At the recent KubeCon + CloudNativeCon Europe 2024 conference in Paris, experts discussed the growing interest in cloud-native technologies such as Kubernetes to meet the demands of AI. With a record 12,000 attendees and hot topics including platform engineering, data observability, and cloud cost management, it was clear that the intersection of cloud-native technology and AI was a key theme. Open-source projects like OpenTelemetry, Cilium, and Prometheus are gaining momentum as companies look for innovative solutions.
The conference also raised questions about the future of AI compute, with participants discussing challenges such as the dominance of GPUs, security concerns, data management issues, and energy consumption. There was a call for better economics to spread the benefits of AI to more companies, and cloud-native technologies were seen as a way to bring down costs and democratize AI. Kubernetes was highlighted as a tool that could help diversify compute away from scarce and expensive GPUs and make AI more accessible to a wider range of organizations.
Jim Zemlin, executive director of the Linux Foundation, addressed the overlap of KubeCon with Nvidia’s GTC conference and emphasized the need for more open data models in AI to democratize technology. The AI Working Group of the CNCF released a Cloud Native AI white paper outlining the challenges and opportunities in managing data for AI development and deployment. Keynote speakers stressed the importance of Kubernetes and cloud-native infrastructure in supporting AI, especially with the growing demands of large language models and AI inference.
The AI boom has led to an explosion in data, raising concerns about data retention, transportation, security, and costs. Organizations are grappling with the challenge of managing massive amounts of data and the associated costs, particularly as they shift to cloud-native technologies. Companies like Chronosphere are developing tools to help customers monitor and manage their data more efficiently in a cloud-native environment. As AI scales and data continues to grow, the integration of cloud-native technologies like Kubernetes will play a crucial role in addressing these challenges.
At the conference, discussions also focused on the impact of AI on cloud cost management and data observability. Cloud optimization vendors noted an uptick in customer interest as more organizations adopt cloud-native technologies. The surge in AI adoption, coupled with the increasing volume of data, emphasizes the need for innovative solutions in managing data costs and optimizing cloud resources. The integration of AI, cloud-native technologies, and data management is set to reshape how companies design, deploy, and manage their cloud-native solutions in the future.
