CNCF Welcomes New Silver Members as Global Demand for Cloud Native Infrastructure Grows

2026-06-18 · Source: Cloud Native Computing Foundation · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure, Software Development & Engineering · Depth: Intermediate, short

Summary

The Cloud Native Computing Foundation (CNCF) announced the addition of 14 new Silver Members, Silver End Users, and a Non-Profit Member on June 18, 2026, at KubeCon + CloudNativeCon India. This expansion reflects the increasing global demand for cloud native infrastructure and engagement within the CNCF ecosystem. Jonathan Bryce, CNCF executive director, noted that 98% of organizations have adopted cloud native techniques, establishing it as the global standard for enterprise infrastructure. The new members, including Actualyze AI, Fongcon Technology, and Raydian Cloud, represent diverse sectors like platform engineering, AI infrastructure, managed Kubernetes services, financial technology, and enterprise software, underscoring cloud native technologies' vital role in building and maintaining AI infrastructure.

Key takeaway

For AI Architects and MLOps Engineers scaling cloud native infrastructure, this announcement confirms the industry's strong pivot towards standardized, open-source solutions. Your strategic planning should prioritize integrating CNCF-hosted technologies like Kubernetes for AI workloads, leveraging the growing ecosystem for robust platform engineering. Consider exploring CNCF membership benefits or engaging with new member organizations to access specialized expertise and resources for your enterprise AI deployments.

Key insights

Cloud native adoption is expanding globally, with new CNCF members highlighting its critical role in enterprise infrastructure and AI workloads.

Principles

• 98% of organizations adopt cloud native techniques.
• Cloud native is vital for AI infrastructure.
• Ecosystem growth defines future infrastructure.

In practice

• Implement Kubernetes for AI workloads.
• Utilize managed OpenStack/Ceph/Kubernetes services.
• Build scalable cloud native platforms.

Topics

• Cloud Native Computing Foundation
• Kubernetes
• AI Infrastructure
• Platform Engineering
• Managed Services
• Open-Source

Best for: AI Engineer, MLOps Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by Cloud Native Computing Foundation.