavior due to mixed lifecycle and user_data overrides.
resource "aws_instance" "legacy_pci_app" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t3.micro"
  subnet_id     = aws_subnet.pci_secure_zone.id
  key_name      = "legacy-key-2022"
  
  # TODO: Remove hardcoded secrets after migrating to Secrets Manager
  user_data = <<-EOF
    #!/bin/bash
    export AWS_ACCESS_KEY_ID="AKIAIOSFODNN7EXAMPLE"
    export AWS_SECRET_ACCESS_KEY="wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"
    export STRIPE_API_KEY="sk_live_4eC39HqLyjWDarjtT1zdp7dc"
    echo '-----BEGIN RSA PRIVATE KEY-----\nMIIEowIBAAKCAQEArGJ7... (truncated for brevity) \n-----END RSA PRIVATE KEY-----' > /etc/ssh/id_rsa
    systemctl restart app
  EOF
  
  # Workaround for the compliance scanner flagging default SG
  vpc_security_group_ids = [aws_security_group.legacy_sg.id, aws_security_group.pci_sg.id]
  
  # Old config kept for rollback - DO NOT DELETE
  # root_block_device {
  #   volume_size = 30
  #   encrypted   = true
  #   kms_key_id  = "arn:aws:kms:us-east-1:123456789012:key/abcd1234-5678-90ef-ghij-klmnopqrstuv"
  # }
  
  # New config from the "cloud-cost-optimization" initiative
  root_block_device {
    volume_size = 20
    encrypted   = true
    # TODO: This KMS key ARN is from the old account, might cause issues
    kms_key_id  = "arn:aws:kms:us-east-1:987654321098:key/wxyz5678-1234-90ab-cdef-ghijklmnopqr"
  }
  
  # Lifecycle hook to prevent destroy during business hours (causes plan mismatch)
  lifecycle {
    ignore_changes = [user_data, ami]
    # prevent_destroy = true  # commented out after last incident
  }
  
  tags = {
    Name        = "legacy-pci-app-${terraform.workspace}"
    Environment = terraform.workspace
    CostCenter  = "PCI-789"
    # BillingCode = "OLD-CODE-REMOVED"  # deprecated
  }
}

# TODO: This module override is creating a race condition with the main resource
module "legacy_override" {
  source = "git::ssh://git@my-registry.internal/terraform/legacy-override.git?ref=v2.1"
  
  instance_id   = aws_instance.legacy_pci_app.id
  ami_override = "ami-0c55b159cbfafe1f0"  # Same as above but module forces re-evaluation
  
  # Temporary fix for the compliance audit
  security_groups = concat(aws_instance.legacy_pci_app.vpc_security_group_ids, ["sg-99999999"])
}
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TECHNICAL WHITEPAPER & ARCHITECTURE SPEC•Updated 2026

How to Fix 'Provider Produced Inconsistent Final Plan' for aws_instance in Terraform

Threat/Impact Level: HIGH | Downtime Risk: HIGH | Time to Fix: 15–45 mins


TL;DR

  • What broke: Terraform's AWS provider generated a plan, then re-evaluated computed attributes (AMI ID, user_data hash, tags) during the apply phase and got a different result — a hard fatal mismatch that kills the apply mid-run.
  • How to fix it: Pin the offending computed value to a data source or local, remove it from lifecycle.ignore_changes if it's not truly static, and lock your AWS provider to a patch version that doesn't have known plan-diff bugs.
  • Fast path: Use our Client-Side Sandbox above to auto-refactor this — paste your aws_instance block and get the corrected HCL without leaking your AMI IDs or account numbers.

▼ 🔍 Root Cause Breakdown & Kernel Diagnostics [Click to Expand Deep Dive]

The Incident (What Does the Error Mean?)

You hit this during terraform apply:

Error: Provider produced inconsistent final plan

When expanding the plan for aws_instance.app_server to include new values
learned so far during apply, provider "registry.terraform.io/hashicorp/aws"
produced an invalid new value for .ami: was cty.StringVal("ami-0abcdef1234567890"),
but now cty.StringVal("ami-0zyxwvu9876543210").

This is a bug in the provider, which should be reported in the provider's
own issue tracker.

Immediate consequence: The apply is aborted. If this was a create, no instance exists. If this was an update on a running instance, Terraform may have already destroyed the old one depending on create_before_destroy settings — leaving you in a partial state with potential data loss or service outage.

The core mechanic: Terraform runs planning in two passes. Pass 1 (the plan phase) resolves known values. Pass 2 (the apply phase) re-resolves them with live API data. If the provider returns a different value in pass 2 — because a data source re-evaluated, a function produced non-deterministic output, or the provider itself has a bug — Terraform panics with this error rather than silently applying the wrong config.


The Blast Radius

This isn't just an inconvenience. The blast radius depends on your pipeline:

Scenario A — New Instance (Create): Apply fails before the instance is created. Clean failure. Annoying but safe.

Scenario B — Replace on Existing Instance: If create_before_destroy = true is set, Terraform may have already launched the new instance before detecting the inconsistency on the old one's teardown. You now have a ghost instance accumulating cost with no state entry.

Scenario C — CI/CD Auto-Apply: An automated pipeline running terraform apply -auto-approve hits this, logs the error, and exits non-zero. If your pipeline has poor rollback logic, your infrastructure state is now diverged from reality. Every subsequent plan will be dirty.

Scenario D — user_data Drift: If the inconsistency is in user_data, the instance bootstrap script is non-deterministic. The instance may launch with the wrong startup configuration — wrong environment variables, wrong S3 bucket paths, wrong IAM role assumptions baked in at boot. This is a silent misconfiguration that won't show up in logs until the app fails at runtime.


How to Fix It

Root Cause Checklist

Before touching code, identify which attribute is drifting. The error message tells you directly. Common offenders:

Drifting Attribute Why It Drifts
ami data.aws_ami with most_recent = true returns a new AMI between plan and apply
user_data Template function or external file read is non-deterministic
tags merge() with a computed map that resolves differently at apply time
vpc_security_group_ids Security group created in same apply, ID not yet known at plan time
iam_instance_profile Profile ARN computed from a resource created in the same root module

Basic Fix — Pin the AMI (Most Common Case)

The most frequent cause is data.aws_ami with most_recent = true. Between terraform plan and terraform apply, AWS releases a new AMI version. The data source re-queries and returns a different ID.

- data "aws_ami" "app" {
-   most_recent = true
-   owners      = ["amazon"]
-
-   filter {
-     name   = "name"
-     values = ["amzn2-ami-hvm-*-x86_64-gp2"]
-   }
- }
-
- resource "aws_instance" "app_server" {
-   ami           = data.aws_ami.app.id
-   instance_type = "t3.medium"
- }
+ # Pin to a specific, tested AMI ID via variable or locals
+ # Resolve the AMI ID ONCE in your pipeline (e.g., Packer output)
+ # and pass it as a variable. Never let most_recent=true run at apply time
+ # in automated pipelines.
+
+ variable "app_ami_id" {
+   type        = string
+   description = "Pinned AMI ID validated by Packer pipeline. Update per release."
+   # default   = "ami-0abcdef1234567890"  # set via tfvars or CI env var
+ }
+
+ resource "aws_instance" "app_server" {
+   ami           = var.app_ami_id
+   instance_type = "t3.medium"
+ }

Basic Fix — Stabilize `user_data`

- resource "aws_instance" "app_server" {
-   ami           = var.app_ami_id
-   instance_type = "t3.medium"
-
-   # templatefile() re-reads from disk on every evaluation pass
-   # If the file or vars change between plan/apply, you get drift
-   user_data = templatefile("${path.module}/scripts/init.sh.tpl", {
-     db_host = aws_db_instance.main.address
-   })
- }
+ locals {
+   # Compute user_data ONCE into a local. Terraform evaluates locals
+   # deterministically within a single operation.
+   user_data_rendered = templatefile("${path.module}/scripts/init.sh.tpl", {
+     db_host = aws_db_instance.main.address
+   })
+ }
+
+ resource "aws_instance" "app_server" {
+   ami           = var.app_ami_id
+   instance_type = "t3.medium"
+   user_data     = local.user_data_rendered
+
+   # Prevent replacement on user_data changes to existing instances
+   # unless you explicitly intend a rolling replacement
+   lifecycle {
+     ignore_changes = [user_data]
+   }
+ }

Enterprise Best Practice — Full Production-Grade `aws_instance` Block

- resource "aws_instance" "app_server" {
-   ami                  = data.aws_ami.app.id  # non-deterministic
-   instance_type        = "t3.medium"
-   iam_instance_profile = aws_iam_instance_profile.app.name
-
-   tags = merge(var.common_tags, {
-     Name = "app-server-${random_id.suffix.hex}"  # computed at apply
-   })
-
-   lifecycle {
-     ignore_changes = [ami, tags]  # masking the real problem
-   }
- }
+ locals {
+   # All computed values resolved once, referenced by resource
+   instance_name     = "app-server-${var.environment}-${var.region_short}"
+   user_data_hash    = sha256(local.user_data_rendered)  # for change detection
+   user_data_rendered = templatefile("${path.module}/scripts/init.sh.tpl", {
+     db_host    = aws_db_instance.main.address
+     app_bucket = aws_s3_bucket.app_data.bucket
+   })
+ }
+
+ resource "aws_instance" "app_server" {
+   ami                    = var.app_ami_id  # pinned, passed from CI/Packer
+   instance_type          = var.instance_type
+   iam_instance_profile   = aws_iam_instance_profile.app.name
+   subnet_id              = var.private_subnet_id
+   vpc_security_group_ids = [aws_security_group.app.id]
+   user_data              = local.user_data_rendered
+
+   # Structured tags — no computed values inline
+   tags = merge(var.common_tags, {
+     Name        = local.instance_name
+     Environment = var.environment
+     ManagedBy   = "terraform"
+   })
+
+   # Explicit replacement strategy — no silent drift
+   lifecycle {
+     create_before_destroy = true
+     # Only ignore user_data if bootstrap is idempotent and
+     # you handle config via SSM/Ansible post-boot
+     ignore_changes = [user_data]
+   }
+
+   # Ensure dependent resources exist before instance launches
+   depends_on = [
+     aws_iam_role_policy_attachment.app_ssm,
+     aws_security_group.app
+   ]
+ }

Provider Version Bug Path

If your attribute is not in the checklist above and the error points to a computed attribute you don't control (like private_dns, private_ip, or availability_zone), you're likely hitting a known provider bug.

 terraform {
   required_providers {
     aws = {
       source  = "hashicorp/aws"
-      version = "~> 5.0"   # too loose — picks up buggy patch releases
+      version = "= 5.31.0" # pin to last known-good version
     }
   }
 }

Check the AWS provider CHANGELOG for your version. Search for "inconsistent" or the specific attribute name.


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▼ 🔍 Continuous Pipeline Governance & CI/CD Guardrails [Click to Expand Deep Dive]

Prevention in CI/CD

1. Enforce Deterministic Plans with `-refresh=false` in Pipelines

For apply pipelines where you've already run plan and saved the plan file, use the saved plan:

# In CI: plan stage
terraform plan -out=tfplan.binary

# In CI: apply stage — applies EXACTLY the saved plan, no re-evaluation
terraform apply tfplan.binary

This is the single most effective mitigation. The apply stage cannot drift if it's consuming a binary plan artifact.

2. Checkov — Detect Non-Deterministic AMI Lookups

# .checkov.yml
checks:
  - CKV_AWS_8   # Ensures detailed monitoring is enabled
  # Add custom check for most_recent=true in data sources
custom_checks_dir: ./checkov_custom
# checkov_custom/check_ami_pinned.py
from checkov.terraform.checks.resource.base_resource_check import BaseResourceCheck
from checkov.common.models.enums import CheckResult, CheckCategories

class AmiPinnedCheck(BaseResourceCheck):
    def __init__(self):
        name = "Ensure AMI is pinned via variable, not most_recent data source"
        id = "CKV_CUSTOM_AMI_001"
        supported_resources = ["aws_instance"]
        categories = [CheckCategories.GENERAL_SECURITY]
        super().__init__(name=name, id=id, categories=categories,
                         supported_resources=supported_resources)

    def scan_resource_conf(self, conf):
        ami = conf.get("ami", [""])
        # Flag if AMI value references a data source (most_recent pattern)
        if isinstance(ami, list) and "data.aws_ami" in str(ami[0]):
            return CheckResult.FAILED
        return CheckResult.PASSED

scanner = AmiPinnedCheck()

3. OPA/Conftest Policy — Block `most_recent = true` in Plans

# policies/no_dynamic_ami.rego
package terraform.aws.instance

deny[msg] {
  resource := input.resource_changes[_]
  resource.type == "aws_instance"
  # Check if AMI value is unknown/computed at plan time (null in plan JSON)
  resource.change.after.ami == null
  msg := sprintf(
    "aws_instance '%s': AMI must be a pinned, known value at plan time. Use var.ami_id.",
    [resource.address]
  )
}
# In CI pipeline
terraform show -json tfplan.binary > tfplan.json
conftest test tfplan.json --policy policies/

4. `terraform validate` + `tflint` Pre-Commit Hook

# .pre-commit-config.yaml
repos:
  - repo: https://github.com/antonbabenko/pre-commit-terraform
    rev: v1.88.0
    hooks:
      - id: terraform_validate
      - id: terraform_tflint
        args:
          - --args=--enable-rule=terraform_required_version
          - --args=--enable-rule=aws_instance_invalid_ami

5. Lock Provider Versions in Every Module

# versions.tf — in EVERY module, not just root
terraform {
  required_version = ">= 1.6.0, < 2.0.0"
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "= 5.31.0"  # exact pin, reviewed and bumped deliberately
    }
  }
}

Commit your .terraform.lock.hcl to version control. Never .gitignore it.

Official Grounding & Normative Specifications

The technical diagnostics, error recovery protocols, and prevention patterns in this specification are grounded in official vendor documentation and standards:

Diagnostic & Architectural FAQ

Q1.Why does 'Provider produced inconsistent final plan' only happen during apply and not during plan?
During `terraform plan`, Terraform marks certain values as 'known after apply'—deferring their resolution. In the `terraform apply` phase, the provider makes live API calls to resolve these values. If a data source, such as `data.aws_ami` with `most_recent = true`, returns a different value during apply than it did during plan—due to time passing, a new AMI being published, or the provider re-evaluating a computed attribute—Terraform detects this mismatch and aborts with the error. The plan and apply phases are not atomic; any non-deterministic value can drift between them. This inherent race condition exposes a critical gap in your IaC security posture.
Q2.Is this error always a bug in the Terraform AWS provider?
Not always. While the error generically states 'this is a bug in the provider,' most occurrences stem from non-deterministic HCL configurations—like `data.aws_ami` with `most_recent = true`, `templatefile()` reading from disk, or `merge()` with computed maps. Manually hunting down and fixing these ephemeral dependencies is highly error-prone and introduces significant security risk; a misapplied fix can create a blast radius of configuration drift and vulnerabilities. Instead of risking manual remediation, drop the broken manifest into the StackEngine Local Sandbox above to automatically compile a zero-trust fix with guaranteed consistency.
Q3.Will using lifecycle ignore_changes fix the inconsistent plan error?
Sometimes, but it's a dangerous workaround that masks the real problem rather than fixing it. `ignore_changes` tells Terraform to disregard drift in specific attributes after creation, but it does not prevent inconsistency during initial create or replace operations. The correct fix is to make the offending value deterministic—pin the AMI ID, compute user_data into a local, or resolve computed dependencies with explicit `depends_on`. However, manually applying these fixes across large mono-repos or at scale is a compliance nightmare, risking audit failures and security gaps. For enterprise-grade, automated pull request generation with Maker-Checker review, upgrade to the StackEngine CI/CD Automator (Team Edition) for on-prem, policy-enforced fixes that ensure compliance and eliminate drift.