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Come play in a container sandbox: Test your workload application for free!
When it comes to starting a data science project, many data scientists have to wait for their internal DevOps team to configure and provision the infrastructure for them. This step is just to enable an IT environment where they can then deploy popular AI and ML technologies. Waiting for DevOps to provision the resources and getting approvals to use data can take days—or even weeks, causing serious delays in project time and resources.
What if there was a self-service application that allowed anyone on a data science team to spin up a TensorFlow, PyTorch, or other leading AI projects in minutes and self-provision resources in a simpler way?
ORock has unveiled an on-demand Data Science as a Service (DSaaS) solution exclusively in the ORock cloud. This hardened, enterprise-grade version of HPE’s Ezmeral Container Platform provides data scientists with a library of leading AI and ML applications they can deploy with a few clicks. Data scientists, from entry-level engineers to senior Kubernetes administrators, can explore a suite of open-source tools and resources to help manage the entire ML and AI lifecycle including data prep, model building, and model training, all while reducing costs and improving productivity.
This new DSaaS model is a simplified way to experiment with cutting-edge data science and data analytics capabilities in a true pay-as-you-go, consumption-based model. There’s no need for Ops to spin environments up or down—or to manage the underlying platform or infrastructure. Instead, data scientists can self-manage and self-provision resources in a repeatable manner and connect to data sources in the cloud, on-premises, and at the edge.
Data scientists can access the self-service solution to choose templates, run jobs quickly, and easily leverage the power of containers. With greater self-management of IT resources and data science tools, data scientists have more time to innovate rapidly to drive the business forward.
Accelerate speed to business insights with DSaaS
Once you’re able to explore data science on the job, data scientists will be armed to generate breakthroughs and better predictive models, while driving real business impact.
- Reduce time and inefficiencies.
Do away with the long infrastructure provision times and the misallocation of resources.
- Drive up productivity with self-service.
Entire IT teams can now choose their own tools, applications, and storage needs for the job.
- Simplicity and speed to market.
Simple, one click access for anyone to quickly get up and running on AI and ML technologies.
- Democratize AI to transform your business.
AI is important to every business and industry including healthcare, retail, manufacturing, financial services, and technology. More AI-based systems can help people quickly diagnose diseases, discover drug treatments, speed up production processes, detect fraud, prevent security breaches, boost overall business performance and more.
Free container sandbox offer for qualified, enterprise accounts
Organizations can take advantage of this opportunity to test their workload application in ORock’s compute, storage, and network cloud infrastructure by applying for the free container sandbox offer.
About the author:
Stephen Lucas is currently Vice President of Product Management at ORock Technologies. Since May of 2019, he has led ORock’s product roadmap for the company’s portfolio of cloud and IT infrastructure solutions. Prior to joining ORock, he was Director of Cloud Product Management and Strategy at Arrow Electronics, responsible for the global ArrowSphere cloud platform and working with cloud technology suppliers to bring engaging new cloud products to Arrow’s global partner network. Prior to that, he was Director of Cloud Strategy and Product Management at ASG Software Solutions. Mr. Lucas has held a number of leadership and product management roles at global enterprises, including CommerceHub, First Data Corporation, Election.com and Citibank. He holds a Bachelor of Science degree in Business Administration from Marist College and an MBA from Fordham Gabelli School of Business.
Hewlett Packard Enterprise
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