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Einstein Had E=MC²; We Have OSS=(MC)²

Proposal status is Rejected
Session Description

Einstein gave us E=MC². We discovered OSS=(MC)² - where Open Source Software emerges from Multi-Cloud Multi-Cluster capabilities squared.

Most teams are trapped in single-cloud architectures, paying premium prices for basic portability. Meanwhile, the cloud giants enjoy unlimited infrastructure flexibility because they built their own platforms. But what if that same capability was democratically available?

Using CAPI for cluster provisioning, Sveltos for day-2 operations, and a carefully assembled stack of CNCF projects, we built Multi-Cloud Multi-Cluster infrastructure that deploys anywhere—AWS, Azure, bare metal, your laptop—with identical workflows.

This talk covers the technical architecture, deployment patterns, and the physics of why (MC)² only becomes a reality when powered by open source.

Key Takeaways

The (MC)² approach demonstrates how CNCF projects can be composed into enterprise-grade infrastructure platforms. By documenting both successes and failures, we accelerate adoption of tools like CAPI, Sveltos, and the broader cloud-native ecosystem.

Teams gain infrastructure portability without vendor premium pricing. The open source multiplier effect means improvements benefit everyone—bug fixes, feature additions, and operational knowledge become community assets rather than proprietary secrets.

This blueprint enables smaller teams to build infrastructure capabilities previously available only to large enterprises. Every implementation strengthens the open source infrastructure ecosystem and proves that vendor independence is achievable through community collaboration.

The real equation: better tools for everyone = stronger open source community = genuine infrastructure freedom.

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Speakers

Bharath Nallapeta
Bharath Nallapeta Senior Software Engineer | Mirantis Inc

Bharath Nallapeta is a seasoned Kubernetes and cloud-native technology expert with a deep passion for AI and its integration with modern infrastructure. With extensive experience in designing and optimizing Kubernetes-based AI/ML deployments, he has contributed to open-source projects and enterprise-grade cloud solutions. Bharath actively works on bridging AI and Kubernetes, enabling scalable, automated AI workloads that maximize efficiency and performance in cloud-native environments.