DevOps was supposed to change everything. Break down silos. Get developers and operations working together. Ship code continuously at scale. And you know what? The technical side actually worked. CI/CD pipelines are everywhere now. Infrastructure as code is standard practice. Automated deployments are the norm.
But the cultural transformation? The bit that was supposed to be the whole point? That failed. This article examines why DevOps failed as a cultural movement, part of our comprehensive exploration of the death of DevOps and the rise of platform engineering.
Werner Vogels’ “you build it you run it” philosophy—the one he introduced at Amazon back in 2006—created massive cognitive overload when everyone tried to copy it. We’re seeing 83% developer burnout rates. Senior engineers spending 30-40% of their time on infrastructure work instead of building things. Observability costs eating up 20-30% of infrastructure budgets.
At DevOpsDays NYC 2023, Charity Majors—CTO of Honeycomb and a longtime DevOps advocate—declared we’ve entered the “post-DevOps era.” She wasn’t saying DevOps was useless. She was recognising that the movement has moved on from its original cultural promises. Platform engineering has emerged as the fix, bringing in dedicated platform teams and internal developer platforms to fill the gaps DevOps left behind.
What Was DevOps Supposed to Solve?
DevOps emerged to kill the “throw it over the wall” model. You know the one—developers build software, then chuck it to operations teams who have to deploy and maintain it. The movement promised cultural transformation: shared responsibility, genuine collaboration, breaking down those organisational silos.
Before DevOps, the wall between dev and ops created predictable dysfunction. Developers built features without understanding production constraints. Operations teams maintained systems without development context. When code was “finished,” developers handed it off to operations, who then struggled with deployment issues and had no developer support to fix them. The result? A toxic blame cycle. “It worked in dev” versus “you built it wrong.”
The business pain was real. Quarterly or monthly releases were common. Change failure rates were high. Mean time to recovery was measured in days or weeks. DevOps promised that if everyone shared responsibility for the entire application lifecycle, collaboration would naturally follow.
Early success stories from Amazon, Netflix, and Etsy showed that rapid deployment through DevOps practices actually worked. These companies shipped code dozens or hundreds of times daily while traditional enterprises struggled with quarterly releases. What wasn’t immediately obvious was how much structural support these successful companies had built to make the cultural transformation work.
Werner Vogels and the Birth of “You Build It You Run It”
Amazon CTO Werner Vogels introduced the “you build it you run it” philosophy in 2006 as Amazon transitioned to service-oriented architecture. The core principle was new for its time: development teams would be responsible for the entire application lifecycle—production operations, on-call duties, incident response, the lot. Vogels’ reasoning was compelling. Ownership creates accountability. Developers write better code when they experience production pain directly.
The context, however, mattered. Amazon in 2006 had over 10,000 employees, mature infrastructure processes, and was deliberately architecting around service boundaries. Amazon had dedicated infrastructure teams. Mature tooling. They specifically hired for operational capability within development teams. Teams at Amazon owned specific services end-to-end, but they weren’t building the platform those services ran on.
The philosophy spread like wildfire throughout the industry. It became a DevOps mantra. But it spread without Amazon’s supporting structure. What smaller companies missed was that platform teams, infrastructure specialists, and operational expertise all stayed at Amazon. Only the philosophy got exported.
The unintended consequence? “You build it you run it” became interpreted as “everyone does everything” rather than “teams own services within a supported platform.” The assumption that all developers could and should acquire operations expertise while maintaining feature development velocity proved unrealistic. This philosophy, brilliant in its original context, became a recipe for cognitive overload when applied universally.
The DevOps Movement: Cultural Promises and Technical Wins
The DevOps movement exploded from 2008-2015, emphasising cultural transformation over specific tools or technologies. The CAMS framework—Culture, Automation, Measurement, and Sharing—articulated the core principles. Early DevOpsDays conferences, starting with Patrick Debois’ 2009 event, focused on breaking down silos, building empathy between teams, implementing blameless post-mortems, and establishing shared goals.
Industry adoption accelerated rapidly. Fortune 500 companies launched “DevOps transformations.” The tool ecosystem exploded. Jenkins for continuous integration. Docker for containerisation. Kubernetes for orchestration. Terraform for infrastructure as code. And countless monitoring solutions.
Yet mixed signals emerged almost immediately. The community mantra insisted “DevOps is a culture, not a role,” even as thousands of “DevOps Engineer” job postings flooded the market. Companies adopted the tools and renamed roles while organisational culture remained largely unchanged.
Technical practices were adopted widely and successfully. CI/CD pipelines became standard. Infrastructure as code brought version control and reproducibility to infrastructure management. These technical wins proved that DevOps practices worked. Cultural transformation, however, proved dramatically harder. Collaboration doesn’t emerge automatically from distributed responsibility. Shared ownership without structural support creates confusion rather than empowerment.
Where DevOps Succeeded: Automation and CI/CD
DevOps’ technical practices changed software delivery in ways that are now so standard we take them for granted. The DORA (DevOps Research and Assessment) research program validated these improvements with actual numbers. High-performing teams now deploy multiple times daily versus the quarterly releases common before DevOps.
CI/CD adoption transformed delivery pipelines. Jenkins, GitLab CI, GitHub Actions, and CircleCI enabled automated build, test, and deploy workflows that caught errors early and deployed reliably. Infrastructure as Code through Terraform, CloudFormation, and Pulumi brought version control and reproducibility to infrastructure, eliminating the “snowflake server” problem.
The container movement, led by Docker and orchestrated by Kubernetes, standardised application packaging and deployment. Monitoring and observability advanced with Prometheus, Grafana, and the ELK stack making system observability accessible to organisations of all sizes.
DORA metrics provided objective performance measurement through four key measures: deployment frequency, lead time for changes, change failure rate, and time to restore service. Elite performers achieved impressive results. Lead time for changes under one hour. Change failure rates below 15%. Deployment frequencies measured in deployments per day rather than per quarter.
Here’s the thing though—these technical practices could be decoupled from cultural transformation. Teams could adopt CI/CD and infrastructure as code without fundamentally changing organisational culture or team structure. This turned out to be both DevOps’ strength and a warning sign. The technical wins were real and achievable, but they didn’t automatically deliver the promised cultural benefits.
Where DevOps Failed: Cognitive Load Without Support
DevOps’ cultural failure stemmed from distributing operational responsibility without providing structural support for the resulting cognitive load. Developers were expected to master an overwhelming array of skills: application code, infrastructure configuration, CI/CD pipeline management, monitoring and observability, security practices, and on-call incident response. Industry research found that the average developer navigates 7.4 different tools in their daily workflow. That’s an overwhelming cognitive burden that contributed to widespread developer burnout and cognitive load in the DevOps era.
Cognitive load—the mental effort required to understand and navigate complex systems—became unsustainable. Developers context-switched constantly between GitHub for code, Jira for project management, Jenkins for builds, Kubernetes for deployment, Terraform for infrastructure, Datadog for monitoring, PagerDuty for incidents, and Slack for coordination. Research on context switching shows it takes an average of 23 minutes to regain focus after an interruption.
Responsibility sprawl compounded the tool sprawl problem. Individual developers were expected to handle feature development, code review, infrastructure management, deployment, monitoring, on-call rotation, and security patching. Junior developers were expected to understand production systems from day one. Senior developers spent increasing amounts of time on infrastructure tasks rather than architecture and mentorship.
The expertise dilution problem became apparent. “Everyone does DevOps” meant no one had deep expertise in any specific area. New developers faced months of onboarding to understand the tool chain before they could contribute meaningful features.
Shadow operations emerged as an informal practice where experienced engineers took on infrastructure tasks to help overwhelmed teammates. This revealed that infrastructure expertise naturally concentrates and specialisation cannot be eliminated through cultural mandate alone. Companies distributed responsibility without providing the structural support that made it sustainable. There were no dedicated platform teams building self-service tooling. No infrastructure specialists focusing on developer experience. Every team reinvented infrastructure solutions because no one was responsible for paving the road everyone travelled.
Charity Majors and the Post-DevOps Era Declaration
At DevOpsDays NYC 2023, Charity Majors—CTO of Honeycomb and longtime DevOps advocate—declared that we’ve entered the “post-DevOps era.” The declaration was notable both for its content and its source. DevOpsDays conferences are where DevOps originated. Patrick Debois’ 2009 event in Ghent coined the term and launched the movement. For Majors, a prominent voice in the DevOps community and expert in observability, to frame the moment as “post-DevOps” signalled fundamental shift rather than mere tactical adjustment.
Majors was careful with her language. She avoided “DevOps is dead” clickbait while acknowledging that the movement had evolved beyond its original cultural promises. The “post-DevOps era” framing acknowledged what worked—automation, CI/CD, infrastructure as code—while recognising what failed: distributed responsibility creating burnout, cognitive overload, and shadow operations.
The message resonated with engineering leaders experiencing DevOps transformation fatigue. Many had invested years in DevOps cultural change only to see persistent burnout, on-call stress, and underwhelming collaboration improvements. Majors’ declaration gave these leaders permission to acknowledge DevOps shortcomings without admitting complete failure.
Her perspective from Honeycomb provided insight into another DevOps pain point. Honeycomb’s customers were struggling with tool complexity and observability costs consuming 20-30% of infrastructure budgets. The observability explosion that DevOps enabled had become its own burden.
The timing coincided with Gartner’s prediction that 90% of organisations would adopt platform engineering by 2025. Platform engineering was positioned as DevOps’ structural evolution—a way to preserve the technical wins while addressing the cultural gaps. The “post-DevOps” framing suggested evolution rather than revolution.
Majors explicitly acknowledged that “you build it you run it” had created unsustainable on-call culture for many organisations. The always-on expectation, the cognitive burden of full-stack ownership, and the interruption-driven work pattern had burned out a generation of developers.
Platform Engineering as DevOps’ Structural Evolution
Platform engineering addresses DevOps’ structural gaps through dedicated teams building internal developer platforms (IDPs) that provide self-service capabilities without requiring deep infrastructure expertise. The key difference is structural. Platform teams provide golden paths—pre-configured workflows that make the right way the easy way—rather than distributing infrastructure responsibility to all developers.
An Internal Developer Platform is a curated set of tools, workflows, and interfaces that abstract infrastructure complexity. Instead of expecting every developer to master Kubernetes, Terraform, and observability platforms, the platform team builds interfaces that let developers deploy applications, provision databases, and set up monitoring through self-service workflows with appropriate guardrails.
The golden path concept is central to platform engineering. It’s the “path of least resistance” for common tasks. Deploying an application. Provisioning a database. Setting up monitoring. Implementing authentication. The platform team optimises this path, documents it, and makes it easier than doing things the hard way.
Structurally, platform engineering introduces dedicated teams—typically 5-7 platform engineers supporting 50-100 developers. These platform engineers are responsible for building self-service tools, maintaining CI/CD infrastructure, creating documentation, and supporting developers. This is a fundamentally different model from DevOps’ distributed responsibility.
The developer experience focus differentiates platform engineering from traditional operations teams. Platform engineers measure success by developer productivity, onboarding time, and deployment frequency rather than uptime alone. The goal is reducing cognitive load and enabling developers to focus on feature development.
Platform engineering builds on DevOps technical wins. The CI/CD pipelines, infrastructure as code, containerisation, and observability practices that DevOps established become the foundation that platform teams build on and abstract. Rather than every developer managing Kubernetes manifests, the platform team provides deployment templates that generate properly configured manifests based on simple inputs.
Gartner’s prediction that 90% of organisations will adopt platform engineering by 2025 suggests industry-wide recognition that DevOps’ cultural model needs structural support. The companies succeeding with DevOps often unknowingly practised platform engineering—they had dedicated platform teams even if they didn’t use that term.
Wrapping it all up
DevOps succeeded technically but failed culturally because cultural change requires structural transformation, not just philosophical commitment. The movement’s technical legacy—CI/CD, infrastructure as code, automation, observability—fundamentally improved how software is built and deployed. But the cultural promise that distributing operational responsibility would create collaboration and shared ownership? That failed when applied without structural support.
Werner Vogels’ “you build it you run it” philosophy worked at Amazon because Amazon built supporting structures: platform teams, mature tooling, clear service boundaries, and hiring for operational capability. When exported to smaller organisations without this context, the philosophy created cognitive overload, shadow operations, and burnout rather than empowerment.
The post-DevOps era that Charity Majors articulated recognises this gap. Platform engineering addresses it structurally by introducing dedicated teams focused on developer experience, self-service tooling, and golden paths. This isn’t abandoning DevOps. It’s evolving it based on 20 years of experience.
Understanding why DevOps failed culturally helps avoid repeating the mistake in platform engineering. Cultural change without structural support fails. Distributed responsibility without dedicated expertise creates shadow operations. Tool adoption without workflow simplification increases cognitive load.
The path forward learns from DevOps while evolving beyond it. Preserve the technical wins. Acknowledge the cultural gaps. Build the structural support—platform teams, golden paths, internal developer platforms—that makes “you build it you run it” sustainable rather than a recipe for burnout. That’s the post-DevOps era: the evolution of DevOps into something more complete.
