Platform engineer: what they do and why they are transforming DevOps teams

As an organization expands its digital products, the infrastructure needed to develop and operate them also increases. Teams begin to work with Cloud, containers, Kubernetes, CI/CD pipelines, observability, secret management, Infrastructure as Code, and various security and deployment mechanisms.

These capabilities allow building more scalable and automated systems, but they also shift a considerable part of the operational complexity onto developers. Creating a new service may end up requiring knowledge about infrastructure, networks, pipelines, permissions, monitoring, and configuration that is far removed from the functionality the team needs to develop.

Platform Engineering addresses this situation by building shared capabilities that teams can consume through an internal platform. The Platform Engineer participates in the design and operation of that platform to provide standardized pathways, automation, and self-service mechanisms that reduce the operational burden on development.

Its growth is also changing the way DevOps is applied. Instead of relying solely on each team to master all the tools needed to operate their applications, a platform can turn part of that knowledge into reusable services.

What is platform engineering

Platform Engineering is a discipline focused on designing and maintaining internal platforms that enable software teams to develop, deploy, and operate applications.

The platform acts as a layer between developers and part of the complexity of the infrastructure. It can provide standardized mechanisms for creating services, deploying applications, requesting resources, configuring observability, or managing certain Cloud components.

The goal is to offer these capabilities as internal products that developers can use with sufficient autonomy. This allows for maintaining technological standards without forcing each team to rebuild the same processes.

From independent tools to an integrated experience

An organization may have Kubernetes, Terraform, CI/CD systems, observability, and Cloud services without necessarily having an internal platform.

Platform Engineering emerges when those capabilities are organized around an experience designed for the teams that use them. Instead of just delivering tools, the platform team defines how they should be consumed and what processes can be automated.

A developer could create a new service by selecting an approved template and providing some parameters. The platform can then take care of generating repositories, pipelines, infrastructure, observability, and necessary configurations according to the organization's standards.

The complexity continues to exist, but it is no longer distributed in the same way among all teams.

What does a platform engineer do

The Platform Engineer works on the infrastructure and tools that enable software operation, but their responsibility is particularly oriented towards turning them into reusable capabilities for other technical teams.

The scope varies depending on the organization and the maturity level of its platform. Among their usual responsibilities are:

• Designing and maintaining components of an Internal Developer Platform.

• Automating infrastructure provisioning, environments, and services through Infrastructure as Code.

• Creating templates and golden paths for recurring development cases.

• Integrating CI/CD, observability, security, secret management, and Cloud services within standardized workflows.

• Developing self-service mechanisms to reduce manual requests between development and operations.

• Maintaining shared components used by different engineering teams.

• Analyzing Developer Experience and identifying friction points within the development cycle.

• Defining guardrails that allow maintaining technical standards without blocking team autonomy.

The work combines knowledge of infrastructure, automation, and software development. An internal platform needs to evolve like any other technological product: it requires architecture, maintenance, documentation, feedback, and decisions on what capabilities to incorporate.

Internal developer platform: the centerpiece of platform engineering

An Internal Developer Platform, commonly abbreviated as IDP, provides an interface between developers and various infrastructure and operational capabilities.

It does not have to be a single application. It can combine a portal, APIs, command-line tools, pipelines, templates, Infrastructure as Code, and internal services. The important thing is that it presents a coherent experience for solving frequent tasks.

A team could use the platform to create an environment, deploy a service, or query operational information without knowing all the details of the tools that execute those operations.

DevOps Engineers can directly participate in building these capabilities, especially when the platform needs to integrate automation, CI/CD, and existing infrastructure.

Self-service reduces dependencies between teams

Without self-service mechanisms, a relatively simple task can generate a chain of requests. Development needs an environment, another team must create it, permissions are then requested, and finally, the pipeline or monitoring is configured.

When this pattern is repeated for numerous teams, infrastructure functions can become a bottleneck.

A platform can turn frequent operations into self-service workflows. The developer requests a capability through a controlled interface, and automation executes the necessary steps.

Self-service does not mean providing unlimited access to infrastructure. Permissions, policies, approved configurations, and limits continue to be part of the platform.

Golden paths: standardizing without forcing everything to be built from scratch

A golden path represents a recommended and prepared way to solve a recurring need. It can define how to create an API, deploy a microservice, configure observability, or publish an application.

The platform team prepares components and automations that allow following that path with less effort. If the organization uses Kubernetes, for example, a developer should not need to write every necessary configuration from scratch to deploy a standard service.

The golden path can automatically incorporate security configurations, health checks, logging, metrics, and necessary resources.

This allows repetitive decisions to be resolved once and reused. At the same time, cases that truly need a different architecture can maintain mechanisms to deviate from the standard path when there is a technical justification.

Platform engineering is changing the way DevOps is applied

DevOps drove greater collaboration between development and operations and promoted practices such as automation, continuous integration, programmable infrastructure, and accountability for software throughout its lifecycle.

The growth of the technological ecosystem has made applying these principles require mastering an increasing number of tools. Asking each developer to deeply understand Kubernetes, Terraform, Cloud networking, IAM, observability, and pipelines can create a considerable cognitive load.

Platform Engineering attempts to turn part of those DevOps capabilities into consumable internal services. Teams maintain responsibility for their applications while the platform provides a standardized foundation for building and operating them.

This approach can also free specialists in Cloud Engineering from repeatedly resolving similar requests and allow them to focus on infrastructure capabilities that can be reused by numerous teams.

Platform engineer vs devops engineer vs sre

The boundaries between these profiles can vary between organizations. In small teams, one person may take on responsibilities belonging to several disciplines. The difference becomes clearer when observing the main focus of each function.

The boundaries can overlap. A Platform Engineer may work with Terraform and Kubernetes just like a DevOps Engineer, while an SRE may develop automations that are later incorporated into the platform.

The difference lies mainly in the problem they are trying to solve. Platform Engineering uses infrastructure and automation capabilities to build an internal experience that other teams can consume.

Developer experience becomes a metric for the platform

An internal platform has users: the developers. Therefore, its quality should not be evaluated solely by the availability or performance of the infrastructure.

It also matters how long it takes a team to perform routine tasks. Creating a new service, deploying a version, obtaining an environment, or accessing logs can take minutes, hours, or several days depending on the existing processes.

Platform Engineering observes these workflows to identify friction. If creating an environment requires multiple tickets and manual approvals, there is an opportunity for automation. If each team configures observability differently, there may be a capability that is worth standardizing.

The platform works best when its decisions stem from the real needs of the teams that develop software.

Kubernetes and cloud often drive the need for platform engineering

The adoption of Cloud allows the use of numerous specialized services and the modification of infrastructure through software. Kubernetes adds a powerful layer for running and coordinating containerized applications.

These capabilities increase the options available to teams, but they also increase the decisions they must make.

In an organization with few services, managing that complexity directly may seem reasonable. When there are dozens of applications and multiple teams, repeating infrastructure configurations, pipelines, security, and observability can lead to inconsistencies and duplicated work.

IT infrastructure specialists can work alongside Cloud, DevOps, and Platform Engineering to maintain a coherent operational base when the platform needs to integrate with networks, identity, corporate systems, and other technological components.

Infrastructure as code enables turning standards into reusable components

Infrastructure as Code makes it easier to represent infrastructure through versioned and automated configurations. Within Platform Engineering, this capability can be used to build modules that teams consume indirectly from the platform.

Instead of providing each developer access to build resources from scratch, the platform team can offer predefined components for routine needs.

This allows for incorporating configurations for networking, security, tagging, observability, or organizational policies within the modules themselves. Standardization occurs during resource creation and reduces subsequent corrections.

An internal platform should be treated as a product

Creating a collection of scripts and tools does not guarantee that developers will use it. A platform that adds additional steps or limits routine cases may end up being avoided by its own users.

The Platform Engineering team needs to understand what problems generate the most friction and prioritize capabilities based on their impact. This requires talking to teams, observing workflows, and analyzing what tasks are repeated.

Documentation, ease of use, and stability of interfaces are also part of the product. Continuously changing internal templates or APIs can shift additional work onto the platform's consumers.

Software architecture also plays a role in these decisions, especially when platform standards need to adapt to different types of applications and architectural patterns.

Platform engineering also introduces guardrails

A platform can increase developers' autonomy while simultaneously maintaining certain constraints.

Guardrails establish limits within which teams can operate. A template may allow selecting the size of a resource among approved configurations, require certain security policies, or automatically incorporate observability.

This approach reduces the need to manually review each recurring decision. Controls can be integrated into the workflows used to create and deploy software.

Security, compliance, and costs can benefit from this strategy because certain requirements no longer rely solely on each team remembering to apply them individually.

When does a company need platform engineering

Not all organizations need to build an Internal Developer Platform. If there are few developers, simple infrastructure, and a limited number of applications, maintaining an additional platform may introduce more complexity than it eliminates.

The need increases when growth causes different teams to start repeatedly solving the same infrastructure and operational problems.

Signs that the team may need an internal platform

Some patterns allow identifying when it is worth evaluating Platform Engineering:

• Developers frequently rely on tickets to obtain environments, infrastructure, or access.

• Each team builds pipelines, observability, or similar configurations independently.

• Creating a new service requires understanding too many infrastructure tools.

• DevOps continuously receives repetitive operational requests that could be automated.

• There are significant differences between application configurations that should follow similar standards.

• Incorporating a new developer requires learning numerous internal processes before being able to deploy software.

• Cloud and Kubernetes have increased the number of operational decisions each team must take.

The isolated appearance of one of these situations does not immediately require creating a platform team. When several are repeated and affect numerous teams, centralizing certain capabilities can generate a much greater impact.

How to start platform engineering without building too large a platform

One of the risks is trying to design a platform capable of solving all possible scenarios from the beginning. This can lead to months of development before teams receive a concrete improvement.

A more practical approach begins by identifying one or two workflows that generate friction recurrently. Creating a new service, deploying an application, or requesting an environment can be good candidates when they affect several teams.

The first version of the platform can automate those processes and later incorporate new capabilities based on actual usage. This evolution allows validating which components generate value before expanding the investment.

It also avoids building overly rigid abstractions. The platform needs to find a balance between standardization and the ability to support technically justified exceptions.

Measuring the impact of platform engineering

The success of Platform Engineering should not be measured by the number of tools incorporated into the platform. A larger IDP does not necessarily imply a better experience.

Metrics should observe whether teams can deliver software with less friction and maintain the necessary standards. Depending on the organization, they can analyze environment creation times, deployment durations, frequency of manual requests, adoption of golden paths, or the time needed for a new developer to work autonomously.

It can also be measured how many different components have been replaced by shared capabilities and how much repetitive operational work no longer requires manual intervention.

These signals allow determining whether the platform is reducing complexity or simply shifting it to another technological layer.

Platform engineering does not replace devops

Platform Engineering and DevOps operate at different levels. DevOps provides principles and practices to improve collaboration, automation, and accountability for software. Platform Engineering uses many of those practices to build a platform that facilitates their application at scale.

Teams still need knowledge of infrastructure, deployments, and operations. The difference lies in how much of that knowledge each squad must rebuild and how much can be provided as a shared capability.

As the organization grows, this separation can allow DevOps to evolve from resolving individual requests to building systems that enable teams to resolve them directly.

The platform engineer turns operational complexity into a reusable capability

The growth of Cloud, Kubernetes, automation, and distributed architectures has provided more capacity to software teams, but it has also increased the number of decisions necessary to operate applications.

Platform Engineering attempts to organize that complexity through internal platforms designed around those who develop software. Self-service, golden paths, Infrastructure as Code, and shared components allow turning specialized knowledge into reusable capabilities.

The Platform Engineer sits at the center of this model. They need to understand infrastructure and automation but also design an experience that other teams can use without knowing all the implementation details.

For organizations with multiple teams and a growing technological infrastructure, incorporating this capability can reduce dependencies and improve delivery consistency. An IT outsourcing model can also allow incorporating specialists in DevOps, Cloud, and infrastructure to build or reinforce these capabilities without immediately creating the entire structure internally.

If your company is evaluating how to scale its engineering teams or develop an internal platform, you can schedule a call with lateam to discuss what profiles and capabilities the architecture needs.