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Terraform Cost Estimator

Rough monthly cost estimate from your Terraform (.tf) resource types.

Runs entirely in your browser - nothing is uploaded and no cloud connection is made. Rates are rough placeholders.
$0
est. $/mo
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Your cost estimate will appear here.

About Terraform Cost Estimator

The Terraform Cost Estimator gives you a rough monthly cost estimate from your Terraform configuration without leaving the browser. It counts resources by type from the .tf you paste, multiplies each type by a fixed placeholder monthly rate, and produces a Markdown table plus a summed total. The goal is a privacy-first, order-of-magnitude sense of spend before you run a real plan, so you can catch obviously expensive shapes early.

Everything is computed locally. The estimator parses your HCL with a bundled parser, tallies resource blocks, and never contacts a cloud account or a pricing API, so secrets, instance sizes and topology stay on your machine. It is a deliberately simple approximation, not a billing system.

Because the rates are illustrative placeholders, treat the number as a conversation starter rather than an invoice. Pair it with a proper tool such as Infracost when you need accurate, usage-aware pricing. The estimator still earns its place for quick comparisons, teaching, and sanity checks during design reviews. For a production-grade number, export the JSON and feed it into a dedicated pricing pipeline, but the in-browser estimate is enough to flag a forgotten large instance before it is applied.

The estimator is also a good teaching tool. New engineers can paste a module and immediately see which resource types dominate the bill, reinforcing the habit of checking cost during design rather than after deployment. Because it runs offline, it works in locked-down environments where external pricing services are blocked, and it can be demonstrated in a workshop without network access.

Keep in mind the model is intentionally flat: it does not account for instance families, regions, reserved capacity, data transfer or storage growth. A fixed instance rate stands in for a small box and should not be read as a bill. The value is in relative comparison and early warning, not precision.

Features

  • Per-type counts - tallies each resource type in your .tf.
  • Placeholder rates - rough monthly $ per type, easy to scan.
  • Live stats - estimated total and resource count.
  • Total - a summed monthly estimate across all types.
  • Markdown table - easy to copy or export.
  • Usage-aware zeros - Lambda, ECS and similar show $0 with a note.
  • Provider coverage - AWS, Azure and GCP common types included.
  • Unknown types - unlisted resources fall back to a small default rate.
  • JSON export - copy a machine-readable breakdown.
  • Local parsing - HCL parsed in the browser, nothing sent.
  • Flat model - one rate per type, easy to understand.
  • Export friendly - JSON slots into a downstream pricing step.
  • Private - no cloud or pricing API.
  • Copy / Download / Print - take the estimate anywhere.

How to Use

  1. Paste your .tf into the text area, or load the sample.
  2. Click Estimate to parse the configuration and build the table.
  3. Review the rows - one line per resource type with count, unit rate and subtotal.
  4. Read the total in the stats row at the top of the output.
  5. Copy, copy as JSON or download the Markdown estimate.
  6. Print a clean copy for a design review.
  7. Compare providers by pasting equivalent resources side by side.
  8. Share the JSON with teammates for a quick cost chat.
  9. Flag surprises - note any unexpectedly large subtotal and revisit sizing.
  10. Adjust and re-estimate as you change the configuration.

Examples

Example - pasting 2 aws_instance plus 1 aws_db_instance yields rows for each type and a summed monthly estimate (2 times the instance rate plus the database rate).

Example - adding an aws_lambda_function contributes a row with a $0 subtotal because its cost depends on invocation volume, not a fixed rate.

Example - a configuration with only outputs and no resource blocks reports that no resources were found so you know to paste the right file.

Example - an aws_eks_node_group row uses a per-node-group placeholder rate so a cluster estimate scales with node groups you declare.

Example - azurerm_virtual_machine and google_compute_instance rows show cross-cloud rates so you can compare providers in one table.

Example - a single aws_cloudfront_distribution contributes a placeholder rate even though real cost depends on requests and bytes served, reminding you to review usage-based services separately.

Benefits

  • Fast - an instant estimate while you design.
  • No secrets sent - parsing stays in the browser.
  • Clear - a readable Markdown table.
  • Comparable - re-estimate after edits to see the delta.
  • Teaching aid - shows how resource types drive cost.
  • Offline friendly - works without network or pricing API.
  • Visible drivers - see which types dominate spend.
  • Cheap to run - no paid service required for a rough number.
  • Honest scope - clearly a rough estimate, not a bill.
  • Portable - copy, download, print or export JSON.

Frequently Asked Questions

How does the estimate work?
It counts each resource type in your .tf and multiplies by a fixed placeholder monthly rate. The total is a rough order-of-magnitude estimate.
Is the pricing accurate?
No. The rates are illustrative placeholders. Replace them with current cloud pricing or use Infracost for accurate numbers.
Does it connect to a cloud or pricing API?
No. Everything is computed locally - nothing is uploaded and no pricing API is called.
What about usage-based resources?
Lambda, ECS and similar are estimated at $0 because cost depends on usage; the table notes this.
Can I export the table?
Yes. Copy, download as .md, or print.