Accelerate time-to-value for AI and machine learning
Organisations in every industry are looking to leverage artificial intelligence (AI) and machine learning (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 programmes, many organisations face challenges when they seek to scale these programmes to production: security concerns, legacy hardware, siloed data and workflows, inefficient processes and daunting costs.
Get the HPE GreenLake edge-to-cloud platform experience
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 preconfigured solution comprises an optimised 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. And as a fully managed solution, the HPE GreenLake offering frees IT from routine infrastructure management tasks.
Operationalise ML workflows on-premises
Unlock the value of your data where it lives. The HPE GreenLake platform is a fully managed on-premises solution that lets you avoid the costs and risks of moving your data to and from the cloud while meeting compliance and regulatory requirements for privacy and data sovereignty.
Accelerate time-to-value for data science teams
HPE Ezmeral ML Ops brings DevOps agility to every stage of the ML lifecycle, and free up your data scientists to concentrate on data science. They can provision testing and development environments in minutes, not days or weeks, through HPE GreenLake Central – spinning up containerised clusters with their choice of open-source or third-party independent software vendor (ISV) tools through an intuitive graphical user interface.
Pay for what you use
Meet the demands of inherently spiky data sets and model testing while paying only for what you use and with a buffer of extra capacity in place ahead of demand. Plus, you can view your usage at any time with complete transparency with the HPE GreenLake Central platform.
Offload the burden of managing your ML infrastructure
HPE GreenLake Management Services, securely delivered from our world-class IT Operation Centres (ITOCs) around the globe, help you fill skills gaps and free up your resources for more productive tasks. HPE experts handle the performance tuning, capacity planning, lifecycle management, firmware updating and patch management while monitoring critical KPIs of performance, uptime, time to resolution and ticket status.
Based on your priorities and your ML workloads, the HPE GreenLake edge-to-cloud platform has several solutions to help you operationalise your ML models efficiently.
The HPE GreenLake edge-to-cloud platform for ML Ops brings DevOps agility to the machine learning lifecycle – speeding data science workflows and enabling data scientists to accelerate the time to value of ML projects with this end-to-end data science platform. This service is powered by HPE Ezmeral ML Ops.
Simplify your experience with analytics platforms like Apache Hadoop to extract business value from unstructured data. The HPE GreenLake platform can take much of the complexity and cost off your back, so that you can focus purely on deriving intelligence from your Hadoop clusters. We offer a complete end‑to‑end solution for Big Data that includes hardware, software and HPE Pointnext Services.
Storage services for AI and Analytics
Address your growing unstructured data needs for AI with storage solutions from HPE GreenLake featuring Scality and Qumulo. Scale and manage billions of files with instant control and the ability to perform actionable analysis quickly. Features like deep and rich data analytics built into the file system help you understand your data in ways you never could before.
See how HPE GreenLake for ML Ops works
Click the arrows to see how you can manage ML Ops within HPE GreenLake Central.
“We’re pleased with the performance of the ML Ops platform so far and very supportive of the steps HPE is taking to deliver ML Ops capabilities as a cloud service through HPE GreenLake.”
Dr. Abdulla Al Kendi, Acting Executive Director of Technology and Policies, Abu Dhabi Digital Authority
Looking to dive deeper? Here are some resources that might interest you.
Operationalising machine learning: The future of practical AI
The possibilities for artificial intelligence in business are almost endless, but what must be done to truly integrate one with the other? The practice of MLOps may be the differentiator for success.
What is HPE Machine Learning Ops?
HPE ML Ops supports the entire machine learning lifecycle, from model building through deployment, monitoring and retraining.
Combine pay per use and Hadoop solutions
Get security, performance and faster time to business insights with a built-for-purpose Hadoop solution.
The do's and don'ts of machine learning
When launching transformative technologies, such as machine learning, organisations not only need an edge-to-core strategy but the expertise to execute on it.