In the fast-paced realm of IT, platform engineers are facing a pivotal moment in their evolution. What once stemmed from DevOps has now blossomed into a distinct discipline with an array of new responsibilities. Today’s platform engineers are not just tasked with managing intricate cloud-native environments; they are also being called upon to lay the groundwork for Artificial Intelligence (AI) across organizations. This means that building AI-ready infrastructure has become a cornerstone of their role.
The landscape is rapidly changing, and platform engineers must adapt accordingly. The shift towards incorporating AI into business operations is not just a trend but a strategic imperative. According to Gartner, a leading research and advisory company, the future of platform engineering is clear. By 2026, a staggering 80% of large software engineering organizations will have dedicated platform engineering teams. These teams will serve as internal providers of reusable services, components, and tools for application delivery—an increase from 45% in 2022.
The impact of this shift will be profound. By 2027, Gartner predicts that platform engineering’s widespread adoption will significantly influence the decision-making processes of infrastructure and operations teams. More than half of their technology choices will be guided by the principles and practices established by platform engineers. This underscores the critical role that building AI-ready infrastructure plays in shaping the future of technology within organizations.
So, what does it mean to build AI-ready infrastructure as a platform engineer? It involves more than just setting up servers and networks—it’s about creating a robust foundation that can support the unique demands of AI workloads. This includes optimizing storage solutions for handling vast amounts of data, implementing scalable computing resources to accommodate intensive processing tasks, and ensuring seamless integration with AI frameworks and tools.
Moreover, building AI-ready infrastructure requires a deep understanding of AI technologies and their implications for the organization. Platform engineers need to stay abreast of the latest advancements in AI and machine learning to design infrastructure that can harness the full potential of these technologies. By aligning infrastructure with AI requirements, organizations can unlock new opportunities for innovation, efficiency, and growth.
In practical terms, this could mean deploying high-performance computing clusters for training AI models, leveraging containerization and orchestration tools for seamless deployment and management of AI applications, and implementing robust monitoring and security measures to safeguard AI systems. By building infrastructure that is agile, scalable, and AI-ready, platform engineers can empower organizations to harness the transformative power of AI.
In conclusion, the role of today’s platform engineer is evolving rapidly, driven by the need to build AI-ready infrastructure. As organizations increasingly embrace AI technologies, platform engineers play a crucial role in designing and implementing the foundational infrastructure that supports these innovations. By staying ahead of the curve, embracing new technologies, and reimagining traditional approaches to infrastructure, platform engineers can position their organizations for success in the AI-powered future.