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Comparison

InfraSync vs Brainboard

One starts from a diagram and emits code. The other starts from a running account and emits code. They travel in opposite directions.

By Linxus Infotech Updated Sep 9, 2026 7 min read
  • Opposite directions of travel
  • What makes the reverse direction hard
  • Where Brainboard is the better choice
  • Where InfraSync is
  • The sequence that uses both
  • Frequently asked questions

Brainboard and InfraSync both end with Terraform, which is why they show up in the same searches. They start from opposite ends. Brainboard starts from a blank canvas and turns a design into code. InfraSync starts from an account full of resources somebody created three years ago and turns reality into code.

If you know which of those you are doing, the choice is already made.

Opposite directions of travel

Brainboard is a visual, collaborative architecture designer. You draw the architecture on a canvas, it generates Terraform as you go, and the diagram and the code stay in sync. For designing new infrastructure, particularly with people who think visually or need a diagram as an actual deliverable, that is a genuinely nice way to work. They also publish a library of reference architectures worth browsing regardless of tooling.

InfraSync reads a live AWS account through a read-only role and generates Terraform for what is actually there, across 89 services and every region you scan. There is no canvas. The input is the account.

What makes the reverse direction hard

Going from a design to code is mostly a translation problem, and it is tractable because the design is already an abstraction. Going from a running account to code is a different kind of problem, and it is worth understanding because it is where generated Terraform usually disappoints people.

Real accounts contain literals. A scan finds subnet IDs, security group IDs and AMI IDs, and writes them as literals because that is what is true. The result is an accurate snapshot and not portable code. Turning it into something you would deploy to a second environment means lifting those into variables and data sources. A diagram-derived generator never has this problem, because a diagram never contained a subnet ID. It also never contained your actual subnet.

Provider output needs correcting. Raw generated HCL does not necessarily pass terraform validate. We run a set of fixes over the output for exactly this reason, and they are specific: quoted depends_on references that are not valid HCL, an invalid constraints block on aws_kms_grant, cross-module ARN references pointing at outputs that were never defined. That work exists because reality is messier than a canvas.

A diagram describes intent, an account describes outcome. The gap between them is drift, and it only exists in the direction InfraSync works in.

Where Brainboard is the better choice

  • You are designing something new. From a blank canvas, a visual designer is a better tool than any scanner, because there is nothing to scan.
  • Diagrams are a deliverable. If architecture reviews, onboarding docs or compliance evidence need a picture, generating it as a by-product of the design beats maintaining it separately.
  • You work across clouds. Brainboard is multi-cloud; InfraSync is AWS-only.
  • Your team thinks visually. A canvas that non-specialists can read is a real collaboration advantage.

Where InfraSync is

  • The infrastructure already exists. This is the common case and it is the whole reason InfraSync exists.
  • You need current-state HCL. What is running, with its real values, rather than what a design says should be running.
  • You need drift detection. Comparing a baseline against the account, including console changes that a plan-based check can miss.
  • You want cost analysis of what is actually deployed. A design cannot tell you that a volume has been unattached for eight months.
  • You want code without learning a canvas. Point at an account, review a pull request.

The sequence that uses both

The honest answer for many teams is both, in order. Use a scanner to codify the legacy estate that nobody documented, so it is finally in version control and under drift detection. Then design net-new infrastructure visually, where a canvas genuinely helps.

The two do not conflict, because they operate on different halves of the estate: the part that already exists and the part you are about to build.

Frequently asked questions

Is InfraSync a Brainboard alternative?

Only for the reverse direction. Brainboard turns a diagram you draw into Terraform, which is the right tool for designing new infrastructure. InfraSync turns an existing AWS account into Terraform. If your infrastructure already exists, a design canvas has nothing to read.

Can Brainboard import my existing AWS infrastructure?

Brainboard's strength is design-first, generating Terraform from an architecture you draw on a canvas. If your requirement is reverse-engineering a live account that was built by hand years ago, that is the problem InfraSync is built for.

Why does generated Terraform contain hardcoded IDs?

Because a scan writes what it found, and what it found were literal subnet, security group and AMI IDs. That is an accurate snapshot rather than portable code. Anything destined for a second environment needs those lifted into variables or data sources, which is a normal part of the first review.

Does InfraSync produce diagrams?

No. InfraSync produces Terraform, drift reports and cost findings. If a diagram is a deliverable your team needs, a visual designer such as Brainboard is the better fit for that part of the work.

Can I use both tools?

Yes, and many teams should. Codify the existing estate with a scanner so it is in version control and under drift detection, then design new infrastructure visually. They operate on different halves of the estate and do not conflict.

Keep reading

Comparison

InfraSync vs Firefly, ControlMonkey & Brainboard Compared

The full matrix across all five tools in one table.

Read the guide ›

Guide · Terraform

How to Generate Terraform From an Existing AWS Account

What to scan, how to structure modules, and how to reach a clean plan.

Read the guide ›
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