<ul><li>Kubernetes, nearing its 11th birthday, faces a new world dominated by AI and greater need for standardization.</li><li>At KubeCon + CloudNativeCon Europe, the question of Kubernetes in the AI landscape was central.</li><li>New AI/ML workloads differ significantly from Kubernetes' original design, posing challenges.</li><li>MCP, a rising protocol, is enabling AI models to connect with data sources without unique integrations.</li><li>Solo.io introduces MCP Gateway to streamline integration of AI agents with cloud native apps.</li><li>AI and cloud-native ecosystems are converging, leveraging advanced AI models in applications.</li><li>Kubernetes continues to orchestrate intelligent workloads despite MCP's popularity in AI models.</li><li>Kubernetes AI Toolchain Operator (KAITO) simplifies deployment of AI models in cloud environments.</li><li>Projects within CNCF like Volcano and Kubeflow are driving enterprise interest in AI-related Kubernetes tools.</li><li>Interest in AI agents is growing, with tools like kagent and enterprise AI stack gaining traction in Kubernetes.</li></ul>

Agents, DeepSeek and MCP: Kubernetes adapts to the brave new world of AI

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