The Problem Nobody Talks About

Picture this: you join a team that runs a dozen microservices across three cloud providers. Nobody has updated the architecture diagram since the original developer left. You are staring at a Confluence page with a PNG that is two years out of date.

This is the normal state of infrastructure documentation for most teams. The tooling to fix it exists, but most developers only know about the AWS-native options. There is a whole world of infrastructure visualization tools that work across providers, and they deserve more attention.

Whether you are on Google Cloud, Azure, a hybrid setup, or running Kubernetes clusters on bare metal, these five tools can help your team actually understand what they built. Let us get into it.

1. Diagrams: Infrastructure as Python Code

Diagrams is an open-source Python library that lets you draw cloud architecture diagrams using code. You define nodes and edges in plain Python, and the library renders a clean architecture diagram automatically.

What makes it stand out is the sheer range of supported providers. It supports AWS, GCP, Azure, Kubernetes, Alibaba Cloud, and even on-premise components. You can mix and match them in a single diagram.

Here is a simple example showing a three-tier web app:

from diagrams import Diagram
from diagrams.aws.compute import EC2
from diagrams.aws.database import RDS
from diagrams.gcp.network import LoadBalancing

with Diagram("Hybrid Web App", show=False):
    lb = LoadBalancing("GCP Load Balancer")
    web = EC2("AWS Web Server")
    db = RDS("AWS RDS")

    lb >> web >> db

That script outputs a .png file you can drop straight into your documentation. Because the diagram lives as code, it sits in your repo alongside your infrastructure config. Pull requests can include diagram updates. Code review becomes architecture review.

Developers who work across stacks find this particularly useful. You are not locked into one provider's tooling, and the diagrams stay accurate because they live in version control. If you end up using these diagrams in docs or web pages, running them through a free image compressor beforehand keeps your page load times healthy.

2. Inframap: Read Your Terraform State and Draw It

Inframap takes a completely different approach. Instead of asking you to write a new diagram, it reads your existing Terraform state file and generates a graph from what is already deployed.

A diagram showing interconnected cloud services across multiple providers with color-coded nodes and arrows

This is genuinely useful for teams that inherit infrastructure. You run one command, and you get a visual representation of what is actually running, not what someone thought was running six months ago.

Key Benefits of Infrastructure Visualization Tools

Supported Providers

100%

Documentation Updates

50%

Code Review Efficiency

75%

Team Understanding Improvement

The basic usage looks like this:

# Generate a graph from a Terraform state file
inframap generate terraform.tfstate | dot -Tpng > infrastructure.png

# Or use HCL directly
inframap generate --hcl ./terraform/ | dot -Tpng > infrastructure.png

Inframap uses Graphviz under the hood to render the final image. The output is not the prettiest diagram you will ever see, but it is accurate. For auditing and onboarding, accuracy beats aesthetics every time.

It supports AWS, GCP, Azure, and several other Terraform providers. The tool filters out noise too, showing you meaningful relationships rather than every single Terraform resource and its twenty dependencies.

When Inframap Shines

Teams doing infrastructure audits love this tool. You can hand a new hire the command above and they can produce a working architecture overview in under five minutes. No manual diagramming required.

It also works well for compliance reviews. When someone asks "what talks to what in production?", you have a reproducible, code-driven answer ready to go.

3. Cloudcraft: Visual-First and Multi-Cloud

Cloudcraft is a browser-based tool that takes the visual-first approach. You can drag and drop components onto a canvas, or let it scan your AWS account and auto-generate a diagram from your live infrastructure.

The interface is polished. Diagrams look like the kind of thing you would actually put in a client presentation or a company wiki. It supports 3D isometric views as well as flat diagrams, which sounds gimmicky but is genuinely easier to read for complex multi-tier setups.

Cloudcraft integrates directly with your cloud account via read-only API access. It scans your running resources and lays them out automatically. You can then edit the layout, add annotations, and export to PNG, SVG, or Cloudformation.

There is a free tier for personal use. Paid plans add team collaboration features, more cloud accounts, and the live sync functionality. For small teams doing regular architecture reviews, it is worth evaluating seriously. Check out the Smashing Magazine community for real-world design and dev tool reviews that cover tools like this in depth.

4. Pluralith: Built for Terraform Plan Output

Most teams run terraform plan before every deployment. The output is a wall of text that is hard to scan, especially when dozens of resources are changing at once. Pluralith solves this by turning that plan output into a visual diff.

Instead of reading through hundreds of lines of terminal output, you see a graph showing exactly which resources are being added, changed, or destroyed. Green means added. Orange means modified. Red means destroyed. Your brain processes it in seconds.

The CLI integration is straightforward:

# Install the Pluralith CLI
brew install pluralith/tap/pluralith

# Run it alongside your Terraform workflow
terraform plan -out=plan.out
pluralith graph --plan-file plan.out

This is a code review superpower. When a pull request includes Terraform changes, you can attach a Pluralith graph as a comment. Reviewers instantly see the infrastructure impact without needing to mentally parse the plan output themselves. For teams practicing GitOps, this fits naturally into CI/CD pipelines.

Pluralith also keeps a history of past graphs, so you can compare how infrastructure evolved over time. That is surprisingly useful for post-incident reviews.

A Note on CI/CD Integration

Pluralith has a GitHub Actions integration that posts the graph directly to your pull request. You configure it once, and every Terraform PR automatically gets a visual infrastructure diff attached. Teams that have set this up report that it meaningfully speeds up review cycles, since reviewers no longer need deep Terraform knowledge to understand what is changing.

5. Mermaid: Lightweight Diagrams Inside Your Docs

Sometimes you do not need a full scanning tool. You just need a quick, accurate diagram that lives inside a Markdown file. Mermaid is a text-based diagramming syntax that renders inside GitHub, GitLab, Notion, and dozens of other tools.

You write a simple text description of your architecture, and the platform renders it as a diagram automatically. No exports, no separate files, no tooling to install.

Top Features of Diagrams Tool

✓

Open Source
Free and community-driven.

✓

Multi-Provider Support
Works with AWS, GCP, Azure, and more.

✓

Code-Based Diagrams
Integrates with infrastructure code.

✓

Pull Request Integration
Easily update diagrams with code changes.

```mermaid
graph TD
    User[User] -->|HTTPS| CDN[CloudFront CDN]
    CDN --> API[API Gateway]
    API --> Lambda[Lambda Function]
    Lambda --> DB[(DynamoDB)]
    Lambda --> Queue[SQS Queue]
    Queue --> Worker[Worker Lambda]
```

GitHub renders that code block as a live diagram right inside the README. No screenshots needed. No outdated PNG files. The diagram updates when the code updates, because they are the same file.

Mermaid supports flowcharts, sequence diagrams, entity relationship diagrams, and Gantt charts. For infrastructure documentation that needs to stay lightweight and version-controlled, it is hard to beat. The MDN Web Docs team uses similar text-based approaches for keeping technical documentation accurate and maintainable.

If you are building a documentation site that includes these diagrams, think about the visual design too. Picking consistent colors for your service nodes makes diagrams much easier to read at a glance. A color palette generator can help you define a coherent set of colors to use across all your architecture diagrams.

How These Tools Compare

Each tool fills a different slot in your workflow. Here is a quick breakdown:

Screenshot of a browser-based cloud architecture diagram tool showing interconnected AWS services in an isometric 3D view

Diagrams (Python): Best for teams that want diagrams in version control, generated from code. Multi-cloud support is excellent.
Inframap: Best for auditing existing Terraform infrastructure. Reads real state, not documentation.
Cloudcraft: Best for polished diagrams and live AWS scanning. Good for client-facing documentation.
Pluralith: Best for Terraform plan review in CI/CD. Turns plan output into visual diffs.
Mermaid: Best for lightweight diagrams inside Markdown files and wikis. Zero tooling overhead.

The right choice depends on your workflow. Are you reviewing Terraform changes in pull requests? Pluralith. Onboarding someone to legacy infrastructure? Inframap. Writing docs that need to stay current? Mermaid.

Many teams end up using two or three of these together. Mermaid for high-level overviews in the wiki, Pluralith for CI/CD review, and Diagrams for detailed service maps that live in the repo.

Getting Started Without Overthinking It

Here is the honest take: most teams spend more time arguing about which diagramming tool to use than they spend actually diagramming. Pick one and start. You can always migrate later.

If your team already uses Terraform, start with Inframap. Run it against your current state file today. You will have a working diagram in under ten minutes, and you will immediately see whether it matches what everyone thinks the infrastructure looks like. Spoiler: it usually does not.

If you are starting fresh or want something that lives in your repo, the Python Diagrams library is a solid default. It has good community support on Stack Overflow and the documentation is clear. You can be productive with it in an afternoon.

Want to go deeper on data visualization concepts that apply to both infrastructure and application monitoring? Plotly's Python documentation covers interactive graph rendering in detail, which is useful if you want to build custom dashboards on top of your infrastructure data. For staying current on the broader developer tooling landscape, The Verge regularly covers infrastructure and cloud tool announcements worth tracking.

One last practical tip: when you export diagrams as images for wikis or slide decks, file sizes add up fast. Running exports through a free image compressor or a free image resizer keeps your documentation site snappy. And if you need to extract brand colors from your company's existing architecture diagrams to keep new ones consistent, a color palette generator will pull the exact hex values from any screenshot in seconds.

The Bottom Line

Infrastructure visualization is not just a nice-to-have. It is the difference between a team that understands what they are deploying and one that is flying blind. The tools above cover every major workflow, from reading live Terraform state to embedding diagrams directly in Markdown.

You do not need to be on AWS to benefit from this kind of tooling. You do not need a dedicated platform team or a budget for enterprise software. Most of these tools are open source or have generous free tiers.

Pick one of the five tools above, apply it to a real piece of your infrastructure this week, and share the result with your team. The conversation that follows will tell you more about gaps in your documentation than any audit ever could. Try Inframap or the Python Diagrams library first, and see what your infrastructure actually looks like.