What is Platform Engineering?

Platform engineering is a set of modern engineering practices that take a holistic approach to managing the entire software development lifecycle, encompassing infrastructure, tools, and processes. The aim of platform engineering is to provide a scalable and secure platform that supports the development, deployment, and operation of software applications in a standardized and efficient way.

What is platform engineering?

In a platform engineering approach, one or more teams—often referred to as the platform engineering team or the platform team—build a comprehensive set of shared tools and services (aka “the platform”) to help development teams develop, deploy, and operate cloud infrastructure on a self-service basis. This includes cloud infrastructure, container orchestration platforms, databases, networking, monitoring, code repositories, and deployment pipelines.

Platform teams use a customer-driven mindset where they treat the application developers that they serve as customers that must be understood and won over through products that solve their problems. The products these teams offer are infrastructure tools and building blocks that development teams use to provision and manage standardized infrastructure for their applications and services. Typically, these tools have built-in guardrails that enforce best practices and security standards without impeding developers’ agility and workflow. This is all done in service of increasing the speed of delivery for the company’s products.

Golden paths and internal developer platforms

Two ideas anchor most platform engineering practice: the internal developer platform and the golden path.

An internal developer platform (IDP) is the product that a platform team ships to its developers. It is the unified surface through which developers self-serve everything they need to build, run, and operate their services. An IDP typically combines a developer portal, infrastructure as code templates, CI/CD pipelines, secrets and policy management, and observability tooling. An IDP is not a single product you buy; it is a curated composition of tools and shared services that reflects your organization’s stack, security model, and developer workflows.

A golden path (sometimes called a paved road) is an opinionated, well-supported route through the platform for a common task — for example, “deploy a stateless TypeScript service to production.” Golden paths are designed to be the fastest, lowest-friction, and most secure option for the most common case. Developers can still go off-road for unusual needs, but the platform team commits to maintaining, supporting, and improving the golden paths as a product. The combination of an IDP and well-defined golden paths is what makes self-service possible without sacrificing security, compliance, or operational consistency.

What are some of the requirements for platform engineering?

Regardless of implementation details or specific methods, there are some simple requirements that many platform engineering teams follow. All of these requirements are driving toward maximizing the use of the cloud at scale across an organization while being secure and compliant and enabling developers and development teams to ship faster.

• Simple and powerful user experience: Build curated experiences that empower developers by meeting them at their level of expertise. Use a variety of approaches to provide an ideal user/developer experience, including infrastructure code libraries (reusable pieces of code), infrastructure CLIs, internal developer portals (IDPs), or shared IaC templates.
• Automation as default: Automation reduces devastating errors. Don’t leave anything to ClickOps. Every change to infrastructure must be run through tests before rolling into production. No change should be untraceable. All infrastructure from resources, configurations, environments, and secrets are tracked in version control. Everything from infrastructure provisioning to control plane orchestrations needs to be programmable.
• Full visibility on everything: Log, monitor, and observe all infrastructure for greater operational control. Optimize against unnecessary costs.
• Security as a foundation: Security and compliance guardrails need to exist for everything. Fine-grained access controls should exist for every piece of infrastructure. Prefer dynamic, short-lived credentials over long-lived, static credentials with seamless integration into development workflows.
• Well architected by design: Decouple the application complexity from the infrastructure complexity, reducing the blast radius of incidents while increasing resiliency. Construct shareable infrastructure components that are built for high availability and low operational maintenance. Operate seamlessly across heterogeneous environments while implementing best-in-class infrastructure.

What is a platform engineer?

Platform engineer is a term used to describe the engineers that make up a platform team or a platform engineering team. Typically, these engineers have the multi-disciplinary skills, experience, and empathy needed to build a great product, serve developers’ needs, and “go to market” within their company. Often, they have experience with multiple engineering disciplines like infrastructure or DevOps and software engineering. The reality is that many engineers who perform platform engineering responsibilities do not have the title “platform engineer.” In practice they have varying job titles like software engineer, DevOps engineer, SRE, cloud architect, cloud engineer, and more. By providing developers with infrastructure and tooling to deploy and operate their applications efficiently, platform engineers enable developers to focus on building great software.

Platform engineers typically take on a mix of responsibilities that span product, infrastructure, and developer-facing work:

• Discovering developer needs: Running interviews and surveys with internal customers, tracking feedback, and prioritizing the platform roadmap like a product manager would.
• Building shared infrastructure components: Authoring reusable infrastructure as code modules, secure-by-default templates, and service blueprints that developers can compose.
• Operating the platform itself: Treating the IDP as production software — running it on SLOs, owning its on-call rotation, and managing its own CI/CD.
• Embedding guardrails: Codifying security, compliance, and cost policies so they are enforced automatically rather than reviewed manually.
• Enabling adoption: Producing documentation, examples, office hours, and migration tooling so development teams can self-serve onto the platform.

The role draws on a broad skill base: cloud infrastructure and container orchestration, infrastructure as code, CI/CD, observability, security, and the product and communication skills required to treat developers as customers.

How does platform engineering differ from DevOps and SRE?

Platform engineering, DevOps, and site reliability engineering (SRE) all aim to make software delivery faster and more reliable, but they answer different questions and produce different artifacts.

The three disciplines are complementary, not mutually exclusive. Many organizations run all three: DevOps sets the cultural baseline, SRE protects production, and platform engineering productizes the shared tooling that both depend on.

Why is platform engineering important?

Developers need infrastructure to run their applications and services. Traditionally, companies have used central infrastructure teams that provision and manage infrastructure on behalf of developers, but this model is prone to bottlenecks as developer requests for infrastructure overwhelm central teams. As modern development teams have taken responsibility over owning and operating their own infrastructure, they also need simple and fast ways of provisioning it while adhering to best practices.

Platform teams solve these challenges:

• The cloud is too complex and unwieldy for most developers to use without abstractions and tooling
• Developers need to know which infrastructure resources to provision
• Developers need an easy way to provision, configure, and manage infrastructure
• Infrastructure provisioned by developers needs to adhere to company best practices

Platform engineering can increase development velocity, improve security, increase infrastructure’s adherence to best practices, and reduce operational costs through automation. It helps organizations increase the ROI on cloud investments and improves the software delivery lifecycle so that developers can ship new features faster.

Many companies have already created dedicated teams for platform engineering. In its 2022 Hype Cycle for Software Engineering, Gartner predicted that by 2026, 80% of large software engineering organizations would establish platform teams as internal providers of reusable services, components, and tools for application delivery (up from 45% in 2022) — a shift that is now well underway across the industry, from financial services to consumer retail (see the case studies.

How is AI changing platform engineering?

Platform engineering is one of the disciplines most directly reshaped by AI. The shift shows up in three places at once:

• More infrastructure, more surface area to govern: AI coding assistants let application developers generate infrastructure faster than ever, which means platform teams are now responsible for guardrails over a much larger volume of cloud resources, IaC programs, and configurations than they were even two years ago. Policy as code, drift detection, and centralized observability move from “nice to have” to load-bearing.
• AI agents as a new class of platform consumer: Human developers are no longer the only callers of the platform’s APIs. Coding agents, deployment agents, and on-call agents increasingly provision, debug, and remediate infrastructure directly. That makes a clean, programmatic, well-documented platform interface significantly more valuable, with strong authentication, authorization, and audit trails on it as table stakes.
• AI as a force multiplier for platform engineers themselves: Routine platform work (writing new IaC modules, diagnosing failed deployments, reconciling drift, keeping dependencies current across many stacks) is increasingly automatable. The most leveraged platform teams use AI to extend the surface area a small team can credibly support, not to replace headcount.

Pulumi Neo is a purpose-built AI infrastructure agent designed for this last shift. It works inside a platform team’s existing Pulumi setup, enforces the same policy as code, and takes on provisioning, debugging, and remediation work, freeing the team to focus on platform design and developer experience rather than ticket queues.

How to get started with platform engineering

There is no one-size-fits-all blueprint, but most successful platform initiatives follow a similar sequence:

1. Identify your developer customers and their top pain points. Talk to development teams about what currently slows them down (environment provisioning, secrets management, deployment, observability) and rank the problems by frequency and cost.
2. Treat the platform as a product, not a project. Stand up a dedicated team with a product manager (or product-minded engineer), define a roadmap, and measure success by developer adoption and lead time rather than infrastructure metrics alone.
3. Define your first golden path. Pick the single most common developer workflow (for example, “stand up a new service in production”) and pave it end to end. Resist the temptation to support every framework, language, and cloud up front.
4. Build on reusable infrastructure as code components. Package your golden path as IaC modules, templates, and policies that developers consume rather than copy. Pulumi supports this with general-purpose languages, reusable components, and policy as code.
5. Layer in self-service through an internal developer portal. Whether you use Backstage, Port, or a custom portal, surface the platform through an interface that meets developers where they already work.
6. Iterate against a maturity model. The CNCF Platform Engineering Maturity Model defines five capability areas (investment, adoption, interfaces, operations, and measurement) across four stages (provisional, operational, scalable, and optimizing), and gives platform teams a shared vocabulary for tracking progress.

Team structure matters as much as tooling. The Team Topologies framework, widely adopted in platform engineering practice, frames the platform team as a dedicated topology that exists to reduce the cognitive load on stream-aligned product teams.

Common challenges of platform engineering

Even well-resourced platform teams hit a predictable set of pitfalls. Knowing them in advance is half the battle:

• Building in a vacuum: Platforms designed without continuous developer feedback tend to ship features no one uses. Treat developer interviews and adoption metrics as core platform telemetry.
• Trying to support everything at once: Spreading the platform across too many languages, frameworks, or clouds before any single golden path is solid leads to a shallow surface that no team trusts.
• Confusing platform engineering with shared services: A central infrastructure team that simply owns shared tooling is not a platform team. Platform engineering requires a product mindset, a defined developer customer, and treating the platform as a first-class internal product.
• Heavy-handed governance: Mandating the platform without making it the lowest-friction path drives developers to work around it. Guardrails should be embedded in golden paths, not bolted on as approval gates.
• Under-investing in operations: An IDP that is unreliable, slow, or undocumented quickly loses developer trust. Run the platform itself with the same SLOs, observability, and on-call discipline you expect of any production service.

Frequently asked questions

What is the difference between platform engineering and DevOps?

DevOps is a cultural and process shift that aims to break down silos between development and operations. Platform engineering is one concrete way to operationalize DevOps at scale: a dedicated platform team builds an internal product (the platform) that packages DevOps practices into self-service tools for developers. In short, DevOps is the philosophy; platform engineering is a discipline that productizes it.

Is platform engineering the same as an Internal Developer Platform (IDP)?

No. Platform engineering is the practice; an Internal Developer Platform (IDP) is one of the artifacts that practice produces. A platform team’s deliverables typically include the IDP plus the golden paths, infrastructure code libraries, security guardrails, CI/CD integrations, and operational runbooks that surround it.

When should an organization invest in a platform team?

The strongest signals are repeated developer wait time on a central ops or infrastructure team, divergent infrastructure patterns across product teams, recurring security or compliance gaps in self-built setups, and growth past the point where shared tooling clearly outweighs the cost of building it. Below that scale, a lightweight set of templates and conventions suffices.

How big should a platform engineering team be?

There is no universal answer, but platform teams often start small (a handful of engineers) and scale with the breadth of the platform’s surface area rather than headcount alone. A focused team owning a well-scoped platform consistently outperforms a larger team spread thin across too many internal products.

Does platform engineering replace SRE?

No — the two are complementary. SRE focuses on the reliability of production services through SLOs, error budgets, and incident response. Platform engineering focuses on developer experience and self-service infrastructure. Most companies that adopt platform engineering keep SRE in place; the platform team often surfaces SRE-defined guardrails through the internal platform itself.

What tools do platform engineering teams use?

A typical platform stack combines infrastructure as code (such as Pulumi), a container orchestrator (commonly Kubernetes), a CI/CD system, a secrets and configuration layer, a policy-as-code engine, and an IDP front end (Backstage, Port, or a custom portal). The specific tools matter less than how cleanly they compose into a coherent self-service experience.

Case studies

Elkjøp Nordic

Elkjøp Nordic is the leading consumer electronics retailer in the Nordics. The company had a modernization strategy to increase agility of development teams by giving them ownership over their services and the infrastructure that runs them. At the same time, they wanted to create security and compliance guardrails that prevent issues while maintaining developers’ freedom. They accomplished this by building an infrastructure platform application that enabled developers to provision infrastructure running on Kubernetes in Azure. Learn more in the blog post.

Washington Trust Bank

Washington Trust Bank modernized its software development and infrastructure practices since migrating to Azure and adopting infrastructure as code. It enables developers with self-service infrastructure components, prevents developers from deploying forbidden resources with Pulumi Policies, and uses automation to save time and effort.

Conclusion

Given platform engineering’s strong focus on infrastructure management, automation, and standardization, platform engineering teams need a solution that enables them to adhere to the principles of platform engineering while empowering their developers and development teams to leverage the cloud in a secure, scalable, reliable, and consistent way.

Pulumi’s solution for platform teams encompasses all of the key requirements described earlier in this article:

1. The developer control plane enables the simple and powerful user experience, allowing platform teams to meet the varying needs of different developers and development teams. The core infrastructure as code tool supports the languages that teams are already familiar with (including TypeScript, Python, Go, C#, Java, and YAML), and leverages the powerful ecosystems surrounding these languages (IDE support, linters, and test frameworks, for example). There’s also support for internal developer portals like AWS Proton and Backstage.
2. Integration and delivery is key to supporting automation as the default. This includes extensive integration with numerous CI/CD systems as well as Pulumi’s own CI/CD offering, called Pulumi Deployments. The Automation API makes it possible to embed IaC into application software, empowering teams to create reusable infrastructure workflows.
3. Monitoring and logging provides the “full visibility on everything” that is a requirement for platform engineering, through support for and integration with leading monitoring, logging, and metric solutions. Pulumi Insights provides advanced search (including natural language search), analytics, and artificial intelligence (AI) into Pulumi Cloud to provide actionable knowledge on cloud usage and cost optimizations.
4. Security and identity ensure security is a foundational element. Pulumi Policies provides policy-based controls—including remediation of policy violations—using the same general purpose programming languages that our core IaC offering supports. Pulumi ESC enables centralized access to secrets and configuration information.
5. Pulumi’s robust provider ecosystem opens up access to a wide plethora of resources to help ensure that all the necessary services, platforms, and offerings needed to build a well-architected design are available.

Pulumi offers a modern and flexible approach to solving the needs of platform engineering teams. Request a demo of Pulumi, or get started using Pulumi’s tools today.