Open source has become less of a standalone movement and more of a quiet, essential layer powering modern technology. In the last few years, the buzz around open source has shifted from idealism to pragmatism, as the AI community releases ambitious models and tools—many of which are closed rather than open. But this doesn't mean open source is fading. Far from it. As evidenced by contributions to the Cloud Native Computing Foundation (CNCF), GitHub's Octoverse data, and the Apache Software Foundation's annual reports, open source engagement is now concentrated in the layers that matter most: Kubernetes, observability, platform engineering, networking, and the infrastructure required to make AI work in production.

Open source has matured. It's become the unglamorous but indispensable substrate upon which modern digital systems are built. And that's exactly why it's more important than ever.

Control through code

While headlines are dominated by news of the latest AI models, open source continues quietly chugging away in the background. The CNCF now hosts more than 230 projects with over 300,000 contributors worldwide. Its 2025 survey found that 98 percent of organizations have adopted cloud-native techniques, and 82 percent of container users now run Kubernetes in production. GitHub's 2025 Octoverse report paints an even broader picture: 1.12 billion contributions, more than 180 million developers, and a record 518.7 million merged pull requests. The Apache Software Foundation may be less flashy, but it's hardly withering—with 9,905 committers across 295 projects and 1,310 software releases in fiscal year 2025.

Who employs all these developers? According to CNCF Devstats, in 2025 Red Hat led all CNCF contribution activity with 194,699 contributions. Second place went to Microsoft with 107,645, and third to Google with 91,158. Independent contributors still mattered, landing fourth at 52,404—a useful reminder that open source hasn't become purely corporate. But the center of gravity is unmistakable. Serious companies are spending serious money for engineers to shape the plumbing their products depend on. The top contributors have remained remarkably consistent over the past decade, indicating a willingness to invest in the long game, even as an influx of new contributors has also emerged.

That shift changes how we should interpret open source contributions. Too many people still talk about them as if they were mostly philanthropy. Too many open source program offices still try to convince engineering teams to contribute because it's the right thing to do, hoping their developers' efforts will ingratiate the company into some nebulous community. But the reality is different. Open source is increasingly 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 exactly, but control over the layers where ecosystems harden into standards. The companies investing upstream aren't doing it because they've discovered civic virtue. They're doing it because whoever shapes the substrate usually gets leverage over everything built on top of it.

Who gives, and why?

Consider Red Hat. It remains the heavyweight in CNCF, and the reason is straightforward. Red Hat's OpenShift is a Kubernetes-centric application platform, so of course the company continues to pour effort into the Kubernetes world. That's not community service; it's product strategy. It fits the way Red Hat has long exercised influence and control. Fortunately for Kubernetes, Red Hat isn't alone. The stats point to a growing, increasingly diverse contributor base across thousands of organizations. Kubernetes won because it became too important for any serious infrastructure company to ignore, and Red Hat contributes heavily because its business depends on that remaining true.

Microsoft's position is even more revealing. Once the company most associated with open source hostility, it now sits second in overall CNCF contributions in 2025. The more interesting signal is where companies like Microsoft are investing. OpenTelemetry has become one of the fastest-rising CNCF projects, with a 39 percent increase in commits in 2025 and a contributor base that grew from 1,301 to 1,756 in a single year. This isn't about charity either—it's more like a land grab around observability standards. Microsoft, Splunk, and other top OpenTelemetry contributors are all helping in order to help themselves. That's the way open source has always worked, and it's not a bad thing.

Then there's Cilium, which exemplifies what happens when boring infrastructure stops being boring. Cilium's journey report shows that the number of contributing companies rose 90 percent after it joined CNCF—from 533 to 1,011—while individual contributors jumped from 1,269 to 4,464. Google, Datadog, and Cloudflare all expanded their contributions as the project matured. This is not random. Cilium sits at the intersection of networking, observability, and security—precisely the categories that become mission-critical once workloads become distributed, latency-sensitive, and expensive. AI may be driving headlines, but much of the real strategic work is happening in projects like Cilium, where the infrastructure determines whether those AI workloads are governable, visible, and efficient.

And what about Nvidia? The company has so much cash it could buy a few countries and set all their developers to work building for Nvidia. But that's not how Nvidia has chosen to spend its riches. It ranked 14th in Kubernetes contributions over the past two years, with 5,892 contributions. It has also open-sourced KAI Scheduler, a Kubernetes-native GPU scheduler that came out of Run:ai, and has described itself as a key contributor to Kubeflow. In other words, Nvidia isn't just selling chips; it's investing in the scheduling, orchestration, and workflow layers that determine how effectively those chips get used in real-world AI systems. And it's doing so through developer communities rather than lump-sum cash payouts.

Nvidia's work is a tell for where open source is going in AI. CNCF reports that 66 percent of organizations hosting generative AI models now use Kubernetes for some or all inference workloads, and it explicitly calls Kubernetes the de facto operating system for AI. Of course the foundation would say that, given its dependence on Kubernetes as a tentpole project, but that doesn't diminish the reality that Kubernetes and Kubeflow are increasingly central to training and inference systems. In sum, AI is making open infrastructure more important because few organizations want to build their future on opaque, inescapable infrastructure they can't inspect or influence.

An essential supporting actor

So is open source increasing in importance? Absolutely, but not in the warm, nostalgic way some people still imagine. It's becoming less romantic and more essential. The old story about open source as a fringe alternative or a developer-led morality play was never entirely accurate, but it's not even 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 being built. It's the quiet engine driving the AI revolution, and its influence will only grow as organizations demand more control, visibility, and efficiency from their systems.

Source: InfoWorld News