Robin.io this week announced the availability of the pay-as-you-go pricing model for Robin Cloud Native Storage (CNS) on Red Hat Marketplace. Robin.io customers can now pay for hourly usage of Robin CNS when purchased on Red Hat Marketplace. This gives them the flexibility to tie their project budgeting to consumption, according to the company.
The dynamic pricing model no longer forces Robin.io customers to commit to fixed pricing up front. The Red Hat Marketplace is a “digital ecosystem” that makes it easier to access certified software for container-based environments.
Facilitating flexible deployment
Robin CNS enables enterprises and 5G service providers to deliver complex application pipelines as a service, according to Robin.io. Built on industry-standard Kubernetes, Robin allows developers and platform engineers to rapidly deploy and easily manage data- and network-centric applications.
Such applications include big data, NoSQL and 5G, according to the company. Robin CNS enables such deployments independent of underlying infrastructure resources, they say.
The service brings advanced data management capabilities to OpenShift, according to the company. Robin CNS installs natively on OpenShift and provides block and file storage for databases, data analytics, and AI/ML applications. Robin.io claims its CNS simplifies storage and data management to enable developers to manage stateful applications.
Robin CNS’s flexibility helps accommodate even ephemeral workloads
Ankur Desai, director of product, for Robin.io, explained the advantages of the new pricing model. “The flexibility to pay for hourly consumption of Robin CNS provides Red Hat Marketplace customers the ability to quickly deploy our industry-leading storage solution for ephemeral workloads,” he said.
“Customers can now pay only for the hourly usage of Robin CNS when they run ephemeral workloads such as ETL processing, AI/ML data preprocessing and ad-hoc data analysis on Red Hat OpenShift.
That process can help users with flexible licensing terms that can reduce costs, Desai explained. This in turn would encourage experimentation with new features and innovation, he added.