Key Criteria for Evaluating Kubernetes Data Storage Solutionsv4.0

An Evaluation Guide for Technology Decision-Makers

Table of Contents

  1. Summary
  2. Kubernetes Data Storage Primer
  3. Report Methodology
  4. Decision Criteria Analysis
  5. Evaluation Metrics
  6. Key Criteria: Impact Analysis
  7. Analyst’s Take
  8. About Joep Piscaer

1. Summary

Organizations of all sizes are embracing cloud computing. They realize that the unparalleled flexibility and continuous innovation that comes with the cloud are key drivers of digital transformation, supporting their ever-evolving activities, business processes, and user bases. However, companies have realized that the cloud isn’t perfect, nor is it the place for every single workload. They’ve rediscovered the value of running applications, including containerized ones, on-premises.

In fact, containerization is overtaking virtualization as the predominant on-premises deployment method, and Kubernetes has become the standard for deploying and managing applications in production.

Kubernetes is now ubiquitous—across the major hyperscale and edge cloud providers, smaller independent service providers, and on-premises data centers. The Kubernetes API and associated storage protocols are no longer emerging or optional technology; they are a hard requirement for organizations looking to deploy an application to a new location.

With its widespread adoption across cloud, edge, and on-premises infrastructure, Kubernetes is instrumental in executing the vision of portable, flexible, and agile hybrid cloud strategies, making applications and their data both 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.

While organizations have discovered the ease of operation that the ubiquitous availability of Kubernetes application programming interfaces (APIs) brings, they have also learned that infrastructure dependencies like storage are still a major consideration for full-blown production deployments with mission-critical applications, especially in multicloud scenarios. The architecture of the control plane specifically is a determining factor in how well a storage platform can be integrated into these infrastructure environments.

It’s still a significant task to select and implement a Kubernetes storage solution for persistent data that makes the most of Kubernetes’ application mobility and data portability potential. Spurred by the rising popularity of cloud computing and containerized applications, developers are increasingly discovering the value and operational simplicity of object storage. That means a key success factor for choosing the right Kubernetes data storage platform is the solution’s support for object storage as a first-class, enterprise-grade storage protocol, in addition to file and block storage. As storage vendors continue to work on adding both native Kubernetes support and support for object storage, finding the right solution to fit your requirements remains a non-trivial task. This is a challenge because vendors must support a common data storage layer that abstracts physical and cloud resources with a standard set of features and services for data protection, security, and enterprise data management (as shown in Figure 1).

Figure 1. Data Storage for Kubernetes

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 must 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’ portable and agnostic promise, and they look for a storage solution that works with feature parity across on-premises and cloud infrastructures, requiring flexibility on the solution’s part as it’s deployed across various cloud and on-premises environments.

This is the fourth year that GigaOm has reported on the Kubernetes data storage space. This report builds on our previous analyses and considers how the market has evolved over the last year.

This GigaOm Key Criteria report details the capabilities (table stakes, key criteria, and emerging technologies) and non-functional requirements (evaluation metrics) for selecting an effective Kubernetes data storage solution. The companion GigaOm Radar reports—one Radar for enterprise Kubernetes data storage and the other for cloud-native Kubernetes data storage—identify vendors and products that excel in those capabilities and metrics. Together, the Key Criteria and Radar reports provide an overview of the category and its underlying technology, identify leading Kubernetes data storage offerings, and help decision-makers evaluate these solutions so they can make a more informed investment decision.

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.

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