Terraform Guardrail Multi-Cloud Policy (MCP) (TerraGuard) is an enterprise-grade IaC governance and guardrail platform that enforces architectural intent, compliance, and platform standards directly inside CI/CD. It runs outside Terraform and gives AI assistants and platform teams real provider context, policy intelligence, and auditable guardrails so every change is safer by default. The result is a cleaner state, fewer failures, and a shorter path from idea to production.
This product is built for teams shipping infrastructure at scale who need speed without sacrificing safety. Guardrail enforces non-negotiable platform invariants, allows composable product constraints, and produces human-readable reports that make decisions obvious and defensible.
It offers an easy way to generate valid Terraform code and ensure compliance. This tool helps your team manage cloud resources more effectively. With a user-friendly CLI and a minimal web UI, you do not need a technical background to get started.
Live app: https://terraform-guardrail.streamlit.app/
Making Infrastructure Governance Executable
Despite using Terraform and security scanners, enterprises still face:
- Inconsistent enforcement across teams
- Policies applied too late in delivery
- Manual reviews that don’t scale
- Different interpretations of “standards”
- Audit findings caused by drift, not intent
👉 The issue is not lack of tools —
👉 The issue is lack of a governance distribution mechanism.
Terraform-Guardrail Multi-Cloud Policy (MCP) is an enterprise-grade IaC governance and guardrail platform for Terraform that enforces architectural intent, compliance, and platform standards directly in CI/CD.
It:
- Establishes a non-negotiable safety floor
- Distributes guardrails consistently via CI/CD
- Enables progressive enforcement (Advisory → Warn → Strict)
- Makes governance versioned, auditable, and repeatable
Governance becomes code, not documents.
| Layer | Role |
|---|---|
| Terraform-Guardrail Multi-Cloud Policy (MCP) | Governance & enforcement orchestration |
| Checkov / tfsec / Terrascan | Deep static security & compliance scanning |
| OPA / Sentinel | Advanced & runtime policy enforcement |
| CI/CD (GitLab/GitHub) | Execution & control point |
Terraform-Guardrail does not replace existing tools — it connects and operationalizes them.
Every Terraform change passes through the same guardrails, before it ever reaches the cloud.
Implemented at:
- Merge request / pull request stage
- GitLab group-level CI enforcement
- No per-repo negotiation
| Phase | Mode | Business Outcome |
|---|---|---|
| Phase 1 | Advisory | Visibility, zero disruption |
| Phase 2 | Warn | Accountability without blocking |
| Phase 3 | Strict | Mandatory compliance for prod |
✔ No “big-bang” rollout
✔ Teams keep autonomy above the safety floor
Without it:
- Governance relies on people & process
- Controls drift over time
- Audit remediation is expensive
With it:
- Governance is automatic and consistent
- Security shifts left into CI
- Audit evidence is generated by default
- Platform teams scale without becoming bottlenecks
Terraform-Guardrail Multi-Cloud Policy (MCP) turns infrastructure governance
from guidelines into guarantees.
It enables speed and safety — without trading one for the other.
Non-negotiable safety floor, composable freedom above it. Guardrails live outside Terraform so platform teams can enforce baseline invariants while product teams retain agility.
flowchart LR
USER[Platform + Product Teams] --> CHANNELS[CLI / UI / REST API / CI]
CHANNELS --> GUARDRAIL[TerraGuard Control Plane]
GUARDRAIL --> POLICIES[Baseline + Context Policies]
GUARDRAIL --> REPORTS[Guidance + Evidence]
GUARDRAIL --> TERRAFORM[Safer Terraform Applies]
classDef actor fill:#e3f2fd,stroke:#1565c0,stroke-width:1px,color:#0d47a1;
classDef channel fill:#f3e5f5,stroke:#6a1b9a,stroke-width:1px,color:#4a148c;
classDef core fill:#e8f5e9,stroke:#2e7d32,stroke-width:1px,color:#1b5e20;
classDef output fill:#fff3e0,stroke:#ef6c00,stroke-width:1px,color:#e65100;
class USER actor;
class CHANNELS channel;
class GUARDRAIL,POLICIES core;
class REPORTS,TERRAFORM output;
flowchart TB
DEV[Developer] --> CLI[CLI]
DEV --> UI[Web UI]
DEV --> API[REST API]
DEV --> MCP["Multi-Cloud Policy (MCP)"]
DEV --> GHA[GitHub Action]
DEV --> GL[GitLab CI]
DEV --> ADO[Azure DevOps]
CLI --> GUARDRAIL[TerraGuard]
UI --> GUARDRAIL
API --> GUARDRAIL
MCP --> GUARDRAIL
GHA --> GUARDRAIL
GL --> GUARDRAIL
ADO --> GUARDRAIL
classDef actor fill:#e3f2fd,stroke:#1565c0,stroke-width:1px,color:#0d47a1;
classDef channel fill:#ede7f6,stroke:#5e35b1,stroke-width:1px,color:#311b92;
classDef core fill:#e8f5e9,stroke:#2e7d32,stroke-width:1px,color:#1b5e20;
class DEV actor;
class CLI,UI,API,MCP,GHA,GL,ADO channel;
class GUARDRAIL core;
- Multi-file scanning with summaries and CSV export
- Secret hygiene checks across
.tf,.tfvars, and.tfstate - Schema-aware validation with Terraform CLI integration
- Provider metadata lookup via Terraform Registry
- Multi-Cloud Policy (MCP) tools for scan, metadata, and snippet generation
- Streamlit and web UI for instant reporting
- Dockerized REST API for CI/CD adoption
- Docker Compose dev stack (API + UI + policy registry, optional analytics)
- OPA bundle-ready policy registry for guardrail packs
- Policy evaluation via OPA bundles with optional signature verification
- Minimal policy registry API (versions + audit history)
- AWS
- Azure
- GCP
- Kubernetes
- Helm
- OCI
- Vault
- Alicloud
- vSphere
Terraform-Guardrail provides first-class support for AWS environments and is designed to complement AWS-native governance services by enforcing pre-deployment, IaC-aware guardrails.
Unlike AWS-native controls that operate post-deployment or at the account boundary, Terraform-Guardrail enforces architectural, security, and compliance policies before Terraform apply, directly inside CI/CD pipelines.
- GitHub Actions (primary AWS CI integration)
- GitLab CI (widely used in regulated AWS enterprises)
- AWS CodePipeline + CodeBuild (via buildspec integration)
- Pre-apply guardrail enforcement for Terraform targeting AWS
- Account- and environment-aware policy evaluation
- OU-aligned guardrails (designed to complement AWS Organizations)
- Shift-left enforcement for Control Tower-aligned environments
- Evidence generation for audits (SOC2, ISO, PCI)
Terraform-Guardrail enables platform teams to define organization-wide AWS standards and ensure they are enforced consistently across accounts, pipelines, and teams — before infrastructure reaches AWS.
| Area | CLI | Web UI / Streamlit |
|---|---|---|
Config scan (.tf, .tfvars, .hcl) |
Yes | Yes |
State leak scan (.tfstate) |
Yes | Yes |
| Schema-aware validation | Yes | Yes |
| CSV export | No | Yes |
| Provider metadata | Yes | Yes |
| Snippet generation | Yes | No |
| Multi-file scan | Yes (directory) | Yes (upload up to 10) |
| Human-readable report | Yes | Yes |
| Policy bundle registry | Yes | No |
| Policy evaluation (OPA bundles) | Yes | No |
flowchart TB
subgraph Interfaces
CLI([CLI])
MCP(["Multi-Cloud Policy (MCP) Server"])
WEB([Web UI])
API([REST API])
STL([Streamlit App])
end
subgraph Core
SCAN((Compliance Engine))
GEN[[Snippet Generator]]
POLICY{Policy Layering}
end
subgraph Integrations
TF[/Terraform CLI/]
REG[(Terraform Registry)]
end
CLI --> SCAN
WEB --> SCAN
API --> SCAN
STL --> SCAN
MCP --> SCAN
MCP --> GEN
SCAN --> POLICY --> TF
GEN --> REG
classDef interface fill:#e3f2fd,stroke:#1e88e5,stroke-width:1px,color:#0d47a1;
classDef core fill:#e8f5e9,stroke:#2e7d32,stroke-width:1px,color:#1b5e20;
classDef integration fill:#fff3e0,stroke:#ef6c00,stroke-width:1px,color:#e65100;
class CLI,MCP,WEB,API,STL interface;
class SCAN,GEN,POLICY core;
class TF,REG integration;
flowchart TB
INPUTS[Inputs: .tf, .tfvars, .tfstate] --> PARSE[Parse & Normalize]
PARSE --> SCHEMA[Provider Schema + Metadata]
SCHEMA --> RULES[Apply Guardrail Rules]
RULES --> REPORT[Findings + Summary]
REPORT --> OUTPUTS["CLI JSON / UI / Multi-Cloud Policy (MCP) / REST"]
Note: Mermaid diagrams render on GitHub and in the Wiki. PyPI will show the raw blocks.
Legend: ✅ Delivered • 🚧 Planned
| Deliverable | v1.0 Foundation | v2.0 Enterprise | v3.0 Ecosystem | v4.0 Intelligent | Docs |
|---|---|---|---|---|---|
| Dockerized Multi-Cloud Policy (MCP) + REST API | ✅ Delivered (0.2.x) | Docs | |||
| CLI-first install | ✅ Delivered (0.2.x) | Docs | |||
| Docker Compose local stack (API + UI + registry) | ✅ Delivered (0.2.x) | Docs | |||
| GitHub Action pre-apply / PR checks | ✅ Delivered (0.2.x) | Docs | |||
| Central guardrail registry | ✅ Delivered (1.0.x) | Docs | |||
| Policy versioning + audit trail | ✅ Delivered (1.0.x) | Docs | |||
| Registry service image (GHCR) | ✅ Delivered (1.0.x) | Docs | |||
| Homebrew package (macOS) | ✅ Delivered (1.0.x) | Docs | |||
| Chocolatey package (Windows) | ✅ Delivered (1.0.x) | Docs | |||
| Linux install script (curl | bash) | ✅ Delivered (1.0.x) | Docs | |||
| GitLab CI templates | ✅ Delivered (1.0.x) | Docs | |||
| Azure DevOps / Pipeline extension | ✅ Delivered (1.0.x) | Docs | |||
| Policy layering model (base → env → app) | ✅ Delivered (1.0.x) | Docs | |||
| Custom rules (Option A/B + local bundles) | ✅ Delivered (1.0.x) | Docs | |||
| AWS CodePipeline + CodeBuild integration | 🚧 Planned | Docs | |||
| Policy authoring UI | 🚧 Planned | Docs | |||
| Policy metadata + rich failure messages | 🚧 Planned | Docs | |||
| Drift-prevention rules before apply | 🚧 Planned | Docs | |||
| Org-wide baselines | 🚧 Planned | Docs | |||
| Group-level enforcement | 🚧 Planned | Docs | |||
| Evidence export (SOC2 / ISO / PCI) | 🚧 Planned | Docs | |||
| Contributor governance + public roadmap | 🚧 Planned | Docs | |||
| Reference implementations across tools | 🚧 Planned | Docs | |||
| Cross-provider invariant enforcement | 🚧 Planned | Docs | |||
| Guardrails-as-a-Service API | 🚧 Planned | Docs | |||
| Enterprise policy packs | 🚧 Planned | Docs | |||
| Context-aware evaluation | 🚧 Planned | Docs | |||
| Suggested fixes + recommendations | 🚧 Planned | Docs |
Terraform Guardrail Multi-Cloud Policy (MCP) (TerraGuard) takes a fundamentally different approach to IaC governance than traditional scanning or linting tools. Guardrail is delivered as a Multi-Cloud Policy (MCP) server with a CLI and web UI. It runs outside Terraform, exposing provider metadata, scanning configs and state for sensitive values, and producing human-readable reports. Its rules engine focuses on secret hygiene and write-only arguments and lets platform teams publish non-negotiable guardrails while product teams compose contextual constraints.
By contrast, existing tools such as Checkov, TFLint and OPA/Conftest operate mainly as static code analyzers embedded in CI pipelines. They scan Terraform files or plans for misconfigurations but do not provide a centralized control plane or cross-provider context. The table below summarizes the key differences:
| Category | Guardrail Multi-Cloud Policy (MCP) | Checkov | TFLint | OPA/Conftest |
|---|---|---|---|---|
| Primary purpose | External IaC governance control plane | Static multi-IaC security scanner | Terraform linter | General policy engine (Rego) |
| IaC support | Terraform + multi-cloud providers (AWS, Azure, GCP, Kubernetes, Helm, OCI, Vault, vSphere, Alicloud) | Terraform, CloudFormation, Kubernetes, Helm, ARM, Serverless | Terraform (HCL) | Any domain via Rego policies |
| Policy model | Central guardrail registry; platform invariants + product constraints; versioned and auditable | Built-in rules (Python/Rego) + custom policies | Provider-specific rule plugins; experimental Rego plugin | Rego rules only |
| Enforcement stage | Pre-apply; prevents bad state and drift; uses provider schemas | Pre-apply scan of templates and plans | Pre-apply linting for errors and best-practice drifts | Pre-apply checks (via Conftest) – outcome depends on integration |
| Governance & audit | Org-level guardrail registry, ownership boundaries, audit trail | No policy lifecycle management | No policy registry | No governance features |
| Developer experience | CLI/Server/Web UI; human-readable reports & fix suggestions | CLI with JSON/SARIF/JUnit output and graph insights | CLI with JSON/SARIF/JUnit output; configurable warnings | CLI library; steep learning curve |
Checkov provides a vast policy library and graph-based resource analysis to catch misconfigurations early, and TFLint offers pluggable, provider-aware linting rules to detect invalid types, deprecated syntax and best-practice drifts. These tools remain valuable for static analysis of Terraform code. Guardrail Multi-Cloud Policy (MCP) builds upon them by acting as a higher-order control plane: it uses provider metadata to validate schema usage, prevents secret leakage and drift before Terraform mutates state, and separates platform-owned safety floors from product-level constraints. In practice, teams often run TFLint or Checkov in their CI to catch coding errors while Guardrail serves as the last line of defense to enforce organizational guardrails and deliver contextual guidance.
| Capability | Terraform-Guardrail | AWS Native Tools |
|---|---|---|
| Terraform pre-apply enforcement | ✅ Yes | ❌ No |
| CI/CD policy gate | ✅ Yes | ❌ No |
| IaC-aware guardrails | ✅ Yes | ❌ No |
| AWS Organizations awareness | 🚧 Planned | |
| Control Tower integration | 🚧 Companion mode | |
| Drift prevention (pre-deploy) | 🚧 Planned | ❌ Post-deploy only |
| Policy versioning & audit trail | ✅ Yes | ❌ Limited |
| Multi-cloud parity | ✅ Yes | ❌ AWS-only |
| Evidence export for audits | 🚧 Planned |
AWS-native governance tools are post-deployment and infrastructure-centric.
Terraform-Guardrail provides pre-deployment, architecture-aware, IaC-native guardrails that
complement AWS governance rather than replace it.
python -m venv .venv
source .venv/bin/activate
pip install -e "[dev]"
# CLI scan
terraform-guardrail scan examples
# snippet generation
terraform-guardrail generate aws aws_s3_bucket --name demo
# list policy bundles
terraform-guardrail policy list
# registry API
terraform-guardrail registry-api
# Multi-Cloud Policy (MCP) server (stdio)
terraform-guardrail mcp
# Web UI
terraform-guardrail webpip install terraform-guardrailPyPI: https://pypi.org/project/terraform-guardrail/ (latest: 1.0.5)
The examples/ folder provides practical CI simulations:
examples/fixtures/includes good and bad Terraform inputs (.tf,.tfvars,.hcl,.tfstate).examples/gitlab-ci/contains a GitLab template example and sample outputs.examples/github-actions/contains a GitHub Actions workflow and sample outputs.
Each example folder includes a README.md with steps and expected output formats (JSON, SARIF,
JUnit, CSV).
Packaging artifacts are generated on release tags. Homebrew and Chocolatey publishes are enabled when the release secrets are configured.
brew install Huzefaaa2/tap/terraform-guardrailchoco install terraform-guardrailcurl -sSL https://github.com/Huzefaaa2/terraform-guardrail/releases/latest/download/install.sh | bashPackaging details: docs/packaging.md.
Full CLI command reference: commands.md.
# scan a directory
terraform-guardrail scan ./examples --format json
# scan state files too
terraform-guardrail scan ./examples --state ./examples/sample.tfstate
# enable schema-aware validation (requires terraform CLI + initialized workspace)
terraform-guardrail scan ./examples --schema
# evaluate OPA policy bundle (requires opa CLI)
terraform-guardrail scan ./examples --policy-bundle baseline
# fail CI on medium+ findings
terraform-guardrail scan ./examples --fail-on mediumSee the full list on the wiki: https://github.com/Huzefaaa2/terraform-guardrail/wiki/Compliance-Rules
| Rule ID | Description | Severity |
|---|---|---|
| TG001 | Sensitive variable missing ephemeral = true |
Medium |
| TG002 | Hardcoded secret in config or tfvars | High |
| TG003 | Sensitive-looking value stored in state | High |
| TG004 | HCL parse error | Low |
| TG005 | Attribute not found in provider schema | Medium |
| TG006 | Public S3 bucket ACL detected | High |
| TG007 | Public S3 access block disabled | High |
| TG008 | Security group ingress open to the world | High |
| TG009 | IAM policy wildcard permissions | High |
| TG010 | Public IP association enabled on compute | Medium |
| TG011 | S3 bucket missing default encryption | Medium |
| TG012 | RDS storage not encrypted | Medium |
| TG013 | Load balancer listener uses HTTP | Medium |
| TG014 | Instance missing subnet/VPC boundary | Low |
| TG015 | RDS instance publicly accessible | High |
| TG016 | Missing mandatory resource tags | Low |
| TG017 | Resource region/location not in allowed list | Medium |
| TG018 | Instance type or SKU not in allowed list | Medium |
| TG019 | Azure storage account public network access enabled | Medium |
| TG020 | EBS volume not encrypted | Medium |
Option A — Environment knobs (no code):
export GUARDRAIL_REQUIRED_TAGS="owner,environment,cost_center"
export GUARDRAIL_ALLOWED_REGIONS="eastus,westus2"
export GUARDRAIL_ALLOWED_INSTANCE_TYPES="t3.medium,t3.large"
terraform-guardrail scan ./infraOption B — OPA policy bundles (recommended):
terraform-guardrail policy init --destination ./my-bundle --bundle-name guardrail
opa build --bundle ./my-bundle --output my-bundle.tar.gz
terraform-guardrail policy validate ./my-bundle.tar.gz
terraform-guardrail scan ./infra --policy-bundle-path ./my-bundle.tar.gzFull guide: https://github.com/Huzefaaa2/terraform-guardrail/wiki/Custom-Rules
Visit http://127.0.0.1:8000 and upload a Terraform file to view a compliance report.
streamlit run streamlit_app.pyLive app: https://terraform-guardrail.streamlit.app/
- Push this repo to GitHub.
- Create a new Streamlit Cloud app.
- Set the main file path to
streamlit_app.py. - Deploy (Streamlit will install from
requirements.txt).
Build and run the API server:
docker build -t terraform-guardrail .
docker run --rm -p 8080:8080 terraform-guardrailAPI endpoints:
GET /healthGET /metricsPOST /scanPOST /provider-metadataGET /policy-bundlesGET /policy-bundles/{bundle_id}POST /generate-snippet
Example request:
curl -X POST http://localhost:8080/scan \\
-H "Content-Type: application/json" \\
-d '{"path":"./examples","use_schema":false}'Pull the published container image (built on release tags):
docker pull ghcr.io/huzefaaa2/terraform-guardrail:latestRun it:
docker run --rm -p 8080:8080 ghcr.io/huzefaaa2/terraform-guardrail:latestRegistry API image:
docker pull ghcr.io/huzefaaa2/terraform-guardrail-registry:latest
docker run --rm -p 8090:8090 ghcr.io/huzefaaa2/terraform-guardrail-registry:latestBring up API + Streamlit UI + policy registry:
docker compose up --buildEnable optional analytics (Prometheus + Grafana):
docker compose --profile analytics up --buildService URLs:
- API: http://localhost:8080
- Streamlit UI: http://localhost:8501
- Policy registry (static): http://localhost:8081
- Policy registry API: http://localhost:8090
- Prometheus (analytics profile): http://localhost:9090
- Grafana (analytics profile): http://localhost:3000 (admin / guardrail)
More details: docs/docker-compose-guide.md.
The local policy registry exposes OPA bundles for guardrail packs. Fetch bundles with the CLI:
terraform-guardrail policy list
terraform-guardrail policy fetch baseline --destination ./policies
terraform-guardrail policy fetch baseline-signed --destination ./policiesPolicy evaluation runs only when --policy-bundle is provided. If a bundle includes verification
settings (public key + scope), the OPA CLI validates bundle signatures before evaluation.
Registry API (Compose): GET /bundles, GET /bundles/{id}/versions, GET /audit.
Signed bundle example:
- Bundle:
baseline-signed - Public key:
http://localhost:8081/keys/guardrail.pub
flowchart LR
subgraph ComposeStack[Docker Compose Stack]
UI([Streamlit UI])
API([REST API])
REG[(Policy Registry)]
REGAPI([Registry API])
PROM[[Prometheus]]
GRAF[[Grafana]]
end
UI --> API
API -.-> REG
REGAPI -.-> REG
API --> PROM
PROM --> GRAF
classDef core fill:#e8f5e9,stroke:#2e7d32,stroke-width:1px,color:#1b5e20;
classDef optional fill:#fff3e0,stroke:#ef6c00,stroke-width:1px,color:#e65100;
class UI,API,REG,REGAPI core;
class PROM,GRAF optional;
Apply layered guardrails in a predictable order:
terraform-guardrail scan infra \
--policy-base baseline \
--policy-env prod \
--policy-app paymentsEnvironment variables (alternative):
GUARDRAIL_POLICY_BASEGUARDRAIL_POLICY_ENVGUARDRAIL_POLICY_APP
Use the built-in action to scan Terraform changes on pull requests:
name: Guardrail
on:
pull_request:
paths:
- "**/*.tf"
- "**/*.tfvars"
- "**/*.hcl"
- "**/*.tfstate"
jobs:
guardrail:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Start local policy registry
run: |
python -m http.server 8081 --directory ops/policy-registry &
- uses: ./.github/actions/guardrail
with:
path: .
fail_on: medium
install_source: repo
policy_bundle: baseline-signed
policy_registry: http://localhost:8081When policy_bundle is set, the action installs OPA automatically and validates signatures (if
configured).
Include the shared template in your .gitlab-ci.yml:
include:
- project: "Huzefaaa2/terraform-guardrail"
ref: "v1.0.5"
file: "/.gitlab/terraform-guardrail.yml"Override variables as needed:
variables:
TERRAFORM_GUARDRAIL_SCAN_PATH: "infra"
TERRAFORM_GUARDRAIL_FAIL_ON: "high"
TERRAFORM_GUARDRAIL_FORMAT: "pretty"
TERRAFORM_GUARDRAIL_JSON_REPORT: "guardrail-report.json"
TERRAFORM_GUARDRAIL_WRITE_REPORT: "true"
TERRAFORM_GUARDRAIL_SARIF_REPORT: "guardrail-report.sarif"
TERRAFORM_GUARDRAIL_JUNIT_REPORT: "guardrail-report.junit.xml"
TERRAFORM_GUARDRAIL_WRITE_SARIF: "true"
TERRAFORM_GUARDRAIL_WRITE_JUNIT: "true"Optional policy bundle evaluation:
guardrail_scan:
before_script:
- python -m http.server 8081 --directory ops/policy-registry &
variables:
TERRAFORM_GUARDRAIL_POLICY_BUNDLE: "baseline-signed"
TERRAFORM_GUARDRAIL_POLICY_REGISTRY: "http://localhost:8081"The template emits JSON, SARIF, and JUnit report artifacts by default. Disable any of them with
TERRAFORM_GUARDRAIL_WRITE_REPORT, TERRAFORM_GUARDRAIL_WRITE_SARIF, or
TERRAFORM_GUARDRAIL_WRITE_JUNIT.
Use the pipeline template in /.azure/terraform-guardrail.yml.
trigger:
- main
pool:
vmImage: "ubuntu-latest"
steps:
- template: .azure/terraform-guardrail.yml
parameters:
path: "infra"
failOn: "high"
policyBundle: "baseline-signed"
policyRegistry: "http://localhost:8081"The template publishes JSON, SARIF, and JUnit reports. Disable publishing with
publishReports: false.
The repo also includes a Marketplace extension scaffold in azure-devops-extension/ with a
Terraform Guardrail Scan task. Build it using tfx and publish from your ADO publisher account.
Example pipeline usage after publishing:
steps:
- task: TerraformGuardrail@1
inputs:
path: "infra"
failOn: "high"
policyBundle: "baseline-signed"
policyRegistry: "http://localhost:8081"
jsonReport: "guardrail-report.json"
sarifReport: "guardrail-report.sarif"
junitReport: "guardrail-report.junit.xml"Automation: the Azure DevOps Extension workflow publishes on tag pushes when the following
secrets are set:
ADO_PUBLISHERADO_EXT_PAT
- PyPI: https://pypi.org/project/terraform-guardrail/
- GitHub Releases: https://github.com/Huzefaaa2/terraform-guardrail/releases
- Container Image: https://github.com/Huzefaaa2/terraform-guardrail/pkgs/container/terraform-guardrail
- Latest release: v1.0.5
- Release history:
RELEASE.md - Enterprise Features: https://github.com/Huzefaaa2/terraform-guardrail/wiki/Enterprise-Features
Terraform-Guardrail is released under the Business Source License (BSL) 1.1.
✅ Free to use for:
- Internal enterprise platforms
- CI/CD pipelines
- Evaluation, learning, and experimentation
- Open-source contributions
❌ Not allowed without permission:
- Offering Terraform-Guardrail as a paid product or SaaS
- Embedding it into commercial platforms or services
- Reselling or monetizing the software directly
Commercial use requires explicit written permission from the author.
If you wish to:
- Offer Terraform-Guardrail as a managed service
- Embed it into a commercial platform
- Distribute it as part of a paid product
Please contact the author to discuss licensing options.
Q: Can I use Terraform-Guardrail inside my company?
Yes. Internal use and CI/CD validation are allowed without permission.
Q: Can I offer it as a paid SaaS or managed service?
No. Paid or monetized use requires explicit written permission.
Q: When does it become Apache 2.0?
On the Change Date defined in the LICENSE (4 years from first public release).
See LICENSE and COMMERCIAL_USAGE.md for full terms.
See docs/streamlit_cloud.md for a detailed Streamlit Cloud walkthrough.
- Update version in
pyproject.toml. - Update
RELEASE_NOTES.mdandCHANGELOG.md. - Commit changes and push to
main. - Create and push a tag:
git tag -a vX.Y.Z -m "vX.Y.Z"thengit push origin vX.Y.Z. - Confirm GitHub Actions release workflow completed successfully.
This repo uses git-cliff to generate CHANGELOG.md.
git cliff -o CHANGELOG.mdOr run:
make changelogmake release-dry VERSION=1.0.5
make version-bump VERSION=1.0.5scan_terraform: Run compliance checks over a path and optional state file.get_provider_metadata: Fetch provider metadata from Terraform Registry.generate_snippet: Generate Terraform snippets for common resources.
Business Source License (BSL) 1.1. See LICENSE.