In the future, the data center’s storage architecture should be able to scale elastically, automatically adapting to performance demands. It should also be more than just reliable; it should be self-healing, and deliver these capabilities with cloud economics. This future sounds great, but how is an organization that today faces fragmented server architectures (physical/virtual), hardware silos, and disparate data services supposed to get there? Startup Springpath thinks it has the answer; a software-defined storage solution that can address the realities of today while delivering the promises of the future.
What is Springpath?
Springpath enters the increasingly crowded software-defined storage (SDS) market that creates a hyper-converged architecture. Their software can run on VMware, Microsoft Hyper-V, OpenStack, or Docker. Unlike other SDS solutions, the cluster can support the above hypervisors or frameworks. The software deploys as a VM in either VMware or Hyper-V, making initial implementation and testing straight-forward.
Once the Springpath controller software is deployed it creates a cluster and aggregates the local storage capacity on each node into a pool of storage accessible from any node or VM. This eliminates the need for a legacy storage infrastructure. The software provides a common set of data services like snapshots, clones, replication, data placement, data optimization, and data persistence, all delivered from management interfaces that one is already used to, like VMware vCenter or Openstack Horizon.
Springpath also lays the groundwork for cloud economics. The software is purchased in a subscription model. The subscription is based on a per server basis, independent of the # of CPU’s or capacity in the server, and includes all the above features and support. As a result, the software is easy to begin testing and implementing and easy to consume.
SDS Built From The Ground Up
When coming to market a company faces many decisions, one of the keys being whether they use open source code or develop all the software themselves in order to leverage the latest development tools and understanding of the technology. The open source route gets a company to market faster, but the build it yourself approach should provide leaner, more robust code.
Springpath chose the latter option. Their software created a log structured architecture that can lay out the data across the cluster in a manner that allows for granular data management, better resiliency and storage efficiency. This allows them to deliver all of the above features at great scale, with minimal impact on performance.
The software-defined storage market is crowded and it is compounded by many legacy vendors claiming that they too are software defined. But even in the software-only part of the SDS market many vendors leverage legacy, often open source code. There are advantages to the open source approach, like time to market and a large testing population. There are also downsides to open source.
For example, optimization of newer data services, like data placement, to take advantage of flash performance or deduplication to drive down storage costs, can be more difficult. Springpath believes that their investment in time has paid off in lean, robust and high performance code that data centers will appreciate.