Preparing for Change: Critical Insights for Adopting Platform Engineering

In today’s hybrid and multicloud environments, complexity is a major challenge. Software development has become more difficult due to the complexity of modern application and cloud architectures. Platform engineering plays a crucial role in mitigating this complexity by providing a unified and streamlined experience for developers and other users, with internal developer platforms (IDP) providing self-service resources and automated workflows. This tool enables businesses to move faster by boosting developer productivity, streamlining workflows, enhancing system reliability and expediting delivery of software solutions.

Adopting platform engineering within an organization's IT strategy, however, is no small feat. About 70% of digital transformation efforts fail due to poor planning, lack of skills and expertise, or resistance to change. Implementing new technologies and processes requires rethinking traditional IT practices and redefining how your organization approaches software development and deployment, as well as internal collaboration.

Many companies face two key questions when considering adoption:

• Where do I start? Identifying the right entry point often requires a clear understanding of business needs, resource availability and employee readiness, which can be difficult without proper guidance.

• What do I need to consider? Factors like cost, scalability, integration with existing systems and the need for staff training are critical to ensuring a smooth transition and long-term success.

This blog addresses these challenges head-on with practical strategies for execution with a focus on self-service.

To understand where to start with platform engineering, we first need to understand its roots in DevOps.

DevOps revolutionized software development by bridging the gap between development and operations teams. Emphasizing collaboration, automation and speed, DevOps teams embraced principles like Continuous Integration/Continuous Delivery/Deployment (CI/CD) and Infrastructure as Code (IaC) as a means of transitioning from rigid, monolithic applications to modular microservices. This helped create the agility and flexibility needed to develop software faster, but the increased speed came at a cost.

Developers faced the overwhelming burden of managing both code and operational tasks. DevOps practices also commonly lacked standardization, leading to fragmentation. Individual application teams created custom workflows and toolchains, resulting in inconsistent practices that complicated security, observability and governance. This lack of centralized oversight and processes constrained the ability to scale effectively across the enterprise.

DevOps teams needed a way to maintain agility while addressing these inefficiencies. Platform engineering introduced a product approach to infrastructure, treating developer platforms as built-for-purpose tools delivering consistent, flexible, self-service experiences. This approach takes the best of DevOps but returns it to an enterprise state — enabling lifecycle management, security operations and observability while empowering teams to focus on development instead of operational overhead.

Platform engineering can be used to extend the developer pipeline into a full enterprise pipeline, with automation inclusive of occasional users, commercial off-the-shelf (COTS) applications, IaC and artificial intelligence (AI) workloads. This provides a way to incorporate those workloads into the self-service, security and full lifecycle manageability of the platform engineering strategy.

At the heart of platform engineering lies a commitment to making the developer or user experience better. A high-functioning platform reduces friction to delivering applications efficiently.

Think of it like a restaurant experience. While DevOps enabled users to “cook any dish” by managing the full cycle — from sourcing ingredients to washing dishes — that approach doesn’t scale very easily. Platform engineering simplifies this process by acting as the restaurant kitchen, where predefined menus (golden paths) offer flexibility without operational overhead. Users order the “meal” they want using predefined inputs, while the platform automates the backend or “kitchen” processes. This not only streamlines complexity and accelerates delivery, but also helps maintain standardization and governance while eliminating bottlenecks caused by legacy practices.

While we won’t go in depth on automation guards and observability here, it’s worth noting that there are three principles that underscore effective platform engineering:

1. Self-Service Capability
Internal developer platforms (IDPs) give users the autonomy to deploy assets (e.g., databases, APIs) via intuitive user interfaces (UIs) or application program interfaces(APIs). By simplifying frequent tasks, users remain focused on coding and innovation. Puppet’s State of Platform Engineering report notes that 40% of engineers find automation-first IDPs significantly improve their productivity. Build processes become repeatable, security considerations standardized and friction minimized.

2. Automation Guards
Standardized guardrails built into IDPs ensure that security, compliance and lifecycle management are seamlessly integrated into workflows. These automations reduce the risk of human errors by enforcing best practices, such as access controls, resource quotas and policy compliance, across the entire development lifecycle. Developers can focus on building while the platform handles critical safeguards in the background, ensuring stability and peace of mind.

3. Actionable Observability
IDPs come equipped with built-in observability tools that integrate directly with monitoring and logging systems. This enables users to track metrics, identify bottlenecks, and debug issues in real-time without needing additional complex setups. With actionable insights at their fingertips, teams can quickly address performance issues, optimize system health, and improve overall application reliability, keeping innovation and uptime on track.

With that, let’s discuss these principles and other key factors that play a role in implementing platform engineering effectively.

Implementing platform engineering goes beyond simply adopting new tools; it requires a fundamental shift in both culture and strategy to ensure long-term success. Four essential focuses must be prioritized to harness the benefits and promise of platform engineering.

1. Automation First
To stay competitive, you have to automate, automate, automate. Automation is the backbone of a streamlined pipeline. IaC replaces manual infrastructure provisioning with repeatable, efficient scripts, reducing errors, saving time and enabling faster iterations. Establishing end-to-end deployment automation tied to approval gates that ensure compliance without slowing things down is a must. This is what enables faster time-to-market and the ability to scale quickly while maintaining quality and freeing up teams to focus the business.

2. Full-Stack Observability
Operational efficiency isn’t just about having systems that work — it’s about being able to see how they’re working at all times. Full-stack observability ensures you’re not just reacting to problems but proactively identifying them before they escalate. Investing in tools like distributed tracing and real-time alerts will allow you to create a culture of transparency and accountability across your teams. Imagine being able to pinpoint the root cause of an issue in seconds rather than hours or even days. For decision makers, this means fewer outages, better customer experiences, and a more connected and collaborative workforce across IT and business units. Visibility is power, and it directly translates to operational success.

3. Standardized Guardrails
Standardized guardrails ensure that compliance and security are baked into every process without stifling creativity. Pre-built templates and standardized APIs help teams move faster by providing a clear foundation to work from while automating policy enforcement reduces the risk of misconfigurations that can lead to costly security or compliance breaches. For business leaders, this means peace of mind; your teams can scale without chaos and innovate freely without fear of cutting corners or compromising sensitive data.

4. Change Management
Now for the big one. Change management is arguably the most crucial component of platform engineering success. The true success of this powerful business tool lies in how effectively it is embraced at every level of the process. For many organizations, this requires rethinking how teams work together and aligning mindsets around shared goals. Clearly communicating the value of platform engineering to the entire organization can help business leaders and decision makers drive this transformation.

Show teams how these changes will make their work easier, more impactful and aligned with business objectives. Start small — pilot workflows with one team or workload to help demonstrate success. This gives you a starting place to work from while minimizing risk and building confidence across the company. You can iterate and scale from there.

Platform engineering amplifies scalability, security and innovation, especially where hybrid cloud environments are concerned. However, success requires both technical expertise and strategic planning, from designing internal developer platforms to implementing automation workflows. That’s where working with platform engineering experts like CDW makes all the difference.

CDW helps organizations successfully adopt and implement platform engineering with the following strategies:

• Tailored consulting for piloting and scaling internal platforms into production.
• Workshops on platform engineering, IaC, and observability.
• Actionable 5-year roadmaps for aligning platform goals with business objectives.