Which solution fits a containerized analytics platform with multi-cloud portability?

HPE Ezmeral Runtime Enterprise is a unified software platform built on 100% open-source Kubernetes. It is specifically designed to deploy and manage containerized applications, including data-intensive analytics and AI/ML workloads. A core feature of the platform is its ability to provide a consistent, cloud-native experience across any infrastructure—on-premises, in multiple public clouds, or in a hybrid model. This directly addresses the question's requirements for a containerized analytics platform with multi-cloud portability, allowing enterprises to avoid vendor lock-in and run applications where it makes the most sense.

HPE StoreEver is a portfolio of tape storage hardware solutions designed for long-term data archiving and backup, not a containerized application platform.

HPE MSA 2060 is an on-premises physical storage array. It can provide storage for containers but is not a portable, multi-cloud software platform itself.

Aruba Instant On is a portfolio of networking hardware (access points and switches) designed for small businesses, which is unrelated to containerized analytics platforms.

1. HPE Ezmeral Runtime Enterprise Data Sheet. (2023). Hewlett Packard Enterprise. Document ID: a00103935enw.

Page 1: "HPE Ezmeral Runtime Enterprise is the industry’s first enterprise-grade container platform... to run both cloud-native and non-cloud-native applications on any infrastructure: on-premises, in multiple public clouds, or in a hybrid model." This confirms its role as a container platform with multi-cloud portability.

Page 2: Under "Key features and benefits," it lists the capability to "Run a broad range of applications and use cases," explicitly mentioning analytics.

2. HPE Ezmeral Software QuickSpecs. (2023). Hewlett Packard Enterprise. Document ID: a00103936enw.

Page 3: "HPE Ezmeral Runtime Enterprise... is a unified container software platform built on 100% open-source Kubernetes... It is designed for both cloud-native and non-cloud-native applications and supports a variety of use cases including data analytics and machine learning." This directly links the solution to Kubernetes (containerization) and analytics.