This GigaOm Research Reprint Expires: Aug 23, 2023

GigaOm Radar for Enterprise Kubernetes Data Storagev3.0

Persistent Storage Solutions for Cloud-Native Applications

1. Summary

The adoption of cloud-native, container-based architectures and application modernization continues to fuel demand for persistent storage on Kubernetes platforms. Organizations understand that the benefits of cloud-native workloads in terms of performance, scalability, and portability are key enablers to achieving business goals.

Many enterprises already run cloud-native workloads and understand the benefits of more agile and flexible architectures, including application portability that enables frictionless workload movement from the data center to the cloud, and even across clouds. This provides greater flexibility and responsiveness to business requirements than using legacy technologies.

Data storage solutions for Kubernetes environments have evolved since our last report, especially in the realm of migration and mobility, as well as in maturing enterprise features for security, advanced data services, and enhanced developer experience.

A common pattern in adopting persistent storage solutions for Kubernetes is the reuse of existing enterprise storage solutions. This is usually considered a safe bet for the first couple of deployments, but these systems weren’t architected with the ephemeral nature of containers in mind. Often, older arrays can’t cope with the sheer number of backend operations required by Kubernetes at scale. However, vendors are quickly removing bottlenecks from their architectures to support containers at scale and stretching their product portfolio to include cloud storage services for multicloud use cases.

Compared to other types of storage systems, enterprise storage is highly scalable and secure, aiming to satisfy even the strictest requirements. Often, these systems are operated by trained storage administrators. However, this has been slowly shifting to a self-service on-demand model, with developers requiring more direct access to storage operations to deploy and manage storage for their applications. This is a major boon for enterprise IT organizations looking for the smartest way to evolve their processes and align them with the latest business and technology requirements.

Organizations can now consider more factors than ever before, including financial and business issues, when choosing where their applications and data should run—and they want the freedom to decide where that should be. The public cloud is known for its flexibility and agility, but on-premises infrastructure is still better in terms of efficiency, cost, and reliability. With widespread adoption across cloud, edge, and on-premises, Kubernetes is instrumental in executing the vision of portable, flexible, and agile hybrid cloud strategies, making applications and their data portable and cloud-agnostic—for the most part. It needs the right integration with infrastructure layers—such as storage—to complement its still maturing native support for stateful data storage.

It’s still a significant task to select and implement a Kubernetes storage solution for persistent data that makes the most of Kubernetes’s application mobility and data portability capabilities.

With Kubernetes now supporting business-critical applications and services, requirements become more stringent. Scalability, performance, resilience, security, and other non-functional requirements are the order of the day, and Kubernetes needs to do it all to ensure a consistent level of throughput without service disruptions. These requirements drive the demand for enterprise-class stateful data services, solid security controls, mature multitenant performance management—like quality of service (QoS) and bandwidth throttling—and thorough alerting, reporting, and monitoring.

Lastly, enterprises do not want to be locked into any single vendor’s ecosystem as they reap the benefits of Kubernetes’s portable and agnostic promise, and they’re looking for a storage solution that works with feature parity across on-premises and cloud infrastructures.

This report focuses on persistent enterprise storage solutions for Kubernetes. These enterprise storage solutions support Kubernetes workloads in addition to bare metal and virtualized environments.

How to Read this Report

This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding, consider reviewing the following reports:

Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.

GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.

Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.

2. Market Categories

In this report, we’re evaluating enterprise storage, referring to storage systems with support for Kubernetes-based workloads. These can be highly available controller- or appliance-based systems, software-defined architectures, or hyperconverged servers. A defining characteristic of these systems is that they support more than just Kubernetes and were not specifically designed to support Kubernetes. Support was added as Kubernetes gained popularity. Often, this means that storage and Kubernetes are physically separated, not running on the same systems.

Due to the pre-existing architecture of these systems, we see a broader diversity in how they interact and integrate with Kubernetes, ranging from basic container storage interface (CSI) functionality to a wide array of integration points to make the storage system container-aware for provisioning and deprovisioning purposes.

While enterprise storage is generally resilient, highly available, and performant, it was not designed with Kubernetes constructs or the ephemeral nature of containers in mind. Though this may have initially created performance bottlenecks or problems with the operational overhead of the continuously changing metadata of containers, we expect no enterprise storage array with support for Kubernetes to significantly suffer from these problems in 2022.

That said, we see that enterprise storage vendors are lagging slightly compared to their Kubernetes-native storage competition in terms of how quickly they support new features and standards, as well as the general depth of support for them.

Keep in mind also that scaling of enterprise storage generally works very differently than scaling of Kubernetes-based applications. The misalignment between these two approaches may cause artificial or temporary bottlenecks as usage grows, causing operational overhead and complexities.

To better understand the market and vendor positioning (Table 1), we assess how well solutions for cloud-native Kubernetes data storage are positioned to serve specific market segments.

  • Small-to-medium business (SMB): In this category, we assess solutions on their ability to meet the needs of organizations ranging from small businesses to medium-sized companies. Also assessed are departmental use cases in large enterprises where ease of use and deployment are more important than extensive management functionality, data mobility, and feature set.
  • Large enterprise: Here, offerings are assessed on their ability to support large and business-critical projects. Optimal solutions in this category will have a strong focus on flexibility, performance, data services, and features to improve security and data protection. Scalability is another big differentiator, as is the ability to deploy the same service in heterogeneous environments, including on-premises and cloud. Finally, developer experience is weighed in this category, as large enterprises often need self-service capabilities for their development teams.
  • Independent service provider/managed service provider (ISP/MSP): In this category, solutions that are suitable for ISPs and MSPs are assessed. These should include additional security and multitenancy capabilities and the ability to throttle performance per tenant.

Key to a successful deployment is a solution’s ability to go where the data goes. In other words, it’s important to determine whether the data storage solution can be deployed on-premises, in the cloud, at the edge, and at smaller independent service providers. Such flexibility not only takes the solution’s architecture into account but also indicates whether it can be deployed easily across the variety of environments organizations have to cope with.

Table 1. Vendor Positioning

Market Segment

SMB Large Enterprise ISP/MSP
Dell Technologies
Pure Storage
3 Exceptional: Outstanding focus and execution
2 Capable: Good but with room for improvement
2 Limited: Lacking in execution and use cases
2 Not applicable or absent

Note that GigaOm is also publishing another Radar report on Kubernetes storage, focused on Kubernetes-native storage systems. These storage solutions are generally built as cloud-native microservices, running on top of and tightly coupled with the container orchestrator.

3. Key Criteria Comparison

Building on the findings from the GigaOm report “Key Criteria for Evaluating Kubernetes Data Storage”, Table 2 summarizes how each vendor included in this research performs in the areas that we consider differentiating and critical in this sector. Table 3 follows this summary with insight into each product’s evaluation metrics—the top-line characteristics that define the impact each will have on the organization.

The objective is to give the reader a snapshot of the technical capabilities of available solutions, define the perimeter of the market landscape, and gauge the potential impact on the business.

Table 2. Key Criteria Comparison

Key Criteria

Advanced (CSI) Integrations Deployment Models Advanced Data Services Control Plane Architecture Data Footprint Optimization Developer Experience Visibility & Insights
Dell Technologies 3 3 2 2 3 2 2
HPE 2 3 2 2 3 2 2
IBM 2 1 3 2 3 1 3
Infinidat 2 3 2 2 3 2 2
LINBIT 2 3 2 3 2 1 1
NetApp 3 2 3 2 3 2 3
Pure Storage 3 2 3 2 3 3 3
VMware 3 1 2 2 3 3 3
3 Exceptional: Outstanding focus and execution
2 Capable: Good but with room for improvement
2 Limited: Lacking in execution and use cases
2 Not applicable or absent

In each vendor write-up, we take special note of the deployment models a solution supports, including:

  • Physical appliance (storage-only or hyper-converged)
  • Software-only Kubernetes-native deployment (operator, Helm chart, CRD, and so forth)
  • Public cloud image or marketplace
  • Virtual appliance
  • Managed service
  • Software-only
  • Cloud-adjacent physical appliance or service, directly connected to the cloud

Table 3. Evaluation Metrics Comparison

Evaluation Metrics

Architecture Scalability Flexibility Efficiency Manageability Performance
Dell Technologies 3 3 2 3 3 2
HPE 1 2 2 3 2 3
IBM 1 3 2 3 3 3
Infinidat 3 3 2 3 2 3
LINBIT 2 2 3 2 1 3
NetApp 3 3 2 3 3 3
Pure Storage 3 3 3 3 3 3
VMware 2 2 3 2 3 2
3 Exceptional: Outstanding focus and execution
2 Capable: Good but with room for improvement
2 Limited: Lacking in execution and use cases
2 Not applicable or absent

By combining the information provided in the tables above, the reader can develop a clear understanding of the technical solutions available in the market.

4. GigaOm Radar

This report synthesizes the analysis of key criteria and their impact on evaluation metrics to inform the GigaOm Radar graphic in Figure 1. The resulting chart is a forward-looking perspective on all the vendors in this report based on their products’ technical capabilities and feature sets.

The GigaOm Radar plots vendor solutions across a series of concentric rings, with those set closer to the center judged to be of higher overall value. The chart characterizes each vendor on two axes—balancing Maturity versus Innovation and Feature Play versus Platform Play—while providing an arrow that projects each solution’s evolution over the coming 12 to 18 months.

Figure 1. GigaOm Radar for Enterprise Kubernetes Data Storage

As you can see in Figure 1, Kubernetes data storage solutions for the enterprise reflect a broad spectrum of solutions and various levels of development and maturity. Vendors in this Radar cater to a wide range of (specific) use cases, making it worth the effort to investigate which vendor best fits your use case, keeping in mind what storage you already have in place.

The bottom-right sector highlights the Innovation Leaders in enterprise Kubernetes storage, three vendors with strong enterprise approaches, advanced data services, and well-executed developer experiences. These vendors have high-quality, well-featured solutions that cater to a wide range of use cases. Alongside category leaders, Pure Storage and Dell Technologies, NetApp is making great strides in ensuring its solutions are broadly usable with Kubernetes. These vendors are bridging the old and new with plug-ins to add native support for Kubernetes to existing storage architectures.

In the bottom-left corner are two vendors with different approaches to the market, LINBIT and VMware, ranging from a focus on open source to a developer and application platform. While the foundations of these products are solid and each has its own strengths and challenges, they both miss the mark on some capabilities or lack broad applicability for general-purpose Kubernetes storage.

On the top-right are three vendors crossing from Maturity into Innovation: Infinidat, IBM, and HPE. This kind of movement usually occurs when a vendor is amid a profound transformation initiative, replatforming, or launching a new product.

Inside the GigaOm Radar

The GigaOm Radar weighs each vendor’s execution, roadmap, and ability to innovate to plot solutions along two axes, each set as opposing pairs. On the Y axis, Maturity recognizes solution stability, strength of ecosystem, and a conservative stance, while Innovation highlights technical innovation and a more aggressive approach. On the X axis, Feature Play connotes a narrow focus on niche or cutting-edge functionality, while Platform Play displays a broader platform focus and commitment to a comprehensive feature set.

The closer to center a solution sits, the better its execution and value, with top performers occupying the inner Leaders circle. The centermost circle is almost always empty, reserved for highly mature and consolidated markets that lack space for further innovation.

The GigaOm Radar offers a forward-looking assessment, plotting the current and projected position of each solution over a 12- to 18-month window. Arrows indicate travel based on strategy and pace of innovation, with vendors designated as Forward Movers, Fast Movers, or Outperformers based on their rate of progression.

Note that the Radar excludes vendor market share as a metric. The focus is on forward-looking analysis that emphasizes the value of innovation and differentiation over incumbent market position.

5. Vendor Insights

Dell Technologies

Dell Technologies’s Container Storage Modules (CSM) solution lets customers use traditional storage arrays as multitenant, feature-rich enterprise storage for modern apps running on Kubernetes. This gives Dell customers a full set of data management features for Kubernetes infrastructure with replication, multitenancy, resiliency, and observability, delivering a great Kubernetes experience backed by enterprise storage.

Dell supports cloud, on-premises, and hybrid storage deployment models; Dell PowerScale and Dell PowerFlex are examples of its cloud offerings. However, its on-premises deployment model is still the most popular deployment method. Dell PowerProtect Data Manager supports in-cloud backup protection on Amazon Web Services (AWS) and Microsoft Azure, helping bridge the gap between on-premises Kubernetes environments and using the cloud for snapshots and backup. Support for application-consistent snapshots is a recent addition. Dell supports volume group snapshots, enabling consistent snapshots for more complex applications.

Dell’s CSM portfolio enables custom extensions for enterprise capabilities such as authorization, quota management, replication, and observability. Dell offers a rich Kubernetes storage portfolio, optimized for many types of workloads, with an extensive list of enterprise features. A new addition in 2022 is the application mobility CSM, as well as integration with third-party key management solutions, like HashiCorp Vault.

One of the CSMs enables mature monitoring, alerting, and analytics, as well as Grafana and Prometheus integration. This gives admins essential performance and capacity storage information that can be used to troubleshoot more complex application performance issues.

Although Dell is clearly offering its customers a good solution, there are issues that still need attention, like modern application mobility, data security, and a better developer experience for self-service. With the pace Dell is making on roadmap items, we expect these slight shortcomings to be solved in the foreseeable future.

Strengths: Dell’s Container Storage Modules are industry-leading extensions to CSI, enabling advanced data services for Kubernetes-based environments. The effort and speed that Dell is putting into adding capabilities to its portfolio is notable.

Challenges: Some features require additional products. Application mobility and developer experience features are lagging but are under active development.


HPE adds Kubernetes support via its CSI drivers for Alletra, Nimble, Primera, and 3PAR, which run on vanilla upstream Kubernetes, Red Hat OpenShift, and HPE Ezmeral Runtime Enterprise.

Data protection is handled by the partner ecosystem, and organizations can integrate their own data protection solution with the HPE Kubernetes storage of their choice.

Data optimization capabilities can be accessed by leveraging the underlying storage features, such as deduplication and compression. The solution supports multitenancy features such as QoS, by which users can limit both IOPs and capacity usage, and it also supports encryption.

As the CSI specification gradually matures features and capabilities, HPE keeps a close watch on differentiating features in its primary storage family of products that could be suitable for implementing in CSI and Kubernetes.

The roadmap is quite interesting, and the development pace of new features is good. Currently, the absence of an orchestrator and additional features to manage large-scale environments can be a limiting factor. It’s not yet possible to get full visibility of the storage resources consumed by a Kubernetes application through standard analytics tools.

Strengths: HPE offers Kubernetes storage capabilities throughout its storage product range, making it simple for organizations to operationalize Kubernetes deployments regardless of their size or the nature of their infrastructures.

Challenges: The absence of a Kubernetes-centric management plane across the entire product range creates unnecessary operational overhead and increases complexity.


IBM supports Kubernetes through its open-source CSI driver, available for IBM enterprise storage platforms, OpenShift, and vanilla Kubernetes clusters. In addition to a block storage CSI driver, IBM also supports IBM Spectrum Scale file-based storage through a second plug-in.

The CSI driver supports the IBM DS8000 family, FlashSystem A9000 and A9000R, the Spectrum Virtualize family, and the SAN Volume Controller. This enables Kubernetes support for a broad range of IBM storage solutions, including block and file systems, as well as hardware and software-only deployments. However, this results in some limitations in using existing enterprise storage platforms, such as too many open connections to the storage, which limits the number of storage metadata operations on the DS8000 platform.

While the CSI driver is clearly a stop-gap solution for adding Kubernetes support to existing enterprise storage solutions, it’s a decent step in the right direction for those running these systems, extending their relevance beyond traditional virtualization and bare metal use cases. Moreover, IBM Fusion Spectrum can be layered on top of enterprise IBM storage to enable additional cloud-native use cases and architectures while leveraging investments in existing storage.

The underlying storage systems provide various advanced data services, like replication, deduplication, and more, but there are no mature data portability or migration features.

Strengths: IBM’s CSI driver unlocks Kubernetes support for its portfolio of enterprise storage solutions, and it is a mature, complete implementation of CSI for customers already running IBM storage.

Challenges: The lack of migration capabilities make the CSI driver a stop-gap solution for existing customers. New customers should look at IBM’s cloud-native Spectrum Fusion instead, although the migration capabilities are immature.


Infinidat focuses on high-performance, large-scale storage arrays. The company offers a general-purpose mixed workload InfiniBox array, a platform for consistent performance and low latency, and an InfiniGuard data protection and secondary storage platform. To meet customers’ growing demands for Kubernetes support, Infinidat created a CSI-compliant driver, adding native support for Kubernetes objects and operations. It has additional CSI-based functionality on the roadmap, including replication management and support for its immutable snapshots via CSI. Additionally, it’s working on adding S3 as a front-end protocol, as well as a target for snapshot shipping.

Infinidat’s scalable snapshots have been recently enhanced with immutability and air gapping features for ransomware protection (when used with InfiniGuard), and other core InfiniBox technologies, such as active/active synchronous and three-site replication options, are built around those snapshot capabilities. Various backup software platforms, including Trilio, integrate with InfiniBox snapshots to provide application consistency and archiving options, as well as public cloud options. Infinidat also supports snapshot scheduling with its own software.

Multisystem management is done in the InfiniVerse SaaS service, which also boasts extensive performance monitoring. All metrics data is accessible through application programming interfaces (APIs), which can then be used with open-source tools like Prometheus and Grafana.

The Infinidat architecture is designed for multipetabyte scale. The data plane gives customers low latency and bulk bandwidth and IOPS, and the control plane provides APIs that are non-blocking and scalable. The InfiniBox CSI driver leverages the same APIs as other user interfaces.

Infinidat’s customers typically require high resiliency and long infrastructure lifecycles, as well as the ability to mix workloads on the same systems—not just Kubernetes. This is seen in the company’s current support for Kubernetes, as well as on its roadmap; both of which do not feel bleeding-edge. Kubernetes is but one integration, and the company focuses on a wide spectrum, including VMware, OpenStack, and OpenShift. The CSI driver can be deployed via a Helm chart or an OpenShift Operator.

Infinidat checks the basic Kubernetes boxes and has solid CSI support, but it relies heavily on its partners for functionality like application-consistent snapshots and in-depth monitoring, which forces customers to invest in other tooling to provide a streamlined Kubernetes environment to their users.

Strengths: Infinidat has mature integration into Kubernetes and its ecosystem, including backup solutions. Its roadmap for Kubernetes-related enhancements is solid.

Challenges: The offering lacks in areas like application-aware snapshots and in-depth monitoring, which require third-party solutions.


LINBIT is the company behind DRBD, an open-source, distributed, and replicated storage system. LINBIT SDS is the company’s commercial offering, leveraging drbd, LINSTOR, and other open-source technologies to create a software-defined distributed storage system focused on cloud-native applications.

The storage solution is highly focused on performance optimization, minimizing the compute and memory footprint. Its direct integration into Linux with a kernel module reduces latency and resource consumption. It includes asynchronous and synchronous data replication, snapshotting, delta shipping (to other clusters or remote S3 buckets), and data reduction.

Due to the solution’s architecture, volumes are accessible on every cluster node, and its integration with Kubernetes means it can change the read/write node for each volume depending on pod (re)scheduling. LINBIT SDS is deployed as a collection of microservices. A controller manages the cluster configuration and resources. The satellite manages the creation, modification, and deletion of storage resources on each node. The storage layer is implemented as a kernel driver, several userspace management applications, and some shell scripts. Its support for ARM and other processor architectures is interesting for certain edge deployments.

LINBIT SDS scales to hundreds of cluster nodes and has a specific mode of operation using NVDIMMs for additional performance. It has native integration with Red Hat’s OpenShift but also runs on vanilla Kubernetes. Notably, there is no support for VMware Tanzu. Due to its need for a dedicated kernel module, it may not run on some public cloud providers.

The LINSTOR GUI is fairly immature and lacks some of the features available via command-line interface (CLI) or API. Most notably, the user interface (UI) does not include any Prometheus or Grafana dashboard integration.

Strengths: LINBIT SDS is a highly performant, flexible solution based on open-source technologies and is eminently suitable for tech-savvy customers like service providers or big in-house deployments that need the performance and flexibility.

Challenges: The solution is not fool-proof and has a greater-than-average learning curve, making the solution ill-suited for many organizations.


NetApp delivers storage and data services for Kubernetes for its portfolio of enterprise storage solutions through Astra Control, with its main feature set focusing on application-aware data protection and mobility for container-based workloads, including snapshots and clones, backup and restore, and disaster recovery.

In conjunction with Astra Trident, an open-source, CSI-compliant dynamic storage orchestrator, Astra Control enables customers to consume and manage their storage resources across NetApp storage platforms. It integrates with Kubernetes to dynamically provision persistent volume requests on demand. Additionally, Trident has a REST interface that can be used by any application to create and manage storage across the configured resources.

A key capability of Astra is its support for SnapMirror, which enables native storage migration between ONTAP and Astra Data Store, allowing organizations to migrate to cloud-native architectures seamlessly, including cloud-based platforms.

With Trident and Astra, NetApp offers a consistent security and tenancy model that can be deployed on cloud-native as well as enterprise storage solutions. Trident supports CHAP for authentication, automatic export policy management to control access to NFS shares, and encryption at rest for ONTAP. Trident is also compliant with role-based access control (RBAC) and other security norms. And with Astra, NetApp offers predefined roles to provide a set of permissions limiting certain users to performing only specific operations at the application level.

NetApp Trident and Astra include the tools needed to effectively monitor activity in Kubernetes clusters. Trident has a Prometheus exporter to consolidate infrastructure monitoring in a single platform, and NetApp also provides monitoring tools via its Cloud Insights product/service for the storage administrator.

NetApp’s portfolio natively supports functionality like inline deduplication, compression, and compaction. Trident leverages storage efficiency functionality natively, supported by NetApp’s data storage portfolio and data movers.

Astra Control is a fully managed (SaaS) application-aware data management service that manages, protects, and moves Kubernetes workloads in both public clouds and on-premises. Optionally, Astra Control can be deployed as a self-hosted service.

Strengths: NetApp has integrated its strong suite of data services into cloud-native environments, creating a unique solution for migrating to and protecting container-based workloads.

Challenges: Astra leans on its ONTAP core, limiting its otherwise strong application portability features for on-premises workloads to NetApp storage, though it started to support cloud block storage services from major providers.

Pure Storage

Pure Storage uses its cloud-native storage solution, Portworx, to unlock Kubernetes support for its enterprise storage products, FlashArray and FlashBlade, using its Essentials edition. Portworx PX-Store aggregates and pools storage capacity and a series of advanced data management components. PX-Store is a modern, distributed, container-optimized storage solution with elastic scaling, storage-aware class-of-service, multiwriter shared volumes, local snapshot capabilities, and multiple failover options (node-aware, rack-aware, availability zone-aware). Local synchronous replication for data center high availability is also supported.

Stateful snapshot capabilities are available, as is the ability to perform Cloudsnap backups to cloud storage. Auto-scaling groups are available and support AWS, Azure, and Google Cloud Platform (GCP). Encryption is available at the cluster level when customers bring their own key management system. Optionally, PX-DR and PX-Backup add additional data protection features.

The integration of Portworx on Pure Storage controller-based architectures significantly enhances data efficiency because users benefit from the data reduction capabilities offered by the storage arrays, which are superior to those offered by the standalone Portworx solution.

Portworx is managed through PX-Central and integrates with Pure Storage Pure1, which consumes telemetry data from Portworx and delivers best-in-class app-centric analytics and, eventually, recommendations.

Although Portworx Essentials may feel limited compared to the standalone Portworx product, it allows organizations to seamlessly deploy cloud-native workloads on a proven Kubernetes storage solution, and as their needs grow, they can effortlessly migrate those workloads to the full Portworx solution if they decide to adopt it.

Strengths: Portworx Essentials allows Pure Storage customers to get acquainted with the Portworx experience immediately and without additional cost. The solution delivers a consistent experience that customers can reuse if they adopt the full Portworx product. The product offers excellent data efficiency and management with good monitoring capabilities.

Challenges: The solution offers limited data management and security features, although this is understandable due to the overlap with the potential full Portworx implementation.


VMware Tanzu is built on top of vSAN, so it can be used either in standard on-premises VMware vSphere environments with vSAN or as a part of VMware Cloud Foundation (VCF). VCF offers a full hybrid cloud experience, and vSAN constitutes VCF’s storage foundation.

When Tanzu is deployed on vSAN, it allows the consolidation of traditional virtualized workloads and cloud-native applications on the same layer and is, therefore, best for organizations already using vSAN in production environments. This mode allows storage to be provided to cloud-native workloads from the same storage clusters without architectural changes. VMware also offers an additional deployment option via the vSAN Data Persistence platform (DPp), a framework for modern stateful service providers to use to build Kubernetes plug-ins or operators on, and for their underlying vSphere infrastructure. Stateful services running on the DPp can be deployed on a vSAN datastore with the vSAN host-local shared-nothing architecture (SNA) policy or in a second mode called vSAN Direct.

The first option, SNA policy, allows the application to control placement and take over the duty of maintaining data availability. The technology makes it easy for the persistent service to co-locate its compute instance and a storage object on the same physical ESXi host. With the host-local placement, it’s possible to perform such operations as replication at the service layer rather than at the storage layer. The second option, vSAN Direct, consists of dedicated hardware with optimal storage efficiency and near bare-metal performance. vSAN Direct allows modern stateful services to leverage the availability, efficiency, and security features built into the modern stateful service layer and to have direct access to the underlying direct-attached hardware.

Part of Tanzu’s strength derives from vSAN’s Storage Policy-Based Management (SPBM) capabilities. Various storage policies can be created, each with different resilience requirements, capabilities (such as encryption), QoS (IOPS throttling), and so on. SPBM can be further expanded by organizations using existing API integrations to automate container provisioning workflows. Individual software vendors can integrate their application’s native data management, replication, and service capabilities (such as app-level replication, erasure coding, and encryption) directly into vSAN DPp to shift some of the storage policies at the application level and avoid resource waste.

Management of the Tanzu environment is handled through Tanzu Mission Control, which allows multicluster Kubernetes management on-premises and across clouds. Data migration is available through Velero.

The solution offers great security capabilities with software-based, in-flight and at-rest data encryption, FIPS 140-2 cryptographic modules, support for third-party KMIP-compliant key managers, and the ability to enable datastore-level encryption with a single click. RBAC is natively supported through vSphere and VCF.

Strengths: Tanzu is ideally suited to organizations with a strong VMware focus as they already have all the building blocks to adopt Tanzu quickly and effortlessly, enabling fast movement toward Day 2 operations. The solution is comprehensive, offers two deployment models, and will completely integrate into the enterprise landscape.

Challenges: Although very well architected, Tanzu’s dependency on other VMware products creates a platform overhead that is unnecessarily complex for organizations looking for a pure cloud-native deployment model.

6. Analyst’s Take

CSI support is no longer a differentiator in the enterprise storage space. Vendors are clearly looking to bridge the gap between enterprise storage and cloud-native use cases with additional solutions, functionality, and capabilities, each with their own strengths and drawbacks.

Relative differences between vendors in this year’s report are reduced, indicating a slowdown in innovation as companies instead invest in cloud-native persistent storage solutions for Kubernetes.

However, switching storage platforms is non-trivial, requiring significant investments in new storage technologies, migration efforts, and associated application replatforming, all of which require time. The solutions discussed in this report are helpful tools that let customers start, or accelerate, these replatforming efforts, and most offer adequate support for Kubernetes, including data portability, data protection, and other advanced data services to make this shift happen.

The Leader’s circle (Figure 1) includes three companies—Pure Storage, NetApp, and Dell Technologies—that are able to overcome limitations in CSI and deliver a mature set of features to Kubernetes-based environments.

That does not mean that these solutions offer the only or the best approach to deliver persistent storage to Kubernetes environments; our sister report “GigaOm Radar for Cloud-Native Kubernetes Data Storage” dives into storage solutions suitable for new projects and greenfield deployments, with solutions aligning much closer to Kubernetes’s capabilities.

7. About Joep Piscaer

Joep Piscaer

Joep is a technologist with team building and tech marketing skills. His background as a CTO, cloud architect, infrastructure engineer and DevOps culture coach. He has built many engineering and architect teams and culture.

Founder of TLA Tech, a tech marketing firm focusing on cloud-native. Co-hosts TheCUBE sometimes. Blogs at

8. About GigaOm

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GigaOm’s perspective is that of the unbiased enterprise practitioner. Through this perspective, GigaOm connects with engaged and loyal subscribers on a deep and meaningful level.

9. Copyright

© Knowingly, Inc. 2022 "GigaOm Radar for Enterprise Kubernetes Data Storage" is a trademark of Knowingly, Inc. For permission to reproduce this report, please contact