Platform Engineering vs DevOps Differences & Comparison

Article Summary

• Platform Engineering and DevOps are not in competition with each other. Rather, they work together, with Platform Engineering providing the infrastructure that makes DevOps practices more effective.
• DevOps is about the cultural collaboration between development and operations, while Platform Engineering is about creating standardized self-service platforms that reduce cognitive load for developers.
• Organizations that have implemented Platform Engineering have reported up to a 60% improvement in developer productivity and deployment frequency.
• The move to Platform Engineering addresses the “DevOps tax”, where developers spend too much time managing infrastructure instead of building features.
• Implementing golden paths through Platform Engineering provides opinionated, well-supported workflows that balance developer freedom with operational stability.

Today’s rapidly changing tech landscape often blurs the line between DevOps and Platform Engineering. While many organizations claim to have mastered DevOps, they are increasingly adopting Platform Engineering practices without fully understanding the difference. This article will clarify the basic differences between these two approaches and show how they can work together to supercharge your development ecosystem.

DevOps is a cultural and operational philosophy that aims to break down silos between development and operations teams. On the other hand, Platform Engineering is a budding discipline that focuses on creating and maintaining internal developer platforms. These platforms are designed to make it easier for development teams to self-serve infrastructure and deployment capabilities. Grasping this difference is critical for organizations looking to optimize their software delivery processes.

The Shift from DevOps to Platform Engineering

Over the last ten years, the software development world has seen significant changes. As companies began to grow their engineering teams and the complexity of cloud infrastructure increased, the shortcomings of traditional DevOps practices started to become apparent. This shift wasn’t a sign of DevOps falling short, but rather a natural progression in the way teams deliver software on a larger scale.

Platform Engineering came into existence when developers began to be bogged down by the increasing complexity of infrastructure, tools, and operational responsibilities. According to Qovery, this trend is a reaction to the “DevOps tax” – the cognitive burden that was placed on developers as infrastructure and operations became code. Platform Engineering is not a replacement for DevOps, but rather represents its evolution into a more sustainable model.

The Transformation of Software Development by DevOps

DevOps has caused a radical shift in software delivery by breaking down barriers between development and operations teams. Prior to DevOps, developers would write code and then “toss it over the fence” to operations, which led to tension, delays, and problems with quality. DevOps brought automation, continuous integration and deployment (CI/CD), infrastructure as code, and a shared responsibility model to the table, which sped up software delivery and enhanced reliability.

The Issues That Surfaced with Scaling

When organizations tried to expand their DevOps implementations, they ran into a number of problems. The task of managing a growing infrastructure became too complex for development teams. The idea of “you build it, you run it” sounded great in theory, but in practice it created bottlenecks because engineers had to balance developing features with operational issues. Different teams using different tools led to inconsistent practices and fragmented knowledge bases. Onboarding new developers also became more difficult.

Many companies found that their developers were dedicating up to 40% of their time to infrastructure issues rather than delivering business value. This inefficiency, combined with the lack of qualified DevOps engineers, created a sustainability issue that required a solution.

Why Many Teams Feel Overwhelmed by DevOps

The “DevOps burden” has become increasingly apparent in organizations that have adopted a pure DevOps approach without evolving their practices. Developers often find themselves overwhelmed by the task of managing infrastructure, security, compliance, and observability in addition to their main job of writing application code. This mental overload reduces productivity and leads to frustration, especially as systems become more complicated.

Yet another obstacle is the spread of tools and workflows that developers are expected to master. A typical developer who is enabled by DevOps might need to be proficient in Docker, Kubernetes, Terraform, multiple CI/CD systems, monitoring solutions, and cloud provider specifics – in addition to their core programming skills. This explosion of tools creates a steep learning curve that affects the speed of the team and creates silos of specialized knowledge.

Understanding the True Meaning of DevOps

In order to better understand the connection between DevOps and Platform Engineering, we first need to clear up any misconceptions about what DevOps really is. At its core, DevOps is about culture and collaboration, not about specific tools or job roles. It’s a mindset that encourages breaking down the walls between development and operations teams to allow for quicker, more dependable software delivery.

DevOps: The Fundamental Concepts

Regardless of how it’s implemented, DevOps is underpinned by a few crucial principles. These include continuous integration and delivery, infrastructure as code, automation, monitoring, and feedback loops. DevOps fosters a sense of shared responsibility, with teams collectively owning both the development and operational results. It encourages a culture of experimentation and learning, where system failures are seen as chances to improve rather than as reasons to point fingers.

DevOps also supports the idea of “shifting left” – incorporating operational considerations earlier in the development process. This method allows for the detection of problems earlier when they’re less expensive to resolve, and it instills operational excellence into applications from the beginning.

Usual DevOps Team Structures

The structure of DevOps teams can differ greatly from one organization to another, but there are some common structures that are often seen. Some companies keep their development and operations teams separate, but they improve their collaboration tools and share responsibilities. Other companies have dedicated DevOps teams that act as a bridge between the development and operations teams. The most advanced organizations often follow a “you build it, you run it” model where cross-functional teams are responsible for the entire application lifecycle, from development to production support.

Every structure has its benefits, but when organizations expand beyond 5-7 teams, coordination problems usually arise. This scaling issue is one of the main reasons for the emergence of Platform Engineering as a discipline.

Typical DevOps Tools and Techniques

DevOps uses a variety of tools and technologies, such as Git for source control, Jenkins and CircleCI for continuous integration, Terraform and CloudFormation for infrastructure as code, Ansible and Chef for configuration management, Docker and Kubernetes for containerization, and Prometheus and Grafana for monitoring. These tools automate the deployment pipeline, provision infrastructure, and perform operational tasks, allowing for quicker and more dependable software delivery.

DevOps practices focus on automation, measurement, and sharing. Automation minimizes manual labor and human mistakes, measurement offers insights for continuous enhancement, and sharing knowledge among teams speeds up learning and avoids silos.

The “Jack of All Trades” Issue

A frequent misunderstanding in the application of DevOps is that each developer needs to be an expert in every operations tool and technique. This “jack of all trades” strategy can result in cognitive overload, particularly as systems become more intricate. Developers are forced to switch between writing application code and dealing with infrastructure issues, which decreases their productivity in both areas.

In larger organizations, the challenge becomes even more significant, where the diversity and complexity of operational requirements can overwhelm development teams. The recognition of this problem has been a significant catalyst for the emergence of Platform Engineering as a specialized discipline.

Platform Engineering: The Newcomer

Platform Engineering is a new field that has come into existence as a solution to the problems that DevOps teams in larger organizations face when they try to scale. It is not a replacement for DevOps principles, but rather a further development of them. The focus of Platform Engineering is on creating standardized self-service capabilities that make operational tasks easier for development teams to handle, much like how platform architecture helps streamline processes.

What it is and Why it’s Important

Platform Engineering involves the creation and design of workflows and toolchains that offer self-service abilities for software engineering teams. Its main goal is to lessen the mental burden on developers by offering reliable operational tools, deployment patterns, and infrastructure through internal developer platforms. These platforms hide the intricacies of the underlying infrastructure while still providing developers with the independence they require.

What sets Platform Engineering apart from traditional DevOps methods is that it views the developer experience as a product, with developers as the customers. Platform teams use product management principles to understand what developers need, create self-service solutions, gather feedback, and constantly improve what they offer.

Understanding Internal Developer Platforms

Internal Developer Platforms (IDPs) are the core output of Platform Engineering. They gather together tools, workflows, and infrastructure capabilities into one unified experience for developers to interact with. Instead of the separate tooling often seen in DevOps environments, IDPs offer a single interface that hides complexity and allows self-service for common tasks.

A good IDP usually has features for setting up environments, deploying applications, visibility, security scans, and compliance checks. It offers templates and best practices that help developers reduce mental effort. The best platforms offer a balance of flexibility and guidelines, so teams can be innovative without having to recreate operational procedures or create security risks.

Advantages of Self-Service Infrastructure

Engineering organizations can reap substantial benefits from transitioning to self-service infrastructure through Platform Engineering. This shift allows developers to independently provision resources and deploy applications, eliminating the need to wait for operations teams and thus significantly reducing lead times and removing bottlenecks. Platform teams can also ensure security and compliance standards are met through the platform itself, which provides consistency without the need for manual reviews for every change. Many organizations have reported increased developer productivity, with some studies showing a reduction of up to 50% in time spent on operational tasks.

5 Essential Differences Between DevOps and Platform Engineering

Although DevOps and Platform Engineering both aim to enhance software delivery and reliability, they differ in their methods, focus, and execution. Comprehending these differences can assist organizations in determining how to effectively incorporate both philosophies. The following main differences illustrate how these approaches can work together rather than in opposition.

1. Focus: Collaboration vs Infrastructure

DevOps is mainly about changing the culture and promoting collaboration between the development and operations teams. The aim is to eliminate organizational barriers and encourage a sense of shared responsibility for both the creation and operation of software. The focus is on practices, attitudes, and communication methods that facilitate faster delivery and improved reliability.

On the other hand, Platform Engineering is all about constructing technical infrastructure and tools that allow development teams to work more productively. It stresses the importance of creating standardized, self-service platforms that remove complexity while promoting best practices. If DevOps tackles the “people problem” of software delivery, Platform Engineering solves the “tooling problem” by creating custom solutions to enhance developer productivity.

2. Team Structure: Embedded vs Centralized

In traditional DevOps models, operational functions are typically integrated within development teams, adhering to the “you build it, you run it” principle. Each team retains accountability for their applications throughout the full lifecycle, including production support and infrastructure management. While this method enhances autonomy, it can result in duplicated work and inconsistent practices among teams.

Usually, Platform Engineering uses a centralized team structure, where dedicated engineers build and maintain shared services that many development teams use. This specialization lets platform engineers concentrate on infrastructure concerns while development teams focus on application logic. The centralized approach encourages consistency and cuts down on duplication, but it needs a lot of attention to the developer experience to prevent becoming a bottleneck.

3. End Users: Customers vs Developers

DevOps practices are ultimately designed to deliver value to end customers by releasing software faster and more reliably. The measures of success include how often deployments occur, how long it takes for changes to happen, and the average time it takes to recover – all of which directly affect the customer experience. DevOps teams primarily optimize their processes to improve these metrics that face the customer.

On the other hand, Platform Engineering views developers as its main customers. Success is gauged by the satisfaction of the developer, decreased cognitive load, and increased engineering productivity. Platform teams use product management principles to understand what developers need, collect feedback, and continuously enhance their offerings to better serve their internal users.

The change in focus doesn’t lessen the significance of the end customers. Instead, it acknowledges that empowering developers eventually results in better customer experiences. Platform Engineering makes developers more productive and reduces operational overhead, allowing more time for innovation and feature development.

4. Tooling Approach: Customized vs Standardized

DevOps implementations usually lead to teams choosing and customizing their own toolchains based on the specific requirements of the project. This freedom fosters innovation and allows teams to optimize for their unique needs. However, it often creates “snowflake” environments that are difficult to maintain and scale. Knowledge becomes compartmentalized as each team develops expertise with their particular tool selections.

Platform Engineering uses a more uniform method, establishing best practices and preferred workflows that lead teams to consistent tools and methods. These uniform solutions integrate organizational best practices and security requirements, which simplifies compliance. Even though some customization options are still available, the platform offers well-supported defaults that are suitable for most use cases.

By standardizing, developers are less likely to experience decision fatigue, and projects are more likely to be consistent. It also makes it easier for new team members to get up to speed because they only need to learn one set of tools and practices.

5. Responsibility Model: Shared vs Specialized

In the traditional DevOps model, responsibility is shared, meaning that development teams are responsible for their applications from the moment they are conceived to when they are in production operations. This “full-stack ownership” model pushes developers to understand operational concerns and participate in on-call rotations. While this approach helps to create well-rounded engineers, it can also lead to a lack of focus and cognitive overload as systems become more complex.

Platform Engineering brings a more specialized responsibility model to the table. The platform teams take the reins of infrastructure, tooling, and operational frameworks, leaving the development teams to focus mainly on application logic and business features. This separation of duties allows each group to develop a deeper understanding of their domain. The platform teams become experts in infrastructure while the development teams can focus on solving business problems without getting mired in operational details.

Although this specialty does not erase the necessity for cooperation, it does necessitate close collaboration to guarantee that platform capabilities meet developer needs. The primary distinction is that operational issues are handled via platform capabilities rather than requiring each development team to independently solve the same problems.

How DevOps and Platform Engineering Complement Each Other

Platform Engineering and DevOps are not in opposition to each other, but rather they complement each other in building effective software delivery organizations. DevOps lays the groundwork in terms of culture and principles that guide how teams work together, while Platform Engineering provides the technical infrastructure that allows these principles to be scaled in complex environments.

Leading companies adopt both philosophies, leveraging DevOps culture to promote teamwork and shared objectives, and utilizing Platform Engineering to offer self-service features that lessen cognitive burden. This integrated approach tackles both the human and technical elements of software delivery.

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A Model of Collaboration

Under the best circumstances, Platform Engineering teams have a close working relationship with development teams, getting to know their workflows and the challenges they face. They use this knowledge to create self-service platforms that encapsulate best practices but are also flexible enough to meet individual needs. Development teams provide feedback and sometimes work together with the Platform Engineering teams to develop features for the platform. This creates a positive feedback loop of ongoing enhancement.

Platform teams and development teams work well together because platform teams view their developer platforms as products that serve internal customers. They perform user research, establish clear service level objectives, and constantly solicit feedback to enhance the developer experience. This allows development teams to be more productive and less burdened by operations, freeing them up to deliver business value. For more insights on platform architecture, check out the comparison between event-driven vs request-response models.

“Platform Engineering doesn’t replace DevOps—it productizes it. It takes the best practices that evolved through years of DevOps culture and packages them into consumable, self-service platforms that make those practices accessible to all developers regardless of their operational expertise.”

Real-World Success Stories

Many large tech organizations have successfully implemented Platform Engineering alongside DevOps practices. Netflix’s platform team built Spinnaker, a continuous delivery platform that standardized deployment practices while still accommodating team-specific workflows. Spotify created Backstage, an open-source developer portal that provides a unified interface for infrastructure, documentation, and tooling. These platforms enable consistent practices without sacrificing team autonomy, demonstrating how Platform Engineering can enhance rather than replace DevOps culture.

Capital One, a financial services firm, revolutionized its software delivery by creating a comprehensive internal platform that cut deployment times from weeks to minutes. The platform included security and compliance requirements as code, ensuring consistency and eliminating manual approval bottlenecks. This strategy preserved the collaborative nature of DevOps while providing scalable solutions for their enterprise environment.

Indications That Your Team Could Benefit from Platform Engineering

There are a number of signs that your organization might be well-served by introducing Platform Engineering to work in tandem with your existing DevOps practices. For example, if your development teams are spending too much time on operational tasks, if inconsistent tooling is leading to the creation of knowledge silos, or if it takes weeks to onboard new developers due to complicated infrastructure, then you could see significant benefits from Platform Engineering. The aim is not to discard DevOps principles, but rather to make them more accessible via well-designed platforms.

Issues with Developer Efficiency

When developers consistently spend over 20% of their time on operational tasks instead of coding, it’s a clear sign that Platform Engineering is needed. This “DevOps tax” shows up when engineers grapple with deployment pipelines, debug infrastructure problems, or wait for environments to be set up. These tasks take focus away from the main development work and decrease total efficiency.

Another sign is high context-switching costs, where developers must mentally shift between application code and infrastructure concerns multiple times daily. This cognitive load leads to decreased focus and quality. Platform Engineering addresses these challenges by providing self-service capabilities that simplify operational tasks and create more consistent experiences.

Discrepancies in Deployment Processes

When each team is left to their own devices to create their own deployment pipeline and infrastructure patterns, it often results in a lack of consistency and a lot of duplicated work within organizations. This type of fragmentation can make it challenging to apply improvements, security standards, or compliance requirements across the entire organization. It also often results in teams coming up with the same solutions over and over again, which leads to a lot of wasted effort and varying levels of quality.

Platform Engineering addresses this issue by implementing standardized deployment procedures and infrastructure models that incorporate the best practices of the organization. These “golden paths” lead teams towards a unified approach while still accommodating the required customization. The resulting standardization enhances the organization’s reliability, security, and efficiency.

Increased Complexity in Infrastructure

With the adoption of new technologies such as cloud-native architectures, Kubernetes, service meshes, etc., the task of managing infrastructure has become increasingly complex. Often, individual development teams do not possess the specialized knowledge required to operate these systems effectively. This can lead to configurations that are not optimal and could potentially pose security risks. When infrastructure complexity starts to become a burden for development teams, it is a clear sign that Platform Engineering could be beneficial.

Scaling Beyond 5+ Teams

Challenge	DevOps Without Platform Engineering	With Platform Engineering
Knowledge Sharing	Ad-hoc, varies between teams	Centralized, documented in platform
Consistency	High variance between teams	Standardized through platform capabilities
Onboarding	Weeks to months	Days to weeks
Security & Compliance	Manual reviews, inconsistent implementation	Built into platform, automated verification

When an organization has more than five development teams, it often becomes difficult to maintain consistency and share knowledge effectively using only DevOps approaches. As the number of teams increases, coordination becomes more difficult and practices tend to diverge. This challenge of scaling is particularly acute in enterprises with dozens or hundreds of development teams, where consistency becomes a business-critical issue.

Platform Engineering delivers a scalable answer by developing shared services and self-service abilities that operate across team limits. These centralized platforms integrate best practices, security needs, and compliance controls, guaranteeing consistency while decreasing coordination overhead. The platform evolves into the main method for scaling DevOps practices throughout the company.

What’s crucial to note is that Platform Engineering tackles the issue of knowledge sharing that often arises in larger companies. Rather than relying on documentation that becomes obsolete quickly or tribal knowledge that vanishes when people leave, Platform Engineering embeds operational knowledge directly into the platform. This method ensures that best practices are available to all teams, regardless of their individual skill levels.

How to Apply Platform Engineering in Your Company

For Platform Engineering to work effectively, it needs to be implemented in a way that balances uniformity with the independence of the team. Instead of constructing the ideal platform in a vacuum, successful companies start off small, concentrate on the experience of the developer, and adapt their platforms according to how they are used in reality. The aim is to develop self-service features that developers are keen to use, rather than rules they have to abide by.

Usually, the process starts by pinpointing the most problematic areas in the current development process. The most common areas to start with include environment provisioning, deployment pipelines, and observability tooling. Tackling these high-impact areas first allows platform teams to show their value quickly and build trust with development teams.

Most successful platform teams work with a product mindset, treating developers as customers, conducting user research to understand pain points, and continuously iterating based on feedback. This ensures the platform solves real problems instead of creating new ones.

Organizations should also consider their cultural readiness for Platform Engineering. Teams that are used to complete autonomy may resist standardization efforts if not properly engaged. Platform initiatives are most successful when they involve development teams in the design process, demonstrating clear benefits instead of imposing solutions from above. This collaborative approach maintains the core DevOps value of cross-team cooperation while creating more scalable solutions.

Begin with Golden Paths

Instead of creating a full platform from the start, successful businesses start with “golden paths” for common workflows. These strong, well-supported patterns guide developers through specific tasks, such as deploying a web service or setting up monitoring. Golden paths reduce cognitive load by providing sensible defaults while still allowing necessary customization. This method provides immediate value while laying the groundwork for more comprehensive platform capabilities.

Creating Your Initial Internal Developer Platform

A successful Internal Developer Platform merges tools, support mechanisms, and documentation to create a seamless developer experience. This usually includes a developer portal that offers a single interface for self-service capabilities, documentation that clarifies the services that are available, and automation that takes care of complex operational tasks. The platform should hide infrastructure complexity while offering enough visibility for troubleshooting. Above all, it should be designed with developer workflows in mind, focusing on the tasks developers do every day instead of operational concerns.

Gauging the Success of Platform Engineering

When it comes to Platform Engineering, success is often measured by a combination of technical metrics and developer experience indicators. Important technical metrics to keep an eye on include how frequently deployments are made, the lead time for changes, and how long it takes to provision an environment. Developer experience can be gauged through things like surveys, the rate at which the platform is adopted, and direct feedback. The most important metric is often “developer toil”, which is the amount of time engineers spend on operational tasks that don’t add value as opposed to developing features. A successful platform should cut down on this toil significantly, while also enabling greater consistency and reliability.

What the Future Holds for Software Delivery

From traditional operations to DevOps and now Platform Engineering, we can see a clear trajectory in the way organizations handle software delivery on a large scale. As systems become more intricate and development teams get bigger, the demand for specialized knowledge in infrastructure and standardized self-service features is becoming more and more obvious. Looking ahead, we can expect to see even more advanced platforms that use AI to decrease cognitive load even further and automate everyday decisions.

Nonetheless, the basic principles of DevOps, such as collaboration, shared responsibility, and continuous improvement, will always be necessary. The most successful organizations will continue to adopt both the cultural elements of DevOps and the technical infrastructure of Platform Engineering, creating environments where developers can focus on innovation while maintaining operational excellence. Instead of choosing between these approaches, forward-thinking companies will incorporate them into a cohesive software delivery strategy that evolves with their needs.

SlickFinch are experts in DevOps, Platform Engineering and in IDPs like Backstage. Book a free consultation with us today if you are struggling with or looking to implement any of these.

Common Questions

There’s often confusion when it comes to understanding the differences between DevOps and Platform Engineering. While both approaches share the same objectives, their implementation methods differ. Here are some frequently asked questions that arise as organizations try to navigate the relationship between the two.

Is DevOps being replaced by Platform Engineering?

DevOps is not being replaced by Platform Engineering, instead, it is being expanded and scaled. DevOps has set essential principles such as collaboration, automation, and shared responsibility that are still fundamental to effective software delivery. Platform Engineering provides the technical infrastructure that makes these principles sustainable as organizations grow.

DevOps should be viewed as the basic cultural and methodological structure, while Platform Engineering is the tooling and infrastructure that allows these practices to be scaled up. Both approaches need to work together in order for organizations to get the best results. The most effective implementations keep the cultural values of DevOps while using Platform Engineering to reduce hard work and standardize common workflows.

Platform Engineering is becoming more important as systems grow in complexity. It helps to maintain the speed and reliability of DevOps without overloading development teams with operational issues. It’s not a replacement, but rather a new way of implementing DevOps principles.

What capabilities do Platform Engineers require in comparison to DevOps Engineers?

Platform Engineers, like DevOps Engineers, require a range of similar technical capabilities such as proficiency in infrastructure as code, containerization, orchestration, and automation. But they also need to have additional skills in product management, user experience design, and API development. Platform Engineers need to comprehend the working of developers and design systems that enhance their workflows instead of hindering them.

DevOps Engineers typically concentrate on constructing pipelines and infrastructure for individual applications, while Platform Engineers devise reusable components and self-service capabilities that are applicable to numerous teams and projects. This wider scope necessitates more robust system design abilities and a more profound comprehension of organizational requirements. To be successful, Platform Engineers must merge technical depth with a consideration for developer experiences, thereby producing solutions that strike a balance between standardization and adaptability.

What is the price of Platform Engineering implementation?

The price of Platform Engineering implementation varies depending on the size, complexity, and existing infrastructure of the organization. Small organizations might start with a dedicated team of 2-3 engineers focusing on the most critical developer workflows, while larger enterprises often invest in larger platform teams of 8-12 specialists. Beyond personnel costs, organizations should consider the cost of tools, training, and the initial productivity impact of transitioning workflows.

Although the initial cost can be quite high, companies usually experience benefits in the form of enhanced developer efficiency, fewer incidents, and quicker onboarding. Research indicates that successful Platform Engineering applications can lower operational costs by 20-30% and speed up deployment rates by 2-3 times. These improvements in efficiency often make the investment worthwhile, particularly for companies with over five development teams.

Is Platform Engineering Beneficial for Small Teams?

Platform Engineering can be beneficial for small teams as well, although the way it is implemented may differ from larger organizations. Small teams should focus on easy-to-use solutions that standardize their most difficult workflows without creating a lot of maintenance work. This could include using managed services, implementing basic self-service capabilities for common tasks, or creating simplified golden paths for deployment and environment management.

What is the timeline for creating an internal developer platform?

Creating an internal developer platform is more of an ongoing process rather than a single project. Most companies start seeing initial results within 3-6 months by focusing on workflows with high impact like deployment pipelines or environment provisioning. More extensive platforms that cover the complete software lifecycle can take 12-18 months to fully mature.

Implementations that are most successful use a step-by-step approach, delivering valuable capabilities early on and expanding based on feedback from developers. This iterative strategy enables organizations to experience benefits quickly while refining their understanding of what developers need. Instead of striving for a perfect platform from the get-go, successful teams concentrate on resolving specific pain points and gradually expanding the capabilities of their platform.

Instead of starting from square one, a lot of companies choose to combine their existing tools to create a seamless developer experience. This method speeds up the time-to-value and lets teams make use of their current investments while they gradually shift towards a more all-inclusive platform strategy.

Keep in mind that platform development is never really “finished” – as technologies advance and organizational needs shift, the platform must continually adapt to stay relevant.