June 9, 2025
In the ever-changing landscape of tooling, process, and management, organizations continuously seek for a balance of many competing goals: delivering business value quickly and maintaining stability, security, and control. This tension has driven many eras of organizational transformations over the decades, each attempting to resolve as many problems as they can for their current goals.
Today, Platform Engineering is the next evolution in this cycle, a pragmatic balance that acknowledges both the need for some specialization and the imperative for developer productivity. In this article, we will explore how we got to this "new" pattern, why previous models fell short, and how this new approach can fix some gaps, but is not the silver bullet to kill all issues.
In the beginning IT organizations were created. This had made many people very angry and has been widely regarded as a bad move -Douglas Adams
The journey from waterfall to platform engineering has been driven by the fundamental tension between business agility and operational control. This evolution is not just about organizational charts reflecting changing business priorities and the recognition that previous models had inherent limitations.
The Waterfall Era prioritized stability over speed through rigid departmental silos.
• Specialized teams (development, operations, security) operated as separate entities
• Limited deployment opportunities required exhaustive upfront planning
• Physical media distribution necessitated complete, error-free software before release
• Business value: predictability and stability at the expense of responsiveness
While waterfall provided stability and clear responsibilities, market pressures eventually demanded faster delivery cycles than this model could support.
Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan – Agile Manifesto
The Agile Revolution responded to market demands for faster delivery by transforming development processes:
• Development teams reorganized around products and features instead of technical components
• Iterative development cycles shortened feedback loops with customers
• Operations, security, and infrastructure remained in traditional silos
• Fundamental problem: Speed improved in development but handoffs to operations became bottlenecks
• Business misalignment: Development viewed as profit center; operations as cost center
Agile dramatically improved development velocity butcreated new integration problems at the boundary between fast-movingdevelopment and stability-focused operations teams.
The DevOps Movement addressed the development-operations divide by unifying responsibility:
• Integration of development and operations through shared practices, tools, and sometimes reorganization
• Key principle: "You build it, you run it" accountability model
• Automation explosion: CI/CD pipelines, infrastructure as code, configuration management
• Technical innovation: Version-controlled infrastructure, automated testing, continuous deployment
• Core tension: Balancing speed with operational stability in the same team
DevOps successfully bridged the dev-ops divide, enabling both increased velocity and operational quality, but introduced an expanding skill set burden on individual teams.
There is no silo only "DevSecFinNetDBTestQAOps"
The Overexpanded DevOps Era pushed the integration model to unsustainable limits:
• Scope creep: Teams expected to master development, operations, security, networking, databases, and more
• Resource inefficiency: Specialized experts spent most of their time underutilized on individual teams
• Duplication: Multiple teams solved identical problems with different tools and approaches
• Technical debt: Solutions built quickly without specialized knowledge created long-term maintenance issues
• Recruiting challenge: "Full-stack DevOps" expertise became nearly impossible to hire for
The "everyone does everything" model created unsustainable cognitive load, expertise shortages, and technical fragmentation across the organization.
“This process is too slow!” she exclaimed, then tried another and declared, “This process is too expensive!” Until finally, she found the perfect one and cheerfully proclaimed, “This platform is just right!” –Goldilocks
Platform Engineering balances specialization with developer productivity:
• Structure: Specialized platform teams build self-service capabilities for development teams
• Key innovation: Treating internal platforms as products with developers as customers
• Technology focus: Self-service portals, API-driven infrastructure, automated compliance guardrails
• Measurement shift: Success measured by developer experience and adoption, not just cost or stability
• Cultural change: From gatekeeping to enablement orientation in specialized teams
Platform Engineering acknowledges that some specialization is necessary but fundamentally reorients specialized teams to serve developer productivity through well-defined interfaces and self-service capabilities.
As we've traced the evolution from Waterfall to Platform Engineering, we've seen organizations continuously adapt their structures and practices to balance competing priorities. But understanding this evolution is only the first step—implementing Platform Engineering successfully requires deliberate focus on several critical factors.