Enterprise Solutions

Are you looking for a two-socket scalable server that powers data analytics and supports hybrid cloud workloads?
The HPE ProLiant Compute for Nutanix Solution is scalable 1U/2U 2P server (HPE ProLiant Compute DL360 Gen12 and HPE ProLiant Compute DL380 Gen12) that delivers exceptional compute performance, memory density with scalability and high-speed data transfer rate to run your most demanding applications. Powered by Intel® Xeon® 6 processors with up to 144 cores and up to 8 TB of memory, the HPE ProLiant Compute for Nutanix Solution is an ideal hyperconverged infrastructure platform for enterprise applications and workloads.
HPE ProLiant Compute for Nutanix Solution is engineered for your future, with next-level security, optimized performance and efficiencies, and automated, AI-driven productivity.

Are you looking for a one-stop solution for your Red Hat® environment?

These three technologies provide everything needed for hybrid cloud, enterprise container, and Kubernetes deployment.

Red Hat OpenShift® Container Platform provides you the flexibility to tailor products to your individual needs with the freedom of choosing from the HPE ProLiant, HPE Synergy and workload solutions portolio.

Red Hat Ansible Automation® helps operating automation across your organization run infrastructure code and automate provisioning tasks for cloud providers, storage solutions, and other infrastructure components. Meanwhile Red Hat OpenShift® Container Storage is persistent software-defined storage integrated optimized for Red Hat OpenShift® Container Platform.

Are your High Performance Compute (HPC) and AI environments struggling with file management?
HPE Data Management Framework 7 (DMF7) delivers centralized data management across HPC and AI storage systems and protects scalable, parallel file systems like Lustre and Spectrum Scale. Namespace reflection is used to create an independent snapshot of file system state, allowing you to recover file systems in a known good state. This system maintains file versions, allowing users to recover files from previous successful job runs.

HPE DMF7 automates data movement between tiers in a storage hierarchy, e.g. between flash and disk. Administrators and users can also use HPE DMF7 to move files between file systems, e.g. when files must be moved from storage that is being retired. HPE DMF7 improves utilization of expensive, high performance storage by automatically moving files to lower cost storage tiers, creating a virtual storage space that appears to scale beyond the physical capacity.

HPE Sustainability Insight Center provides energy and carbon emissions reporting through a unified console to empower customers to make impactful changes, lower costs and achieve their sustainable IT goals.

The HPE Sustainability Insight Center provides a current view of the total energy consumption for HPE Compute devices that are managed by HPE GreenLake for Compute Ops Management and HPE GreenLake for Compute Ops Management – OneView Edition, including information about greenhouse gas (GHG) emissions¹, and costs associated with your energy consumption.

Measures the carbon footprint of HPE IT assets based on actual energy usage. 

Analyzes telemetry aggregated across sites and provides cumulative totals and averages. 

Reports carbon footprint and energy costs across sites (per device and site location). 

Reports energy consumption data from devices.

Is the task of implementing SAP HANA for your company very challenging? The HPE Integrity MC990 X TDI for SAP HANA Scale-up Configurations solve your dilemma. These SAP configurations provide a certified, integrated, pre-configured system that fits smoothly, efficiently into your existing infrastructure of storage and networking. All of the HPE MC990 X TDI for SAP HANA Scale-up Configurations have been tested and are certified. When you select your configuration, you have confidence that it is efficient and effective and meets the SAP HANA performance indicators (KPIs). As your use of your data grows, the HPE MC990 X TDI for SAP HANA Scale-up Configurations are ready to accommodate your increased workloads smoothly, so that you have no concerns about future growth.

HPE InfoSight for Servers combines the machine learning and predictive analytics of HPE InfoSight with the health and performance monitoring of Active Health System (AHS) and HPE Integrated Lights Out (iLO) to optimize performance and predict and prevent problems. HPE InfoSight for Servers nearly eliminates wasted time and headaches by transforming how infrastructure is managed and supported. AHS is like a “flight recorder” for your server that provides continuous, proactive health monitoring and recording thousands of system parameters and diagnostic telemetry data 24x7 on the server. HPE InfoSight for Servers analyzes the telemetry data from AHS to derive insights from the behaviors of the install base to provide recommendations to resolve problems and improve performance. iLO Amplifier Pack functions as an on-premise aggregator and transmitter for HPE InfoSight for servers.

Are you looking to simplify the management of across core to edge to cloud? HPE Solutions with Cohesity address several key issues facing customer today including, data fragmentation, complex or siloed data protection and backup solutions, data governance and compliance requirements, data mobility and cloud integration all with a unified platform. The joint solution empowers your business to protect data and apps, detect cyberthreats, backup and manage data, and recover rapidly from ransomware. HPE Solutions with Cohesity combine optimized HPE ProLiant or HPE Alletra Storage servers with Cohesity software to deliver a multi-cloud, data platform. The solution includes a comprehensive range of data management services, available on-premises or from the cloud. HPE Solutions with Cohesity are designed with a flexible architecture, which allows easy expansion to additional use cases, further increasing operational simplicity and reducing TCO.

Much like pre-DevOps software development, data science organizations still spend a significant amount of time and effort when moving projects from development to production. Model version control and code sharing is manual, and there is a lack of standardization on tools and frameworks, making it tedious and time-consuming to productize machine learning models.

HPE Ezmeral Machine Learning Ops (HPE Ezmeral ML Ops) extends the capabilities of the HPE Ezmeral Runtime Enterprise and brings DevOps-like agility to enterprise machine learning. With the HPE Ezmeral ML Ops, enterprises can implement DevOps processes to standardize their ML workflows.

HPE Ezmeral ML Ops provides data science teams with a platform for their end-to-end data science needs with the flexibility to run their machine learning or deep learning (DL) workloads on-premises, in multiple public clouds, or a hybrid model and respond to dynamic business requirements in a variety of use cases.

HPE Ezmeral Runtime Enterprise is an enterprise-grade container orchestration platform that is designed for the containerization of both cloud-native and non-cloud-native monolithic applications with persistent data. It deploys 100% open-source Kubernetes for orchestration, provides a state-of-the-art file system and data fabric for persistent container storage, and provides enterprises with the ability to deploy AI and Analytics workloads in containers. Enterprises can now easily extend the agility and efficiency benefits of containers to more of their enterprise applications—running on either bare-metal or virtualized infrastructure, on-premises, in multiple clouds, or at the edge.

The HPE Edge Center is a complete self-contained, single cabinet modular, and software-defined data center, which enables any IT environment at the edge. It protects compute, network and storage infrastructure while providing industry first edge management control system which enables edge management automation. The HPE Edge Center provides flexibility to deploy computing fast and efficiently, where and when you need it. The perfect solution for Industrial IoT as well as other enterprise edge or AI workloads.