TerraVision
Turn Terraform or JSON files into professional cloud architecture diagrams with the official AWS, Azure and GCP icons
Watch a 4-Minute Intro
What is TerraVision?
TerraVision automatically converts your Terraform code, or a plain JSON graph of Terraform resource names, into professional-grade cloud architecture diagrams using the official AWS, GCP, and Azure icon sets. Your diagrams stay in sync with your infrastructure — no more outdated Visio, draw.io or Lucidchart files.
Most diagram tools that AI assistants reach for (Mermaid, PlantUML, hand-drawn SVG) produce boxes and arrows. TerraVision produces the diagram a cloud architect would draw: real provider icons, VPCs and subnets nested correctly, resource groups, regions and zones. It runs entirely on your machine, needs no cloud credentials, and outputs PNG, SVG, PDF or an editable draw.io file.
Why TerraVision?
- ✅ JSON graph input — describe an architecture in a few lines of JSON and render it, resources match Terraform names so no need to learn a custom DSL (Graph Format)
- ✅ Always up-to-date — diagrams generated directly from your Terraform code
- ✅ 100% client-side — no cloud access required, runs locally, your code never leaves your machine
- ✅ CI/CD ready — automate diagram updates on every PR merge
- ✅ Free & open source — no expensive diagramming tool licenses
- ✅ Multi-cloud — AWS (full), GCP, and Azure (core services)
- ✅ Interactive HTML output — clickable nodes, pan/zoom, search, animated data flow
- ✅ Editable draw.io export — open in draw.io, Lucidchart, or any mxGraph editor
- ✅ Optional AI annotations — labels, titles, and flow sequences from Ollama (local) or AWS Bedrock
- ✅ Terragrunt compatible — auto-detects single- and multi-module Terragrunt projects
- ✅ MCP server and agent skill — let AI agents generate diagrams from a JSON graph or your Terraform, see the guide
Supported Cloud Providers
| Provider | Status | Resource types |
|---|---|---|
| AWS | ✅ Full support | 385 types |
| Google Cloud | ✅ Full support | 264 types |
| Azure | ✅ Full support | 245 types |
Full list: Node types.
Quick Start
Install
pipx install terravision # or: pip install terravision if in a virtual env
You also need Python 3.10+, Graphviz and Git, plus Terraform 1.x (or OpenTofu) when drawing from Terraform code; JSON graphs don't need it. See the Installation Guide for platform-specific instructions, Docker, and Nix.
Option 1 - Diagram from JSON (no Terraform needed)
Describe the architecture as nodes and connections. AWS is shown here; expand the Azure and GCP examples below.
{
"tv_aws_users.users": ["aws_cloudfront_distribution.cdn"],
"aws_cloudfront_distribution.cdn": ["aws_s3_bucket.static_site", "aws_alb.api"],
"aws_vpc.main": ["aws_subnet.public~1", "aws_subnet.private~1"],
"aws_subnet.public~1": ["aws_alb.api"],
"aws_subnet.private~1": ["aws_lambda_function.orders"],
"aws_alb.api": ["aws_lambda_function.orders"],
"aws_lambda_function.orders": ["aws_dynamodb_table.orders", "aws_sqs_queue.events"]
}
Azure example
{
"tv_azurerm_users.users": ["azurerm_cdn_frontdoor_profile.edge"],
"azurerm_cdn_frontdoor_profile.edge": ["azurerm_linux_web_app.api"],
"azurerm_resource_group.app": ["azurerm_virtual_network.main", "azurerm_mssql_database.orders", "azurerm_servicebus_queue.events", "azurerm_key_vault.secrets"],
"azurerm_virtual_network.main": ["azurerm_subnet.app"],
"azurerm_subnet.app": ["azurerm_linux_web_app.api"],
"azurerm_linux_web_app.api": ["azurerm_mssql_database.orders", "azurerm_servicebus_queue.events", "azurerm_key_vault.secrets"]
}
GCP example
{
"tv_gcp_users_icon.users": ["google_compute_global_forwarding_rule.lb"],
"google_compute_global_forwarding_rule.lb": ["google_cloud_run_v2_service.api"],
"google_cloud_run_v2_service.api": ["google_sql_database_instance.orders", "google_pubsub_topic.events", "google_storage_bucket.assets"],
"google_pubsub_topic.events": ["google_cloudfunctions2_function.worker"]
}
Render it:
terravision draw --source architecture.tvg.json --format svg
Each key is <terraform_resource_type>.<name>; each value is what it connects to or contains. That is the whole format. Full spec, schema and more examples: Graph Format. Works for AWS (aws_*), Azure (azurerm_*) and GCP (google_*).
Using an AI assistant? Install the TerraVision skill (Claude Code, Codex, Gemini CLI, Cursor, Copilot) or the MCP server; the render_graph tool takes this JSON directly. For agents reading docs, llms.txt is a plain-text index of the docs, and llms-full.txt adds the full node-type reference.
Option 2 - Generate your diagram from Terraform
git clone https://github.com/patrickchugh/terravision.git
cd terravision
# EKS cluster example
terravision draw --source tests/fixtures/aws_terraform/eks_automode --show
# Azure VM scale set
terravision draw --source tests/fixtures/azure_terraform/test_vm_vmss --show
# From a public Git repo (note the // for subfolder)
terravision draw --source https://github.com/patrickchugh/terraform-examples.git//aws/wordpress_fargate --show
That's it — your diagram is saved as architecture-aws.dot.png (the provider is appended to the name) and opens automatically.
The diagram is derived from terraform plan, so it shows what the code actually deploys: conditionals, count, for_each and modules are resolved. Eraser and friends draw what the AI imagines; TerraVision proves what the code deploys.
Generate an interactive HTML diagram
terravision visualise --source ./path-to-your-terraform --show
Click any resource to see its Terraform metadata, search resources, pan/zoom, and watch animated data flow on edges. The HTML is a single self-contained file that works fully offline.
Try the Interactive Demos
Click any of these to see the interactive HTML output TerraVision produces:
- 🟧 AWS demo — Wordpress on ECS Fargate with CloudFront, RDS, EFS
- 🟦 Azure demo — VM scale set with load balancer and VNet
- 🟩 GCP demo — Core GCP networking and compute
Basic Usage
Generate a diagram
# From a local directory
terravision draw --source ./path-to-your-terraform
# From a Git repository
terravision draw --source https://github.com/user/repo.git
# Custom format and filename
terravision draw --source ./path-to-your-terraform --format svg --outfile my-architecture
# Editable draw.io file
terravision draw --source ./path-to-your-terraform --format drawio --outfile my-architecture
Use a pre-generated Terraform plan (no cloud credentials needed)
# Step 1: in your Terraform environment
terraform plan -out=tfplan.bin
terraform show -json tfplan.bin > plan.json
terraform graph > graph.dot
# Step 2: diagram generation, no Terraform or cloud access required
terravision draw --planfile plan.json --graphfile graph.dot --source ./path-to-your-terraform
AI-powered annotations (optional)
terravision draw --source ./path-to-your-terraform --ai-annotate ollama # local LLM (no data leaves your machine)
terravision draw --source ./path-to-your-terraform --ai-annotate bedrock # AWS Bedrock via boto3 (uses your AWS credentials)
terravision draw --source ./path-to-your-terraform --ai-annotate restapi # any OpenAI-compatible endpoint (OpenAI, LiteLLM, vLLM, ...)
Only metadata and the summary graph are sent to the LLM — never your .tf source. The bedrock backend authenticates via the standard AWS credential chain (no infrastructure to deploy); restapi is configured via TV_RESTAPI_URL, TV_RESTAPI_KEY, and TV_RESTAPI_MODEL. See the Annotations Guide and AI-Powered Annotations for the full configuration.
Simplified view
terravision draw --source ./path-to-your-terraform --simplified
Strips VPCs, subnets, and networking plumbing. Great for executive presentations.
Common options
terravision --help shows full help text details.
| Option | Description | Example |
|---|---|---|
--source |
Terraform directory or Git URL | ./path-to-your-terraform |
--format |
Output format: png, svg, pdf, drawio, and more |
svg |
--outfile |
Output filename | my-architecture |
--workspace |
Terraform workspace | production |
--varfile |
Variable file (repeatable) | prod.tfvars |
--planfile |
Pre-generated plan JSON | plan.json |
--graphfile |
Pre-generated graph DOT | graph.dot |
--ai-annotate |
AI annotation backend | ollama, bedrock, restapi |
--simplified |
High-level view (no networking) | (flag) |
--show |
Open after generation | (flag) |
Documentation
The complete documentation lives at patrickchugh.github.io/terravision.
For users:
- Installation Guide
- Usage Guide
- Annotations Guide
- CI/CD Integration
- MCP Server Guide
- llms.txt (docs index for AI agents)
- FAQ
- Troubleshooting
For contributors:
FAQ
Common questions — cloud credentials, LLM data privacy, offline use, Terragrunt, output formats, and more — are answered in the FAQ on the documentation site.
Contributing
Contributions are very welcome. See CONTRIBUTING.md for development setup, coding standards, and the PR process.
Support
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Documentation: patrickchugh.github.io/terravision
License
See LICENSE.
Acknowledgments
- Graphviz — diagram rendering
- Terraform — infrastructure parsing
- Terragrunt — multi-module orchestration
- Cloud provider icons from official AWS, GCP, and Azure icon sets
Release files for terravision 0.48.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| terravision-0.48.0.tar.gz | 21.3 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| terravision-0.48.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 43.4 MB
Release files / terravision-0.48.0.tar.gz
| Download URL | terravision-0.48.0.tar.gz |
|---|---|
| Size | 21.3 MB |
| Tags | Source |
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| Tags | Python 3 |
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| Uploaded via |
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
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