OpenAI’s outage revealed what happens when etcd breaks at scale. This post explains why sharding isn’t enough, and how vCluster offloads API load with virtual control planes. Benchmark included.

Can you really save millions on Kubernetes infrastructure without compromising performance? Yes, with vCluster. In this blog, we break down how virtual clusters reduce control plane overhead, unlock higher node utilization, and simplify multi-tenancy, all while maintaining lightning-fast performance.

Running multiple tenants on a single Kubernetes cluster can be complex and risky. In this post, Liquid Reply explores how vCluster offers a secure and cost-efficient solution by isolating workloads through lightweight virtual clusters.

Shared clusters are cost-effective, but when it comes to building and testing Kubernetes controllers, they create bottlenecks, from CRD conflicts to governance issues. This blog breaks down the trade-offs between shared, local, and dedicated clusters and introduces virtual clusters as the scalable solution for platform teams.

As AI and ML workloads scale rapidly, GPUs have become essential, and expensive resources. But most teams underutilize them. This blog dives into how GPU sharing in Kubernetes can help platform teams increase efficiency, cut costs, and better support AI infrastructure.

Managing AI workloads on bare metal Kubernetes with GPUs presents unique challenges, from weak namespace isolation to underutilized resources and operational overhead. This blog explores the pitfalls of namespace-based multi-tenancy, why running a separate cluster per team is expensive, and how vCluster enables secure, efficient, and autonomous GPU sharing for AI teams.

Traditional multi-tenancy in Kubernetes often leads to complex RBAC, noisy neighbors, and security headaches. This post breaks down why platform teams struggle with namespace-based isolation, and how virtual clusters offer a better path forward.

Discover why enterprises in 2025 are shifting from traditional VMware based virtual machines to modern, Kubernetes-native architectures. Learn how adopting Kubernetes closer to bare metal simplifies infrastructure, reduces costs, and enhances scalability and efficiency.

What about Rancher? Does vCluster work on Rancher? How do we manage virtual clusters on Rancher? Hey, what about Rancher? These are just a few of the questions we have heard over the last couple of years at KubeCon, on the interwebs, and everywhere in between. The answer was alwa...

When we first launched vCluster in 2021, our mission was clear: make Kubernetes multi-tenancy easier, safer, and more cost-efficient. Since then, we've helped organizations around the globe manage Kubernetes with greater flexibility and security. But as Kubernetes usage expanded,...

Multi-tenancy in Kubernetes has been an ongoing challenge for organizations looking to optimize their cloud-native infrastructure. Over the years, the approach to multi-tenancy has evolved, from simple namespace isolation to virtual clusters and, more recently, full-fledged inter...

Kubernetes was designed for efficient resource sharing, but complexity escalates when multiple teams or users step into the same cluster. As organizations scale, the challenge isn't just about running workloads; it's about how those workloads coexist securely and efficiently.