DevOps isn’t dead: How platform engineering enables DevOps at scale

As DevOps has grown in popularity, the demands placed on developers have grown just as rapidly. In addition to writing code, developers are now expected to manage infrastructure, adopt and integrate new tools, and take on operational responsibilities. This expanding scope can leads to increased cognitive load, reduced productivity, and, over time, higher rates of stress, burnout, and job dissatisfaction.

Platform engineering addresses this challenge by introducing standardized workflows and reusable, self-service components. This includes internal developer platforms (IDPs), CI/CD templates, infrastructure automation, and other tools that reduce manual effort while maintaining security and reliability.

In short, platform engineering builds guardrails that empower developers to move quickly without compromising standards.

This article explores the growing challenges of DevOps at scale and how platform engineering can help organizations overcome them.

Enhancing DevOps with platform engineering

Platform engineering aims to improve DevOps, not replace it. It reduces the need for developers to manage infrastructure directly or build delivery workflows from scratch. For example, instead of manually spinning up CI/CD pipelines, configuring environments, setting permissions, or scaffolding new repositories, developers can use platform-provided templates and services to get started quickly and safely.

Platform engineers often build these capabilities into IDPs, giving developers a single interface for launching new projects with secure, standardized defaults. This reduces onboarding time and ensures consistency across teams.

The cognitive load of DevOps

Although DevOps was designed to make software development more efficient, DevOps engineers often face numerous demanding tasks that increase their cognitive workload. Let’s walk through a few common examples.

Process design and maintenance

DevOps engineers often need to design new processes for new software projects, such as setting up continuous integration and continuous delivery (CI/CD) and spinning up the infrastructure for development environments while ensuring compatibility with production environments.

This involves managing Docker files, Helm charts, and Terraform code, which require periodic maintenance and support as projects evolve. CI/CD pipelines also need building, and although engineers can take some parts from previous projects, the new project’s testing and build requirements add an extra layer of complexity.

Existing processes must be scaled up or down to meet current demand. These processes include scaling infrastructure to meet new processing or storage requirements and modifying existing workflows designed for a small team of engineers that has since grown.

Tech stack management

DevOps practitioners also manage ownership of many aspects of the software development lifecycle. This includes managing third-party tools and products on top of internal codebases and infrastructure. Other developers will also require code reviews and meetings to discuss potential solution options that require specialized DevOps knowledge.

Monitoring and reporting

Finally, DevOps engineers must ensure systems are logging correctly and that metrics can be collected and analyzed. Keeping on top of different software applications’ performances is vital to ensuring they all run smoothly. It also helps engineers understand potential areas that require scaling.

Beware DevOps burnout

All these responsibilities, on top of meeting service-level agreements (SLAs) and other internal business goals, cause a massive cognitive strain on DevOps practitioners. Each task and process creates extra overhead that DevOps practitioners must deal with, often removing resources from their primary goal of innovation and optimization.

As the cognitive load increases, so does associated complexity and stress, causing burnout, mistakes, and entropy to build. This significantly decreases team productivity and can ultimately stifle innovation.

So, how can platform engineering reduce the load and enable engineers to achieve their primary goals?

What do platform engineers do?

Platform engineers develop IDPs that solve everyday DevOps tasks, reducing or removing overheads entirely. This allows DevOps to focus on tasks that provide real business value more quickly.

Automate DevOps tasks

The main goal of IDPs is to provide a standard and reusable approach for all teams. Setting up a repository, assigning the correct team members, spinning up an environment, and configuring a continuous delivery (CD) pipeline are already built into IDP tools and services. These can be broken down into four key management areas: infrastructure, deployment, configuration, and user access control.

Whether using an off-the-shelf IDP or developing your own, most IDPs offer a user interface (some are command-line only) for developers. Typically, an API layer requests the different services to perform an automated action. This action can be to create a Git repository, spin up a database using a terraform script, or any other common DevOps task. Developers then use the IDP to initialize the core parts of a new project automatically.

Abstracting away the lower-level details of performing these actions prevents developers from diverging in their approach. Infrastructure is configured and deployed in a standard way, making maintenance simpler.

Support developer autonomy

IDPs also promote developer autonomy through self-service tools. This prevents lengthy lead times in deploying project resources caused by designing and building the infrastructure from scratch. Now, developers can use the IDP to do the work for them. IDPs also remove the need to create tickets in the backlog for setting up new environments and waiting for them to be prioritized and completed.

Instead, developers can perform these actions via the IDP interface.

Enforce security by design

Finally, IDPs can be secure and compliant from the start. This means that platform engineers bake in security and compliance features into IDP services so that infrastructure follows security best practices when it is deployed. They can also ensure that Git pipelines are configured to automatically scan code for vulnerabilities before being built and released.

By making secure and compliant processes integral to development workflows, platform teams elevate DevOps pipelines into robust DevSecOps pipelines, ensuring that security is a foundational element throughout the software development lifecycle. This approach benefits organizations by reducing both the burden on developers and the risk of data breaches.

Incorporating platform engineering into DevOps

Let’s examine a hypothetical use case of how platform engineering methods could improve a DevOps team’s workflow.

DevOps versus platform engineering

Imagine a business that designs web applications that each follow a similar architectural pattern. There’s a database, an API, and a web-based front end. The team has reusable components like Docker images and CI/CD templates, but every new project still requires manual setup.

DevOps engineers are responsible for writing Dockerfiles, provisioning infrastructure with Terraform, building pipelines, configuring environments, and setting up monitoring and alerts. They also juggle SLAs, maintenance, and ad hoc developer requests.

This manual, one-off approach doesn’t scale. It slows down delivery, creates operational bottlenecks, and puts constant pressure on DevOps teams.

Where DevOps builds solutions for today’s project, platform engineering builds reusable systems for every project.

The automated approach with platform engineering

To solve these scaling issues, platform engineers create reusable workflows and tools. These are often delivered through an IDP, which eliminates the need for manual project setup.

For example, instead of requesting a new Git repository through a ticket, a developer can use the IDP to generate one immediately. The platform provisions the repository, applies access controls, and connects a preconfigured CI/CD pipeline automatically.

The same approach applies to setting up environments, applying Terraform modules, and enabling monitoring. These tasks are preconfigured according to organizational standards, with security and observability built in from the start.

Platform teams optimize DevOps practices

As you can see, platform engineers don’t replace DevOps processes. They enhance them by building a set of standardized patterns into a self-service internal development platform. This removes the burden of project initialization so teams can start providing business value immediately, rather than spending the first few weeks of a project setting up and working through teething issues.

Furthermore, because developers will be more autonomous, platform engineers can then concentrate on solving bigger architectural challenges and feeding that back into the IDP. In this way, they can improve existing services and strengthen newer systems going forward.

Conclusion

DevOps grew in popularity because it gives developers the freedom to manage the end-to-end lifecycle of the application. However, this great power comes with great responsibility. Over time, it increases the cognitive load required to manage and operate applications at scale.

This is where platform engineering adds value. By turning core DevOps workflows into self-service tools, teams can reduce manual effort, speed up delivery, and ensure consistency across projects.

If you’re ready to scale your DevOps practices with platform engineering, sign up for a free CircleCI account and follow our guide to building a scalable IDP. With the right tools in place, your team can move faster, stay secure, and focus on delivering meaningful results.