MapR Technologies is the latest cloud firm to further embrace the seemingly unstoppable creep of Kubernetes across the ecosystem.
The company is adding support for the container orchestrator to its Converged Data Platform. This integration is labeled as the company’s data fabric for Kubernetes. It provides persistent storage for containers and supports the deployment of stateful containerized applications.
The extension also provides scheduled automation for multi-tenant, containerized, and non-containerized applications regardless of their location in the MapR cluster. And it adds the ability to differentiate data services within a cloud using data synchronization across availability zones; it provides cross-cloud data bursting to support cloud neutral deployments; and it supports onboarding from on-premises and private cloud deployments to public cloud.
Jack Norris, senior vice president of data and applications at MapR, said the new product basically provides access to all an organization’s data within and across clouds and on-premises deployments.
“Containers have made it harder in some cases to share data across an organization because if that container goes away, the data running inside of that container goes with it,” Norris said. “That’s where the data fabric comes in. We can scale it to manage the data regardless of where it’s located, even if a container is no longer running.”
A data fabric architecture is designed to allow an organization access to resources across different topologies. It’s sort of a management console that can see into what are traditionally different data silos.
Containers were initially viewed as a perfect match for stateless applications that did not require stored data to operate or support a running application. These were typically web services that acted as a go-between for any storage needs. Any actual storage within a stateless container was ephemeral, and thus a restart flushed out stored data.
However, as container use cases have evolved, stateful models have matured. These allow containers to maintain stored data even if a container is restarted and can support more developed applications. This model has become critical for enterprises that are running more advanced applications within containers.
Norris noted that some of these issues have stunted the adoption of containers within organizations.
“A lot of the reason for hesitancy is that many have not seen a clear way forward to address their specific application needs,” Norris said. “We think we can help pave the way for faster adoption beyond just supporting Kubernetes and provide an easy way to generate [a return on investment].”
The MapR move appears similar to one initiated earlier this year by Hewlett Packard Enterprise and Portworx. That partnership included the release of a reference configuration that uses Kubernetes to offer enterprises a quick way to deploy and manage stateful container workloads.
However, Norris said MapR’s platform is different because it tackles complexity at the source rather than installing an abstraction layer to hide the complexity. He added that this also allows for better overall performance.
“We have heard from analysts that some of the other solutions out there do work in small volumes, but as use broadens, latency, security, and performance issues will increase,” Norris said.