
May 30, 2024
dotGeneral
Platform Engineering vs. DevOps: What’s the Difference?
As businesses strive to innovate and deliver software faster and more reliably, new methodologies and roles have emerged. Among these, platform engineering has become crucial. According to Gartner, by 2026, 80% of software engineering organizations will establish platform teams.
What is all this hype about, and how does platform engineering differ from DevOps? In this article, we’ll define these two closely related concepts, identify their discrepancies, and provide guidance on implementing platform engineering, a potential next step in the DevOps evolution.
What is DevOps?
The key goal of DevOps is to bridge the gap between software development (Dev) and IT operations (Ops) by breaking down silos between these areas, ensuring seamless collaboration. This collaboration facilitates the automation and optimization of software delivery processes. Traditionally, development and operations teams worked in isolation, leading to communication breakdowns, lengthy deployment cycles, and increased error risks. DevOps addresses these issues by fostering shared responsibility for development and operations tasks.Key roles of DevOps engineers include:
- Continuous Integration and Continuous Deployment (CI/CD)
- Infrastructure as code (IaC)
- Monitoring and logging
What is platform engineering?
Platform engineering focuses on designing and building the infrastructure and services that support application development. Platform engineers are the architects and caretakers of this foundational layer, ensuring developers can concentrate on coding without worrying about the underlying infrastructure. The importance of platform engineering is growing due to modern development's demands for reliable, automated, and scalable infrastructure. With the rise of cloud computing, containerization, and microservices, the need for platform engineering has become more pronounced. Companies have realized that a robust platform can significantly speed up development and deployment processes.Responsibilities of platform engineers include:
- Providing infrastructure
- Container orchestration
- Network and service mesh
- Monitoring and scaling
What is the difference between DevOps and platform engineering?
From the definitions provided above, one thing is clear: while both DevOps and platform engineering aim to improve the efficiency and reliability of software development and deployment, they focus on different aspects and operate at different levels. DevOps is about optimizing the entire software delivery pipeline, emphasizing automation, collaboration, and communication. On the other hand, platform engineering is centered on building and maintaining the infrastructure that supports application development. Platform engineers provide tools and services to developers, enabling them to develop, deploy, and operate applications efficiently.What are the advantages of platform engineering?
In 2009, the world began to talk actively about DevOps, focusing on automating processes between developers and operations and improving communication. DevOps emerged from lean manufacturing principles, aiming to optimize processes at all levels. DevOps redefined how processes within companies are structured, introducing tools that automate key development and operations processes, such as Kubernetes. However, the increasing cognitive load led to resistance against adopting DevOps practices, paving the way for platform engineering. Platform engineering accelerates the development process, improves product quality, and reduces costs. The primary goal of platform engineering is to create a robust and versatile platform capable of supporting different development and operational processes. The platform offers developers, operators, and other stakeholders a convenient interface and a set of tools to simplify and accelerate the development, deployment, and maintenance of applications. Transitioning to platform engineering is the next step in the evolution of DevOps.6 key stages of platform engineering implementation
Implementing platform engineering requires close collaboration between developers and operations teams. Each company may have its own methodology, so the stages can vary depending on the project's specifics. Here are the common steps that serve as a guide for building and developing a platform:-
Requirement analysis
-
Architecture design
-
Development and testing
-
Implementation and deployment
-
Support and maintenance
-
Monitoring and optimization
To wrap it up
In this article, we’ve outlined the key differences between DevOps and platform engineering, demonstrated why platform engineering is considered the next step in DevOps evolution, and provided an overview of the six key stages of platform engineering implementation. Understanding and leveraging both DevOps and platform engineering approaches can significantly enhance software development and deployment processes, leading to faster innovation and improved reliability. Based on your business goals and objectives, Kanda Software can help your organization with DevOps and platform engineering. Contact our team today to be the first adopter of innovative trends and best practices in the industry for streamlining your business processes.Related Articles

Comprehensive AI Security Strategies for Modern Enterprises
Over the past few years, AI has gone from a nice-to-have to a must-have across enterprise operations. From automated customer service to predictive analytics, AI technologies now handle sensitive data like never before. A Kiteworks report shows that over 80% of enterprises now use AI systems that access their most critical business information. This adoption…Learn Morearrow-right
Building Trust in AI Agents Through Greater Explainability
We’re watching companies leap from simple automation to an entirely new economy driven by self-governing AI agents. According to Gartner, by 2028 nearly a third of business software will have agentic AI built in, and these agents will be making at least 15% of everyday work decisions on their own. While that can significantly streamline…Learn Morearrow-right
Machine Learning for Fraud Detection: Evolving Strategies for a Digital World
Digital banking and e-commerce have changed how we transact, creating new opportunities for criminals. Businesses lose an estimated $5 trillion to fraud each year. The sheer number of fast-paced digital transactions is too much for older fraud detection methods. These traditional tools are often too slow and inflexible to stop today's automated threats. This new…Learn Morearrow-right
Software Development Life Cycle (SDLC): Helping You Understand Simply and Completely
Software development is a complex and challenging process, requiring more than just writing code. It requires careful planning, problem solving, collaboration across different teams and stakeholders throughout the period of development. Any small error can impact the entire project, but Software Development Life Cycle (SDLC) provides the much needed support to overcome the complexities of…Learn Morearrow-right

