On Sportswear Achieves Rapid Cloud Migration to Google Cloud Using AI Agents

Google Cloud and premium sportswear brand On have announced a significant achievement in cloud migration, with On successfully moving 24 core services to Google Cloud. What makes this particularly noteworthy is the speed and efficiency of the migration, which was accomplished in weeks rather than the typical months per service, all by leveraging AI agents. A small internal team at On managed 15 of these migrations in-house, experiencing less than five minutes of planned downtime per service. This consolidation onto Google Cloud is intended to establish a robust foundation for modernizing data platforms and deploying Gemini, Google's AI models. This development is highly significant for practitioners in cloud and DevOps. It showcases a tangible example of how AI can fundamentally transform the traditionally time-consuming and complex process of cloud migration. The ability to use AI agents to map dependencies, generate configurations, and automate tasks drastically reduces the manual effort and potential for human error. For organizations grappling with large-scale migrations, this agent-led approach offers a compelling model for accelerating their timelines, minimizing disruption, and freeing up engineering resources for more strategic work. The success of an internal team handling these migrations further highlights the potential for democratizing advanced migration capabilities within an organization. This move by On aligns with a broader, well-established trend in cloud migration, where the focus is shifting from simple 'lift-and-shift' to more intelligent, platform-centric modernization. The increasing demand for AI-driven applications and data-intensive workloads is accelerating cloud investments, requiring GPU-ready infrastructure and scalable data platforms. Cloud migration in 2026 is no longer just about moving infrastructure; it's about engineering a platform for business operations. Google Cloud itself has been actively enhancing its modernization portfolio with AI agents, bringing together existing tools like Migration Center and new agentic capabilities for infrastructure assessment, platform modernization, and application modernization under the 'Google Cloud Modernize' umbrella. This includes tools like the EKS-to-GKE Migration Agent for Kubernetes workloads and Gemini capabilities in Migration Center for TCO projections. This indicates a clear industry-wide push towards leveraging AI to streamline and optimize cloud transitions. In practice, this means that practitioners should actively explore and experiment with AI-powered migration tools and services offered by cloud providers. The success of On suggests that these tools are maturing rapidly and can deliver significant benefits. Organizations should consider pilot projects using agent-led approaches for specific workloads to understand their capabilities and limitations. It also underscores the importance of a well-defined cloud migration strategy that goes beyond just technical execution, considering business outcomes, cost optimization (FinOps), and the long-term operating model. While the promise of AI-driven migration is compelling, human oversight remains critical to ensure accountability and validate decisions made by AI agents. The trade-off between fully automated migration and human-in-the-loop validation will be a key consideration for practitioners as these technologies evolve.