Enterprise Solutions

Is your storage slowing down your HPC compute cluster?

The Cray ClusterStor E1000 Storage System is purpose-engineered to meet the demanding input/output requirements of supercomputers and HPC clusters in a very efficient way. The E1000 parallel storage solution typically achieves the given HPC storage performance requirements, significantly reducing the number of storage drives. That means HPC users with a fixed budget for the HPC system can spend more of their budget on CPU/GPU compute nodes, accelerating time-to-insight. The E1000 Storage System embeds the open-source parallel file system Lustre to deliver this efficient performance. Hewlett Packard Enterprise provides enterprise-grade customer support in-house for Lustre that scales out (nearly) linearly, without software licensing for the file storage systems per terabyte capacity or per storage drive. This allows customers to reap the benefits of the open-source movement while getting enterprise-grade support.

HPE Alletra dHCI radically simplifies infrastructure for every application by reimagining HCI without limitations. Built for business-critical apps and mixed workloads, HPE Alletra  dHCI enables IT agility while ensuring apps are always-on and always-fast. VM-centric and AI-driven operations make it effortless, while 99.9999%² guaranteed data availability and consistent sub-millisecond latency mean it's ideal for the most demanding apps and workloads. It lowers costs with flexible, independent scaling of compute and storage and industry-leading data efficiency. Finally, HPE Alletra dHCI maximizes agility by unlocking the cloud experience across hybrid cloud. We call it HCI 2.0 as it’s HCI without limitations.

Is your IT operations team overloaded with too many alerts and too many tools?

Is the performance of your applications suffering because you're unable to quickly resolve infrastructure incidents?

OpsRamp, a Hewlett Packard Enterprise company, is a SaaS-based ITOM solution that delivers total visibility across on-premises, cloud, and cloud-native environments, centralizes infrastructure monitoring and management of business-critical services, and improves operations through automation and integration with your existing ITOM and ITSM toolsets. OpsRamp helps modern IT operations teams align with the business for delivering innovation, respond faster, and automate procedures to help reduce operating costs and keep your applications performing to expectation. By improving operational efficiencies and governance, your team will be more productive in supporting more strategic business objectives. Centralize your IT operations with OpsRamp today.

Are you struggling with transforming your Microsoft Hyper-V based virtualized infrastructure into a true hybrid environment to benefit from low latency on-premises workloads and the agility of cloud services alike?

Powered by a dedicated virtualization OS platform consumed as an Azure cloud service, refreshed annually and combined with the HPE ProLiant platform, HPE ProLiant for Microsoft Azure Stack HCI Integrated Systems offer the ease of an appliance-like solution experience. It provides the security and efficiency of the HPE ProLiant DL380 Gen11 server platform augmented by HPE deployment and configuration services, available AS HCI compliant Aruba and FlexFabric switches, and rolling testing of any OS and driver updates to confidently operate your important workloads.

HPE and Microsoft partner to provide a seamless experience from initial configuration and deployment to sure-footed management and offer the benefits of cloud services and integrated support experience.

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.

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.

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.