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Has Portworx Created an Optimal Pathway for VM Migration to Kubernetes?
New benchmarking tools, datastore constructs, and storage enhancements aim to simplify how enterprises move virtual machine workloads from traditional hypervisor environments into Kubernetes clusters.
3/24/2026
Key Highlights
Portworx introduced VirtBench, an open benchmarking framework designed to measure the readiness of virtual machines running with KubeVirt on Kubernetes.
The company also announced KubeDataStore, a storage construct designed to provide VMware-style datastore management inside Kubernetes clusters.
Updates in Portworx Enterprise 3.6 include improvements in storage performance, replication control, and security features.
The announcements position Portworx as a structured migration pathway for enterprises evaluating how to move VM workloads into Kubernetes environments.
The News
Portworx announced updates to its Kubernetes data platform designed to support enterprises moving virtual machines into Kubernetes clusters while continuing to run containerized workloads. The company introduced new benchmarking tools, storage management constructs, and enhancements to the Portworx Enterprise platform aimed at addressing storage, migration, and data protection requirements for these workloads. The updates center on simplifying how infrastructure teams migrate and manage VM workloads within Kubernetes clusters. Additional details can be found in the company’s official press release.
Analyst Take
Enterprise infrastructure teams are reassessing how virtualization and container platforms operate within the same environment as Kubernetes adoption expands. In that context, a new question is emerging: what is the most effective pathway for moving virtual machines into Kubernetes clusters?
Portworx reports that this transition is beginning to gain traction among early adopters. According to the company, customers are running more than 100,000 volumes and roughly 30,000 virtual machines on Kubernetes using Portworx, with deployments across dozens of enterprise environments. The company also points to its own internal migration as informing elements of the product strategy, noting that its parent organization has already moved approximately 20,000 VM cores onto Kubernetes and continues migrating several hundred cores per day using a small engineering team. While these figures represent only a small portion of the broader virtualization market, they indicate that production deployments of VMs on Kubernetes are beginning to move beyond early experimentation.
Kubernetes first gained adoption as the control plane for containerized workloads such as microservices and data pipelines. Technologies such as KubeVirt now allow traditional virtual machines to run inside Kubernetes clusters, enabling infrastructure teams to run containers and VMs within the same cluster while relying on Kubernetes scheduling, networking, and automation.
The rise of AI workloads adds another dimension to this transition. Many organizations are deploying Kubernetes clusters to support GPU-based training and inference pipelines while continuing to run existing enterprise applications. In practice, this means infrastructure teams want a single cluster to support containers, virtual machines, and AI pipelines while sharing networking, scheduling, and storage services. That convergence places additional requirements on the storage layer, which must support high-throughput data pipelines while maintaining the reliability and data protection required for traditional enterprise workloads.
The Portworx announcements focus on the storage layer required for this shift. Moving virtual machines into Kubernetes introduces new requirements for persistent storage, failover behavior, migration workflows, and data protection. These challenges become more pronounced when clusters span multiple sites or clouds. The enhancements also reflect a focus on day-to-day operational requirements, including migration workflows, failover management, and workload placement across clusters.
VirtBench and the associated reference architectures reflect an effort to provide a repeatable framework for evaluating and executing VM migrations into Kubernetes environments. KubeDataStore introduces a storage grouping model similar to VMware datastores, allowing administrators to track capacity, latency, and VM placement across storage pools. For many environments, these capabilities may define a more structured pathway for moving VM workloads into Kubernetes clusters.
Enterprises exploring this model are also evaluating other modernization paths. Many organizations continue to run large estates on hypervisors such as VMware vSphere while assessing alternatives including Nutanix, Hyper-V, and cloud virtualization services. Kubernetes-based virtualization therefore represents one possible pathway rather than a universal destination.
The broader challenge for infrastructure teams is how to manage persistent data across clusters that now support containers, virtual machines, and emerging AI workloads. HyperFRAME Research Lens (1H 2026) results indicate that only 14% of organizations classify their data architecture as fully AI-ready, despite 37% operating hybrid environments. This highlights the gap between multi-environment deployment and the ability to manage data consistently across them. Storage orchestration, data protection, and migration tooling will likely determine how far Kubernetes extends into traditional virtualization use cases.
What Was Announced
Portworx introduced VirtBench, an open benchmarking framework designed to evaluate virtual machines running with KubeVirt on Kubernetes clusters. VirtBench measures VM boot time, migration speed, failover timing, and storage throughput under different workload conditions. Infrastructure teams can run these tests before migrating virtual machines from existing hypervisor platforms, allowing comparison across storage backends and cluster configurations. The framework can also be used after upgrades to confirm that performance characteristics remain consistent.
The company also introduced KubeDataStore, a storage grouping model designed to replicate the datastore structure used in VMware environments. KubeDataStore aggregates storage capacity from multiple providers, including on-premises arrays, direct-attached drives, and cloud block storage. Administrators can view datastore metrics such as latency, bandwidth, and capacity utilization, and identify which virtual machines are attached to each datastore. Migration workflows allow VMs to move between datastores without volume-level replication.
KubeDataStore integrates with the Red Hat OpenShift console, allowing administrators to manage storage and VM placement from the same interface used to monitor Kubernetes resources. The datastore view shows storage pools, attached workloads, and health metrics. Migration tools allow VMs to move between storage pools or storage providers.
Portworx also introduced updates in Portworx Enterprise 3.6 focused on storage performance and resilience. Sequential read improvements target database workloads that rely on large block reads. Administrators can also rate-limit replication traffic between storage nodes, allowing them to balance application IO with data replication across the cluster.
Security features were expanded as well. The platform now supports secure boot for supported Linux distributions, allowing system components to be verified during startup. Integration with external key management systems, such as HashiCorp Vault, allows credentials and encryption keys for storage arrays and cloud providers to be stored outside the cluster and accessed through controlled policies.
Portworx also announced general availability of Portworx Backup 2.11, which introduces granular restore capabilities for virtual machines running in Kubernetes. Administrators can restore individual files or directories from Linux virtual machines instead of restoring a full VM image. Backup schedules can also be defined using Kubernetes labels, allowing data protection policies to follow workloads across clusters.
Looking Ahead
In the near term, enterprises evaluating virtualization strategies are likely to continue testing how virtual machines behave inside Kubernetes clusters while maintaining existing hypervisor environments for most production workloads. Rather than pursuing large-scale replacement projects, many organizations are introducing Kubernetes into parts of the infrastructure stack where application platforms, automation frameworks, and developer tooling already depend on it.
As these deployments expand, infrastructure teams will need to determine whether Kubernetes clusters can support virtual machine workloads alongside containers and emerging AI pipelines while maintaining the reliability expected from traditional virtualization environments. This evaluation aligns with broader enterprise trends, where HyperFRAME Research data shows only 37% of organizations report having a structured process for AI deployment, and more than half of AI initiatives fail to reach production or stall before delivering expected outcomes. These results indicate that operational validation and repeatability remain unresolved challenges at scale. Storage orchestration, migration tooling, and data protection will play a central role in that evaluation. Tools such as VirtBench and KubeDataStore are designed to address these challenges by providing benchmarking, storage grouping, and migration capabilities for virtual machines running on Kubernetes.
Competition in this area is also evolving. Many organizations initially extend existing storage platforms into Kubernetes using Container Storage Interface (CSI) drivers from incumbent storage vendors. As deployments scale, additional requirements emerge around migration workflows, failover management, and large-scale VM management. Portworx competes in this segment with storage services included in Red Hat OpenShift Data Foundation, as well as Kubernetes-native storage platforms such as Longhorn and other CSI-based approaches.
Kubernetes virtualization is one path enterprises are evaluating as they modernize virtualization infrastructure. Many organizations continue to run traditional hypervisor estates while exploring alternatives such as Nutanix-based virtualization, cloud-hosted virtualization services, or hybrid architectures that combine multiple technologies. Reflecting this reality, Everpure positions Portworx as one option within a broader set of infrastructure choices.
In our view, the Portworx capabilities introduced here suggest an emerging migration framework for organizations moving virtual machines into Kubernetes clusters. Whether it becomes the optimal pathway will depend on how consistently enterprises can use these tools to migrate workloads, maintain performance, and manage persistent data at scale across mixed VM, container, and AI environments.
Steven Dickens | CEO HyperFRAME Research
Regarded as a luminary at the intersection of technology and business transformation, Steven Dickens is the CEO and Principal Analyst at HyperFRAME Research.
Ranked consistently among the Top 10 Analysts by AR Insights and a contributor to Forbes, Steven's expert perspectives are sought after by tier one media outlets such as The Wall Street Journal and CNBC, and he is a regular on TV networks including the Schwab Network and Bloomberg.
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Don Gentile | Analyst-in-Residence -- Storage & Data Resiliency
Don Gentile brings three decades of experience turning complex enterprise technologies into clear, differentiated narratives that drive competitive relevance and market leadership. He has helped shape iconic infrastructure platforms including IBM z16 and z17 mainframes, HPE ProLiant servers, and HPE GreenLake — guiding strategies that connect technology innovation with customer needs and fast-moving market dynamics.
His current focus spans flash storage, storage area networking, hyperconverged infrastructure (HCI), software-defined storage (SDS), hybrid cloud storage, Ceph/open source, cyber resiliency, and emerging models for integrating AI workloads across storage and compute. By applying deep knowledge of infrastructure technologies with proven skills in positioning, content strategy, and thought leadership, Don helps vendors sharpen their story, differentiate their offerings, and achieve stronger competitive standing across business, media, and technical audiences.