Key Criteria for Evaluating Kubernetes Data Storagev2.0

1. Summary

Enterprises of all sizes are embracing hybrid cloud strategies that are ever more complex and structured, moving quickly from a first adoption phase, where data and applications are distributed manually and statically across different on-premises and cloud environments, to a new paradigm in which data and application mobility is the key to flexibility and agility. Now organizations want the freedom to choose where applications and data should run dynamically, depending on any number of business, technical, and financial factors. Kubernetes is instrumental in executing this vision, but it needs the right integration with infrastructure layers—such as storage—to make it happen.

Kubernetes adoption was driven also by the sudden outbreak of the COVID-19 pandemic in the early months of 2020, which forced many organizations to come up with contingency plans quickly to support their activities, business processes, and users. The only way to do so efficiently was to rely on the cloud. Organizations discovered they needed increased agility to respond adequately to the new challenges they faced, and realized Kubernetes is the platform to meet their agility, flexibility, and efficiency needs. This realization made the demand for scalable and enterprise-ready Kubernetes storage solutions even more critical.

On the whole, organizations have moved past the evaluation phase and are now performing early production Kubernetes deployments, but persistent and reliable data storage, as well as data management and security, still remain key factors to consider during deployment assessments. These factors expand the scope of the orchestrator’s function to a broader set of applications and use cases across different types of on-premises and cloud infrastructures. The goal is to provide a common data storage layer that is abstracted from physical and cloud resources, with a standard set of features and services for data protection, security, and management, as shown in Figure 1.

Figure 1. Data Storage for Kubernetes

Kubernetes adoption as the de facto standard for container orchestration continues unabated. Application portability and its innate ability to support hybrid cloud initiatives make Kubernetes a driver of digital transformation. Early proof-of-concept and development/test efforts showed organizations the benefits containers bring to application mobility.

While early container development initiatives focused on simple, low-impact use cases, organizations are now turning their attention to existing stateful applications. And commercial off-the-shelf applications are also being refactored by their developers into container-native deployment models that allow greater flexibility, scalability, and portability.

Applications that support business-critical processes require heightened performance, stability, and predictability to ensure a consistent level of throughput without service disruptions. These requirements drive the demand for enterprise-class data services, solid security controls, and thorough alerting, reporting, and monitoring. Finally, broad adoption of Kubernetes in the enterprise demands storage that is not only seamlessly scalable, but also supports QoS/bandwidth throttling to ensure that business-critical applications are prioritized during bandwidth contention episodes.

Furthermore, enterprises do not want to be locked into a single vendor even as they seek similar feature sets across different on-premises and cloud infrastructures. They choose the public cloud for its flexibility and agility, while on-premises infrastructures are still a better option in terms of efficiency, cost and reliability. In this scenario, it is highly likely they perform development and testing on the public cloud while production takes place on-premises, in the cloud, or both, depending on the business, regulatory, economic, and technical needs of the particular enterprise.