Tool Alternatives

Terraform Rover alternative: past localhost:9000, toward a diagram you can send someone

By the engineer who builds Datadef, from client work on data platforms · Reviewed August 21, 2026

Rover is the nicest way to look at a Terraform plan. It builds a plan, parses the configuration, and serves an interactive view on localhost with a resource overview, a resource map, and a dependency graph, including modules, counts, outputs, and locals. It is a genuinely good debugging instrument. It is also, by design, a thing that lives on your machine for as long as the terminal is open.

Try it free
6 min readFor engineers using Rover to review plans who also need a diagram for other people

See it as a diagram

Everything below, as a diagram you can edit. Describe yours and see it in seconds.

163/2000• 3 credits left
Try:

No account needed · Editable canvas, not a picture

What Rover is good at

The plan is the point. Rover generates a plan file or takes a pre-generated plan JSON, then renders what a run will do alongside the structure it will act on. For reviewing a change before applying it, that is exactly the right frame, and the interactive UI beats reading plan output in a terminal.

The details are well judged: modules, count usage, outputs, and locals are all visible rather than flattened away, a Docker image saves the local setup, backend config and variable files can be passed in with flags, -standalone true packages the static assets into a rover.zip, and -genImage true writes an SVG when what you need is a file rather than a server on port 9000.

It is actively maintained and free, and for the job it was built for there is not much competition.

Three limits that matter for documentation

Generating a plan is not free. It means a Terraform binary, an initialized working directory, backend access, variable files, and often credentials in the environment, which is a heavier requirement than reading source and one many repositories cannot satisfy from a laptop or a shared runner. Passing a pre-generated plan with -planJSONPath does not remove the requirement, it moves it to whoever produced the plan, and a plan JSON is a sensitive artifact in its own right.

The output is local. A web app on localhost is for the person who ran it. Sharing means the standalone zip or an exported image, which puts you back in the business of regenerating and re-sending artifacts every time infrastructure changes.

And the shape is plan-shaped. A dependency graph answers what depends on what, which is a debugging question. The architecture question, what does this platform consist of and how does it fit together, wants module boundaries, curated importance, and provider icons rather than a complete edge set.

The source parse, hosted and scheduled

Datadef parses the .tf and .tfvars files of a connected repository directly. No init, no plan, no state, no cloud credentials, just a read-only token on GitHub, GitLab, or Azure DevOps and a branch or tag. That is what makes it usable against a production repository or a client repository you can only read.

The drawing is curated before it is rendered, and the curation is deterministic rather than a matter of taste. Modules become zones, no zone holds more than eight nodes, major resources keep their provider icons, and a repeated minor type inside a module rolls up into one node carrying the count and the member names, as in Storage credentials ×2: external, root. Anything left over folds into a single Supporting resources node with its count. The platform repository this was tuned against holds 123 declared resources and reads at around 36 nodes, with the full inventory kept in a generated module reference table.

What never becomes a box is as deliberate. Role assignments, IAM policies, grants, permissions, secrets, diagnostic settings, and every resource from the random, null, tls, and time providers are classified as wiring and counted in a note instead. Node ids come from the Terraform address rather than from the model, so azurerm_storage_account.lake inside module.data is the same node tomorrow that it was today, and a node someone dragged is put back where they left it: the sync records the layout it wrote, and anything more than 12 pixels away from that counts as hand-placed.

Then it stays current on its own: a daily sync, on-demand refresh, and MCP tools so a coding agent can trigger a re-sync after a change merges. The diagram embeds in a README or wiki as a live image, which is the part a localhost UI cannot do. More on the pipeline in visualize a Terraform repository.

Use both, for different questions

Keep Rover for plan review. Before an apply, seeing what will change and how it connects to what exists is a debugging need with a local answer, and Datadef does not do plan diffs.

Use a synced diagram for the questions that outlive the terminal session: onboarding, incident response, security review, and the architecture page someone opens six months from now expecting it to be true.

FAQ

Does Datadef run terraform plan?

No. It parses the .tf and .tfvars source files of the connected repository directly. There is no init, no plan, no state access, and no cloud credentials, so it works on a repository you can only read, which is the common case on a client engagement or a production account you have no role in.

Can it show what a change will do, like a plan visualization?

No. It draws the architecture the code declares on a given branch or tag, not the diff a run would apply. Plan review is a different job with a local answer, and a plan visualizer is the right tool for it. A useful split is Rover before an apply, a synced diagram for everything that outlives the terminal session.

How is the result shared with people who do not run Terraform?

Through a hosted canvas and a live embed image that renders the current diagram in a README, wiki, or doc. Viewers need no account and no toolchain, and the embed follows every sync, so the picture in the wiki is the picture from the last time the infrastructure changed rather than from the last time somebody exported one.

Are modules, counts, and for_each handled?

Yes. Modules render as zones, and count and for_each become a real number: a literal map or list is counted directly, and a for_each driven by a variable is resolved through the per-environment tfvars. A resource created once per environment is drawn once and annotated with the counts, rather than duplicated across the canvas.

Does the diagram get reshuffled every time it regenerates?

No. Node ids derive from Terraform addresses, so a re-sync updates the existing picture instead of relaying it, and the previous ids, labels, and zones are handed back to the generator with instructions to reuse everything that still exists. Nodes moved by hand are put back where they were left, and a commit with no structural change regenerates nothing at all.