엔터프라이즈 솔루션

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.

The edge is where people, devices, and things connect. Here, systems and secure connectivity enable data to be analyzed at its source, creating more personalized experiences, new products and services, and enhanced efficiencies. But many organizations struggle to take advantage of the opportunities at the edge due to massive data growth, sensor sprawl, silos, a distributed landscape, and networking and security challenges.
With the HPE GreenLake platform, organizations can streamline the deployment of an edge-to-cloud solution stack across their locations. From networking to compute and storage to workload orchestration and more, all are available at scale.

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.

Enhance accuracy, competitiveness, product quality, and time to market. With the HPE GreenLake platform, you can transform your data-intensive applications and gain the visibility, control, and performance of hybrid cloud while maintaining the utmost security and compliance your industry demands. Power your business with the improved performance, agility, operational efficiency, and lower costs provided by cloud services that are designed, optimized, and delivered for critical industry vertical and horizontal workloads.
With the HPE GreenLake platform, you can run your business-critical applications on-premises, at the edge, or in colocation centers with the scalability and agility you need without the cost, risks, and complexity associated with the public cloud. Spend your time responding to changing customer demands and discovering new ways to better serve them instead of infrastructure management.

Consume pre-architected and validated end-to-end hybrid cloud managed services with an existing, brownfield IT environment that provides a full view into your consumption and use across your entire hybrid cloud and multi-cloud estate. With the HPE GreenLake edge-to-cloud platform, you can consume, manage and control all your cloud services from a single, self-service dashboard, enabling your IT staff to focus on business outcomes, such as developing new applications and services to attract more customers and grow revenue. It’s time for a simplified solution that helps you get the most from hybrid cloud without high costs and a steep learning curve. The HPE GreenLake platform reduces risk and complexity while accelerating cloud adoption with automated cloud operations to manage and optimise performance, costs, security and compliance.

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. Monthly billing tracks your actual usage, while HPE GreenLake Central monitors your consumption, working with you to add additional resources as needed ahead of business demand. Whether you prefer a Nutanix environment with a choice of hypervisors, or an HPE SimpliVity–based solution, modular pre-configurations make it easy to select the right options, and HPE can deliver your configuration to your on-premises or co-located data center in as few as 14 days.

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.

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.

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

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.