Platform Engineering: how to stop reinventing the wheel across every technology team

Imagine the following scenario: two engineering teams at the same company, working on different products, simultaneously building the same observability solution. Each one with their own tool choices, alert configurations, and log pipelines. Neither one knows the other exists. By the end of the quarter, both delivered something functional. And both wasted weeks that could have been invested in features customers actually pay for.

This scenario is not the exception. It is the rule in organizations that grew quickly, accumulated teams, and never stopped to think about how software engineering is produced internally. This is precisely where Platform Engineering comes in — not as yet another market buzzword, but as a structural response to a problem that is costly and that most technology leaders still underestimate.

The problem nobody wants to admit

When a technology organization scales, it tends to replicate problems. Every new team that forms needs to solve the same fundamental questions: how do you deploy? How do you configure monitoring? How do you manage secrets and environment variables? How do you ensure compliance with company security policies?

In the absence of a centralized answer, each team improvises. And improvisation in technology carries a compounding cost: in the short term, it creates delays; in the medium term, it creates inconsistency; in the long term, it creates technical debt that paralyzes the organization.

A study by DORA (DevOps Research and Assessment) shows that high-performance organizations deliver code up to 973 times more frequently than low-performance organizations. The difference lies not only in the talent of the people — it lies in the quality of the environment in which they work. Teams that have standardized tools, reliable pipelines, and self-service infrastructure deliver faster because they spend less time fighting against their own organization.

What Platform Engineering actually is

Platform Engineering is the discipline of building and maintaining an internal platform — often called an Internal Developer Platform (IDP) — that abstracts infrastructure complexity and allows product teams to focus on what truly matters: writing code that generates business value.

A platform team does not develop features for the end customer. It develops capabilities for other engineering teams. Think of it as a product team whose internal customer is the company's own developers.

This platform typically covers:

• Infrastructure provisioning — environments created in a self-service manner, with built-in security and cost guardrails
• Standardized CI/CD pipelines — from commit to deploy, with traceability and automated rollback
• Centralized observability — logs, metrics, and traces in a single dashboard, without each team needing to configure from scratch
• Secrets and identity management — transparent integration with solutions such as AWS Secrets Manager or HashiCorp Vault for all teams
• Project templates and scaffolding — new services created from approved standards, already with best practices built in
• Internal service catalog — visibility into what exists, who owns it, and its status, avoiding rework and duplication

The key here is the concept of developer experience: the platform needs to be good enough that teams want to use it, not merely be required to use it. Platforms imposed without genuine adoption are a waste of investment.

Why this is a strategic decision, not just a technical one

It is common for CEOs and CIOs to view Platform Engineering as a matter exclusively for CTOs and architects. This is a mistake that I have seen cost large organizations dearly.

When you have 10 engineering teams and each one reinvents the wheel on infrastructure, you are paying for 10 solutions to the same problem. If each team spends an average of 20% of its time on platform-related issues — and that number is conservative — you are wasting the equivalent of 2 entire teams on overhead alone. In a company with 100 engineers at an average cost of R$15,000 per month, that means R$300,000 per month evaporating into work that never reaches the customer.

Beyond the direct cost, there is the opportunity cost. Every week a team spends configuring infrastructure is a week it did not spend developing the feature that could have generated revenue or retained customers.

In the projects I led at companies such as B3, BTG, and Inter, adopting a structured internal platform reduced the onboarding time for new projects from weeks to hours. This is not a theoretical number — it is the result of eliminating manual steps and replacing them with automated guardrails.

How to build without falling into common traps

Building an internal platform is a product project, not an infrastructure project. This distinction changes everything about the approach.

The most common trap is assembling a technology-driven platform team — people who love tools and want to implement everything in the CNCF (Cloud Native Computing Foundation) ecosystem. The result is a technically impressive platform that nobody uses because it is too complex or solves problems the teams do not have.

The right approach begins with discovery: understanding the real pain points of the engineering teams. What are the tasks that cause the most delays? Where are the bottlenecks in the delivery pipeline? What do the most senior engineers do repeatedly that could be automated?

From this discovery, the platform team defines a value-driven roadmap, prioritizing the capabilities that have the greatest impact on the day-to-day work of internal teams. Start small, deliver fast, collect feedback, iterate.

Another critical point is treating product teams as customers. This means SLAs, documentation, support channels, and yes — measuring internal NPS. Teams that feel well served by the platform adopt it voluntarily and become internal evangelists. Teams that feel ignored create parallel solutions, increasing fragmentation.

In practice, organizations that go furthest with Platform Engineering share some common characteristics:

• The platform team has a clear mandate and leadership support — it is not a group of volunteers doing this in their spare time
• There is a dedicated senior technical lead with a product mindset and the ability to influence architectural decisions
• The platform has a developer portal (tools such as Spotify's Backstage are a reference here) that centralizes the experience
• Adoption metrics and impact metrics are tracked regularly — not just infrastructure availability metrics

The relationship between Platform and Cloud

Years of working with AWS have given me a clear perspective on a common misconception: many organizations think that adopting cloud is enough to solve the standardization problem. It is not.

AWS offers more than 200 services. Without an internal platform layer that defines which services are approved, how they should be configured, and how teams access them, you have the same fragmentation problem — now with added cloud costs.

Platform Engineering does not replace the cloud — it governs it. It defines the right abstractions so that product teams can use infrastructure consistently, securely, and cost-effectively, without needing to become experts in every available AWS service.

With Generative AI entering the stack of virtually every company, this role becomes even more critical. Teams that want to experiment with language models, RAG, and autonomous agents need a platform that already has security guardrails, data access standards, and evaluation pipelines ready to go. Without that, each team will improvise its own AI solutions — and the security and compliance risks will be considerable.

When your organization is ready to invest in this

There is no magic number of teams or engineers that justifies creating a dedicated platform team. But there are clear signals that the time has come:

• Different teams make conflicting infrastructure decisions that cause integration problems later
• The time between the start of a new project and the first production deploy is measured in weeks
• Recurring incidents originate from inconsistent infrastructure configurations across teams
• Senior engineers spend a significant portion of their time solving environment issues that should be trivial
• A security or compliance audit reveals that each team implemented controls differently

If you recognized your organization in two or more of these points, the cost of inaction is already greater than the cost of building the platform.

What changes when the platform works

When an Internal Developer Platform is mature and well adopted, the impact goes beyond operational efficiency. It changes the engineering culture of the organization.

Teams begin to trust infrastructure instead of fearing it. New engineers arrive and become productive in days, not months. Technical leadership starts discussing strategy and innovation instead of constantly firefighting infrastructure incidents. The security team stops being the department that says no and becomes an enabler, because controls are already built into the platform.

Ultimately, Platform Engineering is about making technical complexity invisible to those who build products. It is about ensuring that your company's best engineers are focused on the problems that nobody else in the market can solve — not on the problems that everyone has already solved a thousand times.

"The best infrastructure is the one the developer does not need to think about to use. When the platform gets out of the way, innovation appears."

If your organization is still stuck in the cycle of reinventing the wheel with every new team or project, the time to break that cycle is now. Not out of trend-chasing, but because every quarter that passes without a platform strategy is a quarter of competitive advantage handed on a silver platter to those who have already solved this problem.