HPE GreenLake for General Purpose Compute
Get a balance of performance, expandability, and manageability across diverse workloads with the HPE GreenLake edge-to-cloud platform for general purpose compute. Built on a foundation of rack-optimized HPE ProLiant DL and HPE Apollo servers, the solution offers scalability in a small footprint, and can be configured to support even your most critical applications and data on premises. HPE Financial Services can even help you manage the end-of-use upcycling of your existing compute assets in a secure and environmentally responsible manner as you migrate to a pay-per-use model.
Your infrastructure is delivered as a service with HPE GreenLake for compute, so you're ready to scale up or down without up-front capital investment, risk of overprovisioning, or extended purchasing and implementation timeframes. And it can be delivered to your on-premises or co-located data center in as few as 14 days.
HPE GreenLake for Composable Compute
The HPE GreenLake edge-to-cloud platform composable compute solution offers the speed and flexibility you need to compose the workloads that drive business value. Powered by HPE Synergy, the industry's first platform built from the ground up for composable infrastructure, this configuration combines compute, storage, and fabric so all resources are instantly available to run applications—you enjoy the speed, scale, and efficiencies of a cloud experience for your business. It can be delivered to your on-premises or co-located data center in as few as 14 days, and you can extract value for the transition from your existing compute assets—plus support sustainability goals—with assistance from HPE Financial Services.
With composable compute delivered as a cloud service on-premises, you’ll gain agility and avoid costly manual configuration and management of compute resources.
HPE GreenLake for Storage Optimized Compute
HPE GreenLake for storage optimized compute delivers the right balance of performance, expansion, and manageability you need to handle your most critical data-driven applications. With the power of HPE ProLiant and HPE Apollo Servers, you get an ultra-dense, rack-scale architecture designed for big data analytics, software-defined storage, backup and archive, and other data-dense workloads.
Your storage-optimized infrastructure is delivered as a service in a pay-per-use model with the HPE GreenLake edge-to-cloud platform, so you're ready to scale up or down without up-front capital investment, risk of overprovisioning, or extended purchasing and implementation timeframes. Plus, you can recover residual value from your existing compute infrastructure, regardless of the original vendor, and support the circular economy with help from HPE Financial Services. And your new infrastructure can be delivered to your on-premises or co-located data center in as few as 14 days.
HPE Ezmeral Unified Analytics
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.
With Ezmeral Unified Analytics, simplify analytics workloads, unify data silos and modernize data lakes and warehouses with the support and security of HPE services
HPE GreenLake for Machine Learning
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.
HPE GreenLake for AI and Analytics
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.
HPE Ezmeral Runtime Enterprise delivered As a Service
The HPE GreenLake edge-to-cloud platform offers a high-performance, on-premises container solution in a pay-per-use model. HPE engineers perform installation and configuration, and HPE provides complete management of your solution, a single point of contact for support and a technical team who knows your environment and your business. And with a standardized hardware and software build, you avoid a costly manual deployment, and you can have it delivered to your data center.
HPE GreenLake for containers is powered by HPE Ezmeral Runtime Enterprise, a CNCF-certified distribution using 100% open-source upstream Kubernetes. It’s built on 100% open-source upstream Kubernetes, optimized for multi-tenant, multi-cluster management, and it’s suitable for cloud-native apps, non-cloud-native apps, and legacy apps—even stateful ones requiring persistent storage. Cluster management enables administrators to easily create clusters, add policies and permissions, and allocate clusters to developers
HPE GreenLake for Cloud Data Protection
Data, the critical store of business value, is growing exponentially. To effectively exploit data while protecting against data loss and ransomware threats, organizations must modernize data protection from edge to cloud — simplifying operations, aligning infrastructure to actual use, and shifting from insurance to insight.
Secure your backup data and harness its true value with the HPE GreenLake platform. This service is designed to meet every data protection SLA without up-front capital expense or overprovisioning risk. On-demand, cloud-native backup and recovery services deliver agility while preconfigured, on-premises solutions extend your options. It's all delivered with the agility of elastic scale and a pay-per-use structure that links business value to use. Get cloud protection instantly and deploy your on-premises data protection solution in a matter of days.
HPE GreenLake for On-Premise Data Protection
As data growth accelerates and data copy sprawl increases, the challenges of backing up and protecting that data also grow, especially with complex hybrid cloud environments and an evolving threat and compliance landscape. You can protect your business's essential data and unlock its value while keeping up-front capital costs in check with on-premises data protection through HPE StoreOnce with cloud services delivered by HPE GreenLake. Your business gains reliable, cost-efficient automated backup, recovery, and data retention without the risks of overprovisioning, and as it's a pay-per-use deployment, your cost closely tracks your actual usage. Plus, you can recover value from your existing storage infrastructure, regardless of the original vendor, with the help of HPE Financial Services. And with modular pre-configured options, HPE can deliver your solution to your on-premises or co-located data center in as few as 14 days
HPE GreenLake for Database
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.
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