Infrastructure as Code: the MVP decision that outlasts your MVP

The conversations that surround a new product build tend to focus on the visible parts: which features ship in version one, what the design system looks like, how quickly the first users can be in front of it. These are the right things to discuss, and founders are equipped to discuss them. The decisions that get less attention sit underneath: how the cloud environment is set up, how new versions get deployed, how a second engineer hired six months from nowwill be able to work on the product without breaking it. These choices are usually made early, often in the first few weeks of a build, and they tend to stay in place far longer than anyone expects.

The discipline that governs this layer is called Infrastructure as Code, or IaC. It is not a flashy topic, and it rarely comes up in early product conversations. But the decision to use it, or to skip it, shapes the cost, flexibility, and resilience of a product for years. This article is about why that is, and what good looks like.

What Infrastructure as Code actually is

Stripped of jargon, Infrastructure as Code is the practice of writing down the cloud setup in files that live alongside the application code, instead of configuring it by hand through a web console.

A small example makes the difference clear. Without IaC, setting up a new environment looks like an engineer opening the cloud provider's dashboard, clicking through several dozen screens, and configuring servers, databases, permissions, and networking one by one. The setup works, but it exists only in the live environment. There is no record of what was done, in what order, or why.

With IaC, the same setup is described in a file. The file specifies, in plain terms, what the environment should contain. Running the file creates the environment. Running it again creates an identical copy. Editing the file and re-running it updates the environment to match the new specification.

The difference sounds modest. In practice it changes almost everything about how a product is built and maintained.

It means a new environment can be created in minutes, not days. It means staging and production stay in sync, because both are produced from the same source. It means infrastructure changes go through code review, the same way feature changes do. It means a new engineer can read the file and understand the setup, instead of relying on whoever happened to build it.

Most modern engineering teams treat IaC as a baseline. The teams that skip it usually do so because the first build felt too small to bother, and by the time it feels big enough, the cost of going back has grown.

Why infrastructure decisions outlast the MVP itself

The premise of an MVP is that it is temporary. The features will change. The design will be reworked. Some of the code written in the first three months will be deleted in the next six. Founders internalise this, and rightly so.

Infrastructure does not work the same way. The way the cloud environment is structured during the initial build tends to persist, because rebuilding it later is expensive and risky in a way that rewriting application code is not. A poorly named database, a permissions structure that conflates staging and production, a deployment process that only one person understands: these things calcify. They become the foundation that every later decision is built on top of.

Three years into a product's life, it is common to find that the architectural decisions made in the first month are still in place, even after most of the original code has been replaced. The reason is straightforward. Replacing a feature affects users for a few hours. Replacing the way infrastructure is managed affects the entire team for weeks, requires careful migration of live data, and carries real risk of downtime. Most teams defer this work indefinitely, which means the early choices keep paying interest.

For a founder, this has a practical implication. The Infrastructure as Code setup chosen for an MVP is, in effect, a long-term decision dressed up as a short-term one. It deserves at least as much scrutiny as feature scoping, even though it rarely gets it.

The hidden costs of skipping Infrastructure as Code

The visible cost of poor infrastructure is the cloud bill, and that one tends to get attention. The less visible costs are larger and harder to reverse.

Environment drift

When the production setup exists only as a series of manual configurations made through the cloud provider's web console, no other environment will ever quite match it. The staging environment behaves slightly differently. The development environment behaves more differently still. Bugs that appear in production cannot be reproduced anywhere else, which means they get fixed by guesswork. Over time, the team learns to distrust its own testing, and this distrust silently slows every release.

Cloud bills that scale faster than the product

Cloud pricing rewards thoughtful architecture and punishes the absence of it. A product built on always-on servers will cost roughly the same whether it has one user or one thousand. A product built on serverless components will cost almost nothing at low traffic and scale up in proportion to actual use. The difference between the two approaches, on a small product, can be the difference between a few hundred dollars a month and a few thousand. On a growing product, it can be the difference between viable unit economics and a runway problem.

Knowledge trapped in one person's head

When the infrastructure has not been written down anywhere, it lives in the memory of whoever set it up. If that person leaves, takes a holiday, or simply forgets, the team loses the ability to make changes safely. This is one of the most common reasons that small engineering teams hit a wall when they try to grow from two engineers to five.

Migration costs when the team grows

A serious in-house engineering team, hired a year into the product's life, will expect a certain baseline. Version-controlled infrastructure. Reproducible environments. A clear deployment process. If those things are not in place, the first three months of the new team's time will be spent retrofitting them, while the founder waits for new features that never quite ship.

None of these costs are visible during the first build. All of them are determined by it.

How Thinslices approaches Infrastructure as Code

When we build an MVP, the cloud environment is treated as a first-class part of the product, not an afterthought. Every environment we create is defined in code from day one, lives in the same version control as the application, and goes through the same review process as any other change.

For most of the products we ship, that work is done on AWS, using two specific tools: AWS Cloud Development Kit (CDK) and SST. CDK lets engineers describe cloud resources in familiar programming languages rather than in lengthy CloudFormation configuration files, which makes the infrastructure easier to read, easier to review, and significantly less prone to error. SST builds on top of CDK with a focus on serverless products, which suits the cost profile of an early-stage MVP particularly well: a product with low traffic costs almost nothing to run, and the cost grows in proportion to real use.

These tools are not the only sensible choices, and we are not religious about them. Terraform, Pulumi, and others are reasonable alternatives, and there are projects where one of them would be a better fit. The point is not the specific tool. The point is that the choice is made deliberately, documented, and consistent across the project.

What this means in practice for the founders we work with is straightforward. A new environment can be spun up in an afternoon, not a week. The cost of running the product at low traffic stays low. When the time comes to bring engineering in-house, the new team inherits something they can read, change, and extend without having to start over. This last point matters more than it tends to sound. Teams that operate on a build-measure-learn cadence depend on being able to ship changes quickly and confidently, and infrastructure that resists change quietly drains that cadence away.

What a healthy Infrastructure as Code setup looks like

For founders without a deep technical background, it is hard to inspect infrastructure directly. But the absence of good IaC tends to leave traces that are visible from a distance.

A healthy setup produces consistent answers. Asked how long it would take to create a new environment for a demo or a pilot, the team answers in hours. Asked who can deploy a change to production, the team can name several people, not one. Asked where the infrastructure is documented, the team points to a folder in the repository, not to a person.

A healthy setup also produces predictable costs. The monthly cloud bill follows a curve that tracks user growth, not a curve that grows independently of it. Costs do not spike unexpectedly when traffic is flat, and they do not balloon when traffic doubles.

And a healthy setup produces a clean handoff. When the product is mature enough to bring engineering in-house, or when responsibilities shift between teams, the infrastructure does not need to be explained verbally. The new team reads the code, runs it, and continues.

None of this is exotic. It is the baseline that any modern engineering team should expect, and the baseline that founders should expect from anyone building on their behalf.

A quiet decision with a long tail

Most of the decisions made during an MVP build can be reversed cheaply. Infrastructure decisions are the exception. They are made early, made quietly, and made by people the founder rarely interacts with directly. And they keep shaping the product long after the original team has moved on to other things.

Treating Infrastructure as Code as a baseline rather than a luxury is one of the simplest ways to make sure that those long-tail decisions work in your favour rather than against you. It does not require a deep understanding of the tools. It requires only the recognition that the choice is being made, and the expectation that it will be made well.