By Guest: Saiyam Pathak (LinkedIn)
Company: vCluster Labs
Show Name: To The Point
Topic: Kubernetes, Cloud Native
vCluster is making a bold move into the developer tooling space with the launch of vind, a new tool that combines virtual Kubernetes clusters with the simplicity of Docker. Saiyam Pathak, Head of Developer Relations at vCluster, calls it “a better kind”—and the features suggest he’s not exaggerating. From sleep/wake functionality to out-of-the-box load balancers, vind addresses pain points that have frustrated Kubernetes developers for years.
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vind: Rethinking Local Kubernetes Development
vCluster is launching vind, which Pathak describes as “vCluster in Docker.” The tool creates isolated Kubernetes environments designed specifically for development, testing, and security pipelines. “We are actually going down to the fundamental layer,” Pathak explains, emphasizing vCluster’s commitment to empowering developers at every stage of their workflow.
What makes vind different from existing tools like kind? Pathak outlines several key advantages: the ability to sleep and wake virtual clusters, easy node addition, a built-in UI based on vCluster’s new free tier, and seamless load balancer functionality. “It’s very difficult to make that work with kind—kind of annoying,” he notes, highlighting a common developer frustration that vind solves out of the box.
vind also introduces pull-through cache support and hybrid node capabilities, allowing developers to use their local machines while also attaching EC2 instances via vCluster VPN. This flexibility bridges local development and cloud resources, creating a more versatile development environment.
The Free Tier: Democratizing Enterprise Features
Alongside vind, vCluster is launching a free tier that Pathak describes as “free forever, with limited CPU and GPU capacity.” This tier includes enterprise features previously unavailable in the open-source version, such as private nodes, auto nodes, standalone virtual clusters, and the polished UI that vind leverages.
The strategy is clear: lowering barriers to entry while maintaining a path to enterprise adoption. “The enterprise features are there to drive revenue,” Pathak acknowledges, “but on the community side, we’re doing a lot in the first quarter alone.”
From Developer Workstations to AI Factories
vCluster’s 2026 strategy extends beyond individual developers to address the infrastructure needs of AI factories. Pathak envisions a complete stack approach where organizations can use vCluster “right from the fundamental layer to the enterprise level,” incorporating features like private nodes, auto nodes, standalone clusters, and vCluster VPN.
“We want vCluster to fundamentally change how AI factories think about their architecture,” Pathak states. The vision is a plug-and-play solution that creates production-ready environments for AI infrastructure, addressing the complexity challenges that currently slow AI deployment.
Community-First Philosophy
Throughout the announcement, Pathak emphasizes vCluster’s commitment to the community. “I care about the community, I always listen, and I always want to do more for them,” he says. This philosophy drives the simultaneous launch of both vind and the free tier in Q1 2026, providing developers with professional-grade tools regardless of budget constraints.
The approach reflects a broader strategy: build trust and adoption at the developer level, then provide clear upgrade paths as organizations scale. By solving real pain points—from annoying load balancer configurations to expensive enterprise features—vCluster is positioning itself as a partner for the entire Kubernetes journey.
What This Means for Kubernetes Developers
vind and the vCluster free tier represent more than new product launches. They signal a commitment to making Kubernetes development more accessible and less frustrating. For teams evaluating local Kubernetes solutions, vind offers capabilities that go beyond what existing tools provide, particularly in hybrid cloud scenarios where development environments need to span local and cloud resources.
For organizations building AI infrastructure, vCluster’s vision of production-ready AI factories built on virtual Kubernetes clusters could simplify deployment pipelines and reduce infrastructure complexity.
