Open source has become less of a romantic ideal in the last few years. The narrative that open source is always better, often championed by purists, now competes with a more pragmatic reality. While the AI community continues to release ambitious, often closed, models and tools, and while the very definition of open source evolves, the importance of open source is not fading. It is shifting to the layers that matter most: Kubernetes, observability, platform engineering, networking, and the infrastructure required to make AI work in production. According to CNCF contribution tables, GitHub's Octoverse data, and the Apache Software Foundation's latest annual report, engagement is skyrocketing in these critical areas.
Open source grew up and became dull in the best possible way. It is no longer a fringe movement but the foundation of modern computing.
Control through code
While headlines focus on the latest AI models, open source quietly powers the backend. The Cloud Native Computing Foundation (CNCF) now hosts more than 230 projects with over 300,000 contributors worldwide. Its 2025 survey found that 98% of organizations have adopted cloud-native techniques, and 82% of container users now run Kubernetes in production. GitHub's 2025 Octoverse report tells a similar story from a broader angle: 1.12 billion contributions, more than 180 million developers, and a record 518.7 million merged pull requests. The Apache Software Foundation, though less flashy, remains robust with 9,905 committers across 295 projects and 1,310 software releases in fiscal year 2025.
Who employs all these developers? In 2025, CNCF Devstats show Red Hat leading contribution activity with 194,699 contributions, followed by Microsoft (107,645) and Google (91,158). Independent contributors still matter, taking fourth place with 52,404 contributions, which serves as a reminder that open source hasn't become purely corporate. However, the center of gravity is unmistakable: serious companies now invest heavily in engineers to shape the plumbing their products depend on. The top contributors have remained constant over the past decade, demonstrating their long-term commitment. At the same time, an influx of new contributors signals a growing ecosystem.
This shift changes how we should interpret open source contributions. Many still view them as philanthropy, and open source program offices often encourage contributions because it is the right thing to do or to ingratiate the company into a community. But the reality is different. Open source is now a strategic battleground where vendors try to set defaults, normalize interfaces, and shape the operational assumptions everyone else must live with. In other words, open source has become less about openness for its own sake and more about control. Not proprietary control, but control over the layers where ecosystems harden into standards. Companies investing upstream are not driven by civic virtue; they understand that whoever shapes the substrate usually gains leverage over everything built on top of it.
Who gives, and why?
Take Red Hat. Its continued heavy investment in CNCF is unsurprising because Red Hat's OpenShift is a Kubernetes-centric application platform. Pouring effort into the Kubernetes world is not community service; it is product strategy. This approach fits how Red Hat has long exercised influence, and it is not charity. Fortunately for Kubernetes, Red Hat is not alone. The contributor base is growing and becoming more diverse across thousands of organizations. Kubernetes won because it became too important for any serious infrastructure company to ignore.
Microsoft's position is even more revealing. Once the poster child for open source hostility, Microsoft now ranks second in overall CNCF contributions in 2025. The more interesting signal is where Microsoft and others are investing. OpenTelemetry has become one of the fastest-rising CNCF projects, with a 39% increase in commits in 2025 and a contributor base growing from 1,301 to 1,756 in a single year. This is not charity; it is a land grab around observability standards. Microsoft, Splunk, and other top contributors are helping themselves by standardizing the tools they depend on.
Then there is Cilium, which exemplifies what happens when boring infrastructure stops being boring. Cilium's journey report shows that the number of contributing companies rose 90% after it joined CNCF, from 533 to 1,011, while individual contributors jumped from 1,269 to 4,464. Google, Datadog, and Cloudflare expanded their contributions as the project matured. This is not random. Cilium sits at the intersection of networking, observability, and security—the categories that become mission-critical when workloads become distributed, latency-sensitive, and expensive. AI may drive headlines, but much of the strategic work is happening in projects like Cilium, where infrastructure determines whether AI workloads are governable, visible, and efficient.
Nvidia offers another compelling example. Despite having vast resources, Nvidia has chosen to invest in open source. It ranked 14th in Kubernetes contributions over the past two years, with 5,892 contributions. It also open sourced KAI Scheduler, a Kubernetes-native GPU scheduler from Run:ai, and is a key contributor to Kubeflow. Nvidia is not just selling chips; it is investing in the scheduling, orchestration, and workflow layers that determine how effectively its hardware gets used in real-world AI systems. And it does so through developer communities rather than lump-sum cash payouts.
Nvidia's work is a clear signal of where open source is heading in AI. CNCF reports that 66% of organizations hosting generative AI models now use Kubernetes for some or all inference workloads, explicitly calling Kubernetes the de facto operating system for AI. While CNCF has a vested interest in promoting Kubernetes, the reality is that Kubernetes and Kubeflow are increasingly central to training and inference systems. AI is making open infrastructure more important because few organizations want to build their future on opaque, inescapable infrastructure they cannot inspect or influence.
An essential supporting actor
So is open source increasing in importance? Absolutely, but not in the warm, nostalgic way some still imagine. It is becoming less romantic and more essential. The old story of open source as a fringe alternative or a developer-led morality play was never entirely accurate, and it is not remotely credible now. Open source is where the cloud-native stack gets standardized, where observability gets normalized, where platform engineering gets productized, and where AI infrastructure is increasingly built. The investments by major companies in Kubernetes, OpenTelemetry, Cilium, and other projects underscore this transformation. As AI workloads continue to scale, the need for open, malleable infrastructure will only grow, ensuring that open source remains the foundational control plane for the next era of computing.
Source: InfoWorld News