Platform Engineering: Bridging the Developer Experience Gap in Enterprise Software Development

What is Platform Engineering

Before we understand platform engineering (PE), let’s quickly run through a scenario of typical software teams. Here, we have multiple teams working on different projects. Each team has their own way to set up servers, set up CI/CD pipelines, set up monitoring tools, and deployment scripts, etc. The problem is that, when we have a completely new team for a new project, the company has to spend time and resources to set them up with the same set of tools. In some cases, the setup is included in the project scope. The tools can be different based on the technology stack, but the motive would be the same. This can be time-consuming and costly.

Enter platform engineering - The idea behind platform engineering is to give developers ready-to-use, standardized tools and environments so they don’t reinvent the wheel every time. It is also referred to as “Internal Developer Platform”—IDP. Basically, with IDP, the team doesn’t have to spend time setting up infrastructure. They can just focus on the development of real products.

Is it the same as DevOps? No. This is a common misconception about platform engineering. DevOps is more like a set of principles/guidelines (culture + practices) for achieving faster, automated, and more reliable software delivery. Platform engineering takes those principles and builds reusable systems (platforms) so that all teams can apply DevOps without reinventing automation from scratch.

Importance of Platform Engineering

During the early adoption of DevOps (around the year 2000), it was expected that developers should implement necessary infrastructures beyond the actual product. While it improved ownership, it also created an unintended consequence: developer cognitive overload. [1]

Research shows that developers spend over 10x more time reading and understanding code than writing it. Add to this the operational burden of managing complex deployment pipelines, monitoring systems, and infrastructure configurations, and it becomes clear why 76% of organizations admit their software architecture's cognitive burden creates developer stress and lowers productivity.[2]

Platform engineering takes away the painful burden of implementing DevOps and lets developers focus on the actual development. Rather than expecting every developer to become an expert in Kubernetes, Terraform, and observability tools, PE abstract away this complexity while maintaining flexibility.

Additionally, platform engineering is agnostic to technologies and environments. For example, one team uses .NET, another uses Node.js, another uses Python with an environment as on-prem or AWS or Azure or Kubernetes etc. The platform team can build standardized building blocks (abstractions) that work across technologies and environments.

Platform engineering is set to grow significantly in 2025 and beyond. [3]

Here are some opinions from industry leaders:

• Google reports that standardization of build/deployment pipelines and self-service infra provisioning led to reduction in onboarding time and a measurable increase in deployment frequency.[4]
• Effectual documents a “reduction in operational support requests and decrease in security incident response time” after IDP implementation.[5]
• N-xI survey states that organizations with mature IDPs saw “cycle time reductions of up to 50% and self-reported DevEx improvements in annual employee surveys”.[6]

Current Implementation Challenges

As impressive as the idea of platform engineering looks, the challenges are just as significant. Let’s discuss the major challenges.

Limited expertise: While the skills required to develop PE aren’t unique, the challenge is to integrate those skills to implement it. For example, DevOps may be good at containerization and orchestration but may not have enough expertise to develop API. The same applies to developers as they can create robust API but lack DevOps, or cloud knowledge. Further, a person knowing both may not be a good product manager. So, a good PE team should encompass a mix of DevOps, Cloud expert, software engineering and product mindset. I guess this should give you an idea of how difficult it could be to find and assemble a team with these skills.

3rd party platforms: If the above challenges feel overwhelming, the organization may plan to buy a 3rd party platform engineering product. However, PE is a product and not a tool. Meaning, the requirements can change rapidly and dependence on 3rd party PE products may have adverse effects.

Integration Effort: If an organization has multiple large existing projects, then integrating those development and operational tools would be a difficult task.

Key points for building platforms

Platform engineering requires a significant amount of time and money investment. If the features provided by the platform are not what developers need then it may sit unused. Let’s discuss key points to consider while building a robust and useful platform.

Research the existing team’s setup: Even though users are internal teams, various factors like client need, technology stack etc. could impact individual infrastructure setup. Thorough research must be conducted before initiating the work. The research should be able to answer pain areas, intentions or reasons behind team practices and tool usages. As this is a crucial phase, the result should have a clear picture of what the product will do after the developer checks-in the code - the journey of the code from developer’s machine to production box.

A Google Cloud engineering article emphasizes the need for foundational “golden paths”—prescribed routes and templates that enable developers to ship faster while following security and compliance requirements. “Without golden paths, IDPs risk becoming yet another layer of complexity,” the authors state.

Measuring the Impact

Rigorous measurement of platform engineering products now includes both technical and human-centered productivity metrics. The top statistics and measurement approaches observed among leading teams include:

Lead Time for Changes: Time between code commit and deployment. Deployment Frequency: Number of deployments to production per unit of time. Change Failure Rate: Percentage of deployments causing failures in production. Mean Time to Recovery (MTTR): How long it takes to restore service after a failure. Developer Satisfaction Scores: Collected via anonymized internal surveys on ease of use, perception of productivity, and pain points. Onboarding Time: Time required for a developer to ship their first change via the platform. New Project Setup Time: This single measure can impress organizations when a new project is ready in very short duration compared to a non-IDP environment.

Note that, if an existing development team already has a robust individual solution then the metrics may not show much improvement, however, the goal is to have a re-usable product.

Conclusion

Platform engineering is not just another tech buzzword—it is a shift in how organizations approach software delivery. By creating standardized, reusable, and developer-friendly platforms, companies reduce cognitive load, accelerate onboarding, and enable developers to focus on building products instead of managing infrastructure. Unlike DevOps, which defines principles and practices, platform engineering turns those ideas into tangible systems that every team can leverage.

However, building a successful platform engineering product requires thoughtful investment, a multidisciplinary team, and a progressive approach to adoption, and measurable outcomes. It’s not a one-size-fits-all product but rather a product that evolves with organizational needs. When implemented effectively, platform engineering can deliver measurable business value—shorter cycle times, fewer operational bottlenecks, improved developer experience, and ultimately faster innovation.

In essence, platform engineering bridges the gap between DevOps ideals and practical execution, laying the foundation for sustainable, scalable, and developer-centric software delivery in 2025 and beyond.

References

[1]: https://www.castsoftware.com/pulse/alleviating-the-cognitive-load-on-software-developers [2]: https://www.agileanalytics.cloud/blog/reducing-cognitive-load-the-missing-key-to-faster-development-cycles [3]: https://mia-platform.eu/blog/top-4-predictions-for-platform-engineering-in-2025-and-beyond/ [4]: https://cloud.google.com/blog/products/application-development/how-platform-engineers-can-improve-their-developers-experience [5]: https://effectual.ai/platform-engineering-for-the-financial-services-industry-2/ [6]: https://www.n-ix.com/platform-engineering-trends/ [7]: https://wso2.com/library/blogs/top-ten-internal-developer-platforms-compared-2025/