Platform engineering has become a central operating layer for many enterprises as organizations consolidate infrastructure, security and data services into shared internal platforms.
As companies standardize cloud operations and internal developer environments, platforms are increasingly expected to improve delivery speed, enforce governance and reduce operational risk across teams.
Yet many platform initiatives stall even after significant investment in modern tooling. In practice, adoption problems are often rooted in organizational dynamics—how teams collaborate, how tradeoffs are communicated and whether internal users see clear value in changing how they work.
Yasmin Rajabi, COO at CloudBolt, says the biggest obstacles to platform success are rarely technical.
“A lack of trust in the tooling, along with fear of losing control or being forced to slow down—especially when decentralized teams have had easy access to infrastructure at their fingertips—creates resistance,” Rajabi says. “If the platform feels like a speed bump, or even worse a risk to deployment, teams will find a way around it.”
That behavior is increasingly visible as platform teams attempt to standardize deployment pipelines, security controls and infrastructure provisioning.
Driving Scalable Adoption
While self-service portals and automation frameworks are designed to simplify access to cloud and infrastructure services, Rajabi says adoption depends on whether developers believe the platform improves their day-to-day work.
“Platform teams need to quickly demonstrate how they will reduce toil for their end users to drive adoption in a scalable way,” she says.
Reducing toil—manual, repetitive work such as provisioning environments, managing access and resolving routine infrastructure issues—has become one of the most practical ways platform teams can build internal credibility.
Without that improvement, developers often bypass official workflows through direct cloud access, scripts or alternative tools.
Rajabi says trust also depends on creating a shared language between platform teams and the application teams they support.
“Tradeoffs need to be explicit and repeatable, with options encoded so teams have flexibility of choice while still avoiding a wild west approach to infrastructure,” she says. “Transparency into those options—especially around cost and speed—is necessary to build trust in the platform.”
In practice, that means exposing the implications of platform choices directly inside workflows—for example, surfacing how environment size, region selection or deployment models affect cost and performance—rather than relying on policy documents or separate financial reports.
Rajabi argues that this transparency is far more effective when platform teams adopt a product mindset instead of treating the platform as an internal infrastructure project.
“Platform teams are most successful when they adopt a product mindset; without it, they will fail,” she says. “A platform can’t exist for its own sake; it exists because end users need it and choose to use it.”
Speed to Deliver Working Services
For platform engineers, this shifts success away from the number of tools integrated or features delivered and toward user experience and time to value—the speed at which developers can deliver working services using the platform.
“That means delivering capabilities that are critical to developers, with a strong focus on user experience and time to value,” Rajabi says.
Organizational misalignment often appears when platform roadmaps are driven primarily by technology modernization rather than business priorities. Rajabi says platform leaders must anchor decisions in business constraints from the outset.
“Start with the business constraints,” she says. “The goal isn’t to build a platform with all the bells and whistles, but to align with the business needs and realities of the organization.”
That alignment requires platforms to support revenue growth, operational efficiency and reliability—not simply internal standardization.
“If the platform can’t enable revenue-driving initiatives, improve margins, or reduce the risk of downtime, it won’t become part of the critical path,” Rajabi says.
Measuring Adoption, Operational Impact
As platform engineering becomes more tightly connected to security, compliance and cost governance, measuring success also needs to move beyond delivery milestones and tooling checklists. Rajabi points to adoption and operational impact as the most meaningful indicators.
“The most obvious metric is adoption: what percentage of the organization is using the platform, and what percentage of workloads operate on—or because of—the platform,” she says.
She also emphasizes onboarding speed and efficiency trends.
“How long does it take to onboard?” Rajabi says. “What is the impact on costs and efficiency from using the platform, and how are these metrics trending over time?”
For organizations treating platform engineering as a strategic capability, Rajabi’s view is that sustained success depends less on the tools selected and more on whether teams build trust, communicate tradeoffs clearly and treat the platform as a product tied directly to business outcomes.