Introduction

I’ve spent enough time around early-stage startups to notice a repeat pattern: teams reach for heavyweight infrastructure long before they have the demand or complexity to justify it. The instinct is understandable. Everyone wants to be ready for the day growth shows up all at once.

But infrastructure is not a trophy. It is a tool in service of the business. The goal early on is not to build something that looks like a scaled company. The goal is to build something that reliably supports the product you are shipping today, with a clear path to evolve as real usage and real constraints emerge.

Yes, you should plan for growth. You should make choices that do not paint you into a corner. Still, the best "scalability strategy" for most startups is to stay honest about current needs, measure what is actually happening, and upgrade only when the evidence says it is time.

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The Question That Comes Before Technology

A lot of times, especially with first-time founders, I've noticed a strange pattern. People tend to build their infrastructure based on their past experience. For example, they will build an analytics stack based on how they used to operate at a tech giant, rather than what their startup actually needs today.

The problem with this is that people often overestimate their systems' complexity and scalability. Your infrastructure's north star should be your business.

For example, something doesn't sit well with many founders often is the idea that you can't rely on free-tier offerings once you reach $1,000+ in MRR. The very idea of equating revenue with scalability is absurd. The only reliable way to understand your system's load is through observability.

Start with Non-Functional Requirements (NFRs)

As a technical founder, one of the most important questions you need to answer from the start is:

What scale do I expect once my business reaches each milestone?

Writing down a basic set of non-functional requirements (NFRs) helps a lot.

For a beta release, for example, you can define expectations around:

• Traffic
• API latency
• Page load times
• Uptime
• Storage growth

Every business is different, so your beta release requirements could differ vastly from someone else's, and that's completely fine. As long as you have a clear understanding of your requirements, you're in a good place.

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You Can't Optimize What You Can't Measure

I don't know if you're a gamer, but there are always skills or tools that experienced players recommend unlocking early in the game because they pay off tremendously in the long run (think the Mikiri Counter in Sekiro). Observability is one of those investments. It's something you should prioritize right from the start.

Apart from the fact that dashboards are really fun to look at, seeing how your infrastructure behaves with fine granularity gives you the ability to answer questions like:

• Should I opt for a bigger instance?
• Am I just fine with a t3.micro EC2 instance?

Observability gives you evidence instead of assumptions.

It's also incredibly useful when discussing technical decisions with non-technical co-founders. Concepts like vertical scaling, horizontal scaling, cache hit rates, or database bottlenecks can be difficult to communicate in the abstract. A few well-designed dashboards make those conversations far more intuitive.

Trust me, everyone loves to see graphs in a presentation!

Observability and Unit Economics

Observability also helps you understand the unit economics of your tech stack.

As I wrote in the beginning, every technical decision should ultimately tie back to your business.

One area where telemetry is especially valuable is serverless workflows. Metrics can tell you:

• How often a function is invoked
• How long it runs
• What each execution costs

While lightweight events may contribute very little to your bill, more expensive workloads such as AI inference, image or video processing, PDF generation, data imports, or long-running background jobs should be tracked closely.

Once you know the cost of each event, you can make informed decisions about optimization, pricing, and whether a particular workflow should remain serverless or move to dedicated infrastructure.

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Rent Your Infrastructure

When you start out, it's extremely important to save as much money as possible.

One way to do that is by outsourcing parts of your infrastructure to available services.

During the MVP and beta stages, your objective is to validate the business, not optimize infrastructure costs or build every piece of the stack yourself.

This is a two-parter, actually:

1. Technical services you can outsource.
2. Startup offers you should take advantage of.

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Part 1: Outsource What Isn't Your Core Business

Let's talk about the components in your infrastructure you can outsource.

The table below has a list of few stacks you don't have to own (and probably never will for a few of them).

Especially with AI inference: a lot of people are tempted to host GPU servers, but a lot of times that's not needed.

A provider like fal can be perfectly suitable for AI inference tasks. They provide APIs for almost all inference tasks, and they support multiple providers as well (Qwen, Seedance, Gemini, etc.).

Don't buy GPUs just because you're building an AI product.

Managed inference providers like fal let you ship faster, avoid idle infrastructure, and only pay for what you use. Revisit the decision only when the economics or technical requirements clearly justify owning GPU infrastructure.

These services also help you validate your use cases as you enter the market. In other words, they can reveal whether you need a custom solution for a given feature set or whether existing tools are sufficient.

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Part 2: Take Advantage of Startup Offers

The second thing that you can (and should) do is get startup offers!

Almost all providers these days have startup offers that you can avail of.

For example, if you're part of the AWS Activate program, you can get startup offers for a lot of services.

Check this out: Activate Offers | AWS Startups — licenses that are free for up to a year, which will easily cover your MVP and beta rollouts.

You can (and should) opt for business plans for tools like Notion, Atlassian, ClickUp, Zoho, etc. for your productivity needs, since many of them offer startup deals.

The only caveat is that these offers lock you into a plan, and once they end, you're back to being a paid subscriber. This can be a major hurdle if you're still entering the market and don't yet have the financial resources to afford these tools.

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Design for Migration

One important thing to note about renting your tech stack: you should always be ready for a migration.

This is a separate topic I'll cover in another blog.

In short: keep things modular.

Design patterns aren't just fancy computer science theory you read for interview prep. The more you incorporate them into your code, the smoother and more efficient migrations become.

More on this in another blog.

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Conclusion

If there's one thing I've learned from working with early-stage startups, it's that good infrastructure isn't about having the most sophisticated architecture. It's about making decisions that fit where your business is today while leaving yourself room to grow tomorrow.

Start with clear non-functional requirements. Measure everything that matters. Let observability tell you when it's actually time to scale instead of relying on instinct or copying what larger companies are doing. And whenever you can, rent the parts of the stack that don't differentiate your product so you can spend more time building the things your customers actually care about.

As your product grows, your infrastructure will grow with it. Some managed services will eventually become too expensive. Some workloads will deserve dedicated infrastructure. Some architectural decisions you'll make today will need to be revisited. That's normal. Infrastructure isn't something you build once, it's something that evolves alongside your business.

For an MVP or even a beta release, your biggest constraint usually isn't compute, storage, or network bandwidth. It's time, focus, and runway. Spend those wisely, and let your infrastructure earn the right to become more complicated.