HPE Ezmeral

Basic Information

HPE Ezmeral is a comprehensive software portfolio designed for data-driven initiatives, encompassing container orchestration, data management, and machine learning operations. It includes key components such as HPE Ezmeral Runtime Enterprise (formerly Container Platform), HPE Ezmeral Data Fabric, HPE Ezmeral ML Ops, and HPE Ezmeral Unified Analytics Software.

• Model/Components: HPE Ezmeral Runtime Enterprise, HPE Ezmeral Data Fabric, HPE Ezmeral ML Ops, HPE Ezmeral Unified Analytics Software.
• Version:
  • HPE Ezmeral Runtime Enterprise: Latest stable versions include 5.7.0 (released November 12, 2024) and 5.7.1 (released April 30, 2025).
  • HPE Ezmeral Data Fabric: Latest stable versions include 7.9.0 (released March 31, 2025) and 8.0.0 (published November 2025).
  • HPE Ezmeral Unified Analytics Software: Version 1.5.x.
• Release Date: The HPE Ezmeral brand and platform debuted on June 23, 2020.
• Minimum Requirements: Requirements vary significantly based on deployment environment (production vs. non-production), workload type (e.g., ML Ops, Big Data), and host function (compute, gateway, storage).
• Supported Operating Systems: Linux distributions including Red Hat Enterprise Linux (RHEL), Rocky Linux, Ubuntu, SUSE Linux Enterprise Server (SLES), and Oracle Enterprise Linux (OEL). Specific versions depend on the Ezmeral component and release.
• Latest Stable Version: See above for individual components.
• End of Support Date:
  • HPE Ezmeral Runtime Enterprise: Lifecycle stages are Active (12 months), In Maintenance (6 months), and End of Maintenance. For example, version 5.6.4 reached End of Life on March 1, 2025. Version 5.7.0 is In Maintenance until October 31, 2025, and 5.7.1 until April 30, 2026.
  • HPE Ezmeral Data Fabric: Releases are fully supported for 27 months and in maintenance for 18 months before end of support.
  • HPE Ezmeral Unified Analytics Software: Version 1.5.x enters End of Life on October 31, 2025.
• End of Life Date: See End of Support Date.
• Auto-update Expiration Date: Not explicitly stated, but updates typically cease at the End of Maintenance stage.
• License Type: Term licensing, capacity-based on vCPU and GPU, available for one, three, or five years. An Instant-On license is available for evaluation purposes. Subscription license-to-use models are also offered.
• Deployment Model: Supports deployment on-premises, in public clouds (AWS, Azure, Google Cloud Platform), hybrid cloud environments, and at the edge, on both bare-metal and virtualized infrastructure.

Technical Requirements

Technical requirements vary by the specific HPE Ezmeral component and its intended role within the deployment. General guidelines for typical nodes are as follows:

• RAM: A standard compute/storage node for HPE Ezmeral Data Fabric typically requires 64 GB of RAM.
• Processor: For HPE Ezmeral Data Fabric, a standard compute/storage node uses a dual CPU socket system with 2x8 core CPUs (32 cores with Hyper-Threading enabled). For HPE Ezmeral Unified Analytics Software, the combined vCPUs of worker hosts should be at least 96.
• Storage: A standard HPE Ezmeral Data Fabric node requires 12x2 TB SATA drives. The operating system should reside on a single, dedicated drive, not shared as a data drive. All storage must be surfaced as a raw block device, without partitions or mounted file systems. The installation host for Unified Analytics requires a minimum of 20GB for Docker.
• Display: Not a direct requirement for the platform itself; management is typically via web-based consoles.
• Ports: A 10GbE network interface is required for HPE Ezmeral Data Fabric nodes. The installation host for Unified Analytics requires firewall access on port 8080.
• Operating System: Supported Linux distributions include Red Hat Enterprise Linux (RHEL) 7.x/8.x, Rocky Linux 8.x, Ubuntu 18.04/20.04, SLES 15 SP2/SP3/SP5, and Oracle Enterprise Linux 8.x. HPE recommends dedicated hosts with clean OS installations and the latest packages.

Analysis of Technical Requirements: The technical requirements emphasize robust hardware for performance and scalability, particularly for data-intensive and AI/ML workloads. The platform's reliance on specific Linux distributions and the recommendation for dedicated, clean OS installations highlight its enterprise-grade nature, prioritizing stability and controlled environments. The storage requirements for raw block devices indicate a focus on direct, high-performance data access for its distributed data fabric. The significant vCPU requirements for Unified Analytics suggest its capacity for handling complex computational tasks.

Support & Compatibility

• Latest Version: See Basic Information for the latest stable versions of HPE Ezmeral Runtime Enterprise, Data Fabric, and Unified Analytics Software.
• OS Support: Extensive support for enterprise Linux distributions including RHEL, Rocky Linux, Ubuntu, SLES, and OEL. Specific versions are tied to individual Ezmeral components and releases.
• End of Support Date: Lifecycle policies define Active, In Maintenance, and End of Maintenance stages, with specific dates varying by version and component. Users are encouraged to upgrade to newer versions for continued active support.
• Localization: Not explicitly detailed in public documentation, but enterprise software typically offers multi-language support.
• Available Drivers: The platform integrates with various ecosystem components and provides necessary drivers. GPU support is available for Spark workloads through the NVIDIA RAPIDS plugin.

Analysis of Overall Support & Compatibility Status: HPE Ezmeral demonstrates strong compatibility with leading enterprise Linux operating systems, ensuring a broad foundation for deployment. The clear lifecycle management for each software version provides transparency for planning upgrades and ensures access to bug fixes and new features. The emphasis on ecosystem integration, including GPU support, highlights its readiness for modern AI/ML workloads. While specific localization details are not prominent, the enterprise focus implies standard international support.

Security Status

• Security Features: HPE Ezmeral provides enterprise-grade security and authentication, robust policy management for Kubernetes clusters, and secure model management within multi-tenant environments. It is designed to meet security compliance requirements. SELinux is supported in various modes (Enforcing, Permissive, Disabled) on compatible operating systems.
• Known Vulnerabilities: HPE provides information regarding security vulnerabilities and updates to address container image vulnerabilities through its documentation and support channels.
• Blacklist Status: No information found indicating a blacklist status.
• Certifications: HPE offers product certifications for professionals in HPE Ezmeral Data Fabric, verifying expertise in implementation, administration, maintenance, and troubleshooting.
• Encryption Support: While not explicitly detailed in search results, "enterprise-grade security" implies comprehensive encryption capabilities for data at rest and in transit.
• Authentication Methods: Supports user identity authentication, particularly for Spark workloads, and provides secure access control.
• General Recommendations: HPE recommends installing Ezmeral on dedicated hosts with clean OS installations to prevent unpredictable behavior and enhance security. Using the standard OS kernel and keeping OS packages updated are also advised.

Analysis on the Overall Security Rating: HPE Ezmeral prioritizes enterprise-grade security, offering features like robust authentication, policy management, and secure environments for AI/ML workloads. The support for SELinux and the proactive approach to addressing container image vulnerabilities demonstrate a commitment to a secure posture. Recommendations for dedicated and clean OS installations underscore the importance of a secure underlying infrastructure. The availability of professional certifications further indicates a focus on secure deployment and management practices.

Performance & Benchmarks

• Benchmark Scores: Specific public benchmark scores are not readily available in the provided search results.
• Real-World Performance Metrics: HPE Ezmeral is designed for consistent data storage performance optimization, particularly for analytics workloads. Its Data Fabric provides a high-performance file and object store capable of exabyte-scale data and trillions of files. It aims to accelerate AI deployments from months to days.
• Power Consumption: Not explicitly detailed, but performance is tied to the underlying hardware infrastructure chosen by the customer.
• Carbon Footprint: Not explicitly detailed, but related to the efficiency of the underlying hardware and data center operations.
• Comparison with Similar Assets: Competitors include Amazon SageMaker AI, Alteryx Designer, Cloudera AI, Google Cloud Platform, Teradata VantageCloud, Google Kubernetes Engine (GKE), Amazon EKS, Red Hat OpenShift, and Azure Kubernetes Service (AKS). Reviewers have rated HPE Ezmeral Runtime Enterprise higher than Amazon SageMaker AI and Cloudera AI in categories such as service and support, ease of integration and deployment, and evaluation and contracting.

Analysis of the Overall Performance Status: HPE Ezmeral is engineered for high performance and scalability, particularly for demanding AI, ML, and analytics workloads. The distributed data fabric is built to handle massive datasets efficiently, enabling faster insights. While specific benchmark numbers are not provided, the platform's architecture, including its Kubernetes foundation and optimized data storage, suggests strong real-world performance. Its competitive positioning against major cloud and enterprise platforms indicates a focus on delivering robust performance for complex data-intensive applications.

User Reviews & Feedback

User feedback and reviews highlight HPE Ezmeral's strengths in unifying diverse data and application environments, particularly for AI/ML and analytics.

• Strengths: Users appreciate its ability to run containers and Kubernetes at scale, modernize applications, and manage applications, data, and operations with AI and analytics for faster insights. The platform provides control for governance, compliance, and cost management, along with enterprise-grade security. Its open architecture and flexible deployment options are valued for streamlining AI and GenAI development. The centralized data management platform simplifies access, governance, and security across diverse data types, accelerating time-to-value for AI initiatives. Compared to some alternatives, it receives higher ratings for service and support, ease of integration and deployment, and evaluation and contracting.
• Weaknesses: While not explicitly detailed as weaknesses, the need for dedicated hosts and specific OS versions for optimal performance and stability could be perceived as a constraint by some users.
• Recommended Use Cases: HPE Ezmeral is recommended for cloud-native applications, stateful analytics, AI/ML workloads, data-intensive operations, DevOps, CI/CD pipelines, application modernization, hybrid cloud deployments, and edge computing. It is particularly suited for building data lakes and data warehouses.

Summary

HPE Ezmeral is a robust and comprehensive software portfolio designed to accelerate digital transformation by providing a unified platform for AI, machine learning, and analytics workloads across hybrid cloud environments. Its core components, including HPE Ezmeral Runtime Enterprise (for container orchestration), HPE Ezmeral Data Fabric (for distributed data storage), and HPE Ezmeral ML Ops (for streamlining the ML lifecycle), offer a powerful ecosystem for modern enterprise applications.

Strengths of HPE Ezmeral include its open architecture, flexible deployment across on-premises, public cloud, and edge environments, and its ability to run both cloud-native and stateful applications at scale using Kubernetes. The platform excels in providing enterprise-grade security, robust data governance, and simplified data access, which are critical for data-intensive initiatives. Users benefit from its strong support for various enterprise Linux distributions and clear lifecycle management, ensuring stability and predictable updates. Its competitive standing against major industry players in terms of service, support, and ease of deployment further solidifies its value proposition.

Potential weaknesses, while not explicitly stated in reviews, may include the stringent technical requirements for underlying infrastructure, such as dedicated hosts and specific OS versions, which might necessitate careful planning and resource allocation.

Recommendations: HPE Ezmeral is highly recommended for enterprises seeking to modernize their application landscape, operationalize AI/ML models efficiently, and manage large-scale data analytics across diverse infrastructure. It is particularly well-suited for organizations adopting a hybrid cloud strategy and those requiring robust data persistence and governance for their containerized workloads. Its comprehensive suite of tools and focus on open-source technologies make it a strong contender for driving data-driven innovation.

Information provided is based on publicly available data and may vary depending on specific device configurations. For up-to-date information, please consult official manufacturer resources.