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Virtualized environments running on hyperconverged infrastructure combine the flexibility and streamlined agility of VMs with the operational efficiency and simplicity of hyperconverged systems. The HPE GreenLake edge-to-cloud platform delivers your business the benefits of hyperconverged virtual machines without the cost and complexity of manual configuration and operation—or the financial risks of overprovisioning.
These HPE GreenLake platform configurations based on purpose-built, cloud-native infrastructure, offer a versatile HCI solution in a pay-per-use model. You can streamline IT operations with fast, efficient, resilient, and intelligent hyperconverged platforms—whether you choose the consistency and simplicity of an HPE SimpliVity offering, or the flexibility of a Nutanix deployment running on HPE ProLiant DX hardware.
We offer three tiers of hyperconverged virtual machine infrastructure configurations for each of the two options.
The HPE Ezmeral Unified Analytics solution modernizes legacy data and applications to optimize data-intensive workloads from edge to cloud to deliver the scale and elasticity required for advanced analytics.
Organizations in every industry are looking to leverage AI and ML to harness the power of their data and deliver business innovation through data science. But even when they achieve some measure of success with machine learning pilot programs, many organizations face challenges when they seek to scale these programs to production: security concerns, legacy hardware, siloed data and workflows, inefficient processes, and daunting costs.
To deliver the value of ML and data science to your enterprise, the HPE GreenLake platform delivers an enterprise-grade ML cloud service that enables developers and data scientists to rapidly build, train, and deploy ML models—from pilot to production, at any scale. This solution comprises an optimized hardware stack and is powered by HPE Ezmeral ML Ops. It provides data scientists with self-service access to a sandbox environment for prototyping and testing, to eliminate IT provisioning delays, ensure repeatability, and accelerate time-to-value.
To help you mine continuous streams of value locked in your data, HPE GreenLake delivers a trusted, enterprise-grade AI/ML and analytics cloud-like experience so you can accelerate your data modernization initiatives, from edge to cloud. With a cloud-native architecture, support for open source data science tools, and AI accelerators and frameworks, it provides choice and an elastic, unified analytics platform for data and applications on-premises, at the edge, and in public clouds. The consistent experience helps data, IT teams, developers, and analysts simplify the complexities of machine learning lifecycles and data management at scale, leading to better, faster decisions no matter where your data resides.
Many enterprises have their high-performance databases supported by traditional infrastructure. Managing these segregated workloads results in burdensome manual processes that can expose your database to costly human error. In addition to high maintenance costs, database sprawl, and increased security risk, such siloed operations on traditional infrastructure result in slow provisioning, inflexibility, poor quality insights, and expensive workarounds for disaster recovery.
You need high performance capabilities to unlock the potential of your data and accelerate innovation and run your modeling, simulation, artificial intelligence (AI), and analytics workloads efficiently. Now you can answer your most challenging questions with HPC for your standard business processes, removing the barriers to HPC and leveraging true HPC technology in this cloud service.
With HPE GreenLake for HPC, organizations can gain the agility to scale the environment with ease and empower users with self-service. The HPE GreenLake platform can deliver superior flexibility, scalability, and control of HPC solutions with a cloud service consumption model on premises. Open up AI, ML and more HPC techniques with this second generation cloud service, now with a lower flexible entry point, more GPU choices, Slingshot high speed networking, and HPE Parallel Storage.
While the costs and risks of an on-premises cloud migration are typically lower than those of a public cloud migration, most organizations are looking for a hybrid model that utilizes on-premises cloud, multiple public clouds, and edge computing to deliver the right mix of decision-making effectiveness, agility, security, and cost.
With HPE guiding you through the process, you can achieve your right mix to unlock value in your data wherever it resides, while reducing technological and financial risks. Even though most organizations use an average of five cloud solutions, a majority of core business applications run on expensive, legacy platforms. But with one accountable migration partner with thousands of successful enterprise-wide hybrid and multi-cloud adoption engagements—including HPE GreenLake on-premises cloud with easier, fewer, and less risky steps—you can easily reap the full value of transformation that will move your business forward.
Most enterprises store diverse data types across multiple platforms, such as on-premises data centers, multiple clouds, and at the edge. Each environment becomes an independent silo that restricts access to the data and the insights they contain. This means slower time to modernize analytics and gain the insights that you need to innovate and drive your business.
The HPE GreenLake platform offers a fully managed, on-premises service containing an analytics-ready data fabric for hybrid environments. From a single management view, it allows you to set up, administer, and manage globally distributed data sets across edge-to-cloud deployments. It lowers risk by providing infrastructure in a pay-per-use model, while HPE Ezmeral Data Fabric modernizes analytics and data management, unifying different data types across on-premises, multi-cloud, and edge, and delivering seamless access to a trusted source of data.
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.
Are you looking to accelerate deployment of SAS High-Performance Visual Analytics? HPE Converged Infrastructure for SAS High-Performance Visual Analytics is optimized for the in-memory analytics engine, scaling from 1, or 4 to 256+ HPE ProLiant BL and DL Servers, delivering analytical results to Web browsers and mobile devices in seconds to minutes. These pre-approved configurations support deployments of non-distributed to highly distributed environments. Flexible SMP and MPP configurations that are sized to your workload, and are integrated by the HPE factory closest to you, wherever you are worldwide, regardless of the organizational size. HPE performs onsite installation, working with you to verify network connectivity before a SAS® consultant completes the final software setup. HPE Financial Services offers financing for the total solution, both HPE CI and SAS solutions alike. This solution enables the co-existence of data nodes with Cloudera®. They are supported by SAS EEC.
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