Software-Defined Storage: It’s Real but Defining It Can Be a Real Trick


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If you Google “software-defined storage” (SDS) you’ll come across some good informative articles. You’ll also come across equally informative articles that complain about the term, charging it with being more a marketing gimmick than a technical term.

Software-defined storage is certainly a broad term. Various storage vendors define SDS quite differently for different segments of the market.

Let’s start with the foundational definition of SDS and see how vendor products fit.

SDS Definition

In general (very general), SDS decouples the underlying storage hardware from the data services layer and automates storage management functions across multiple devices. Individual arrays may have more advanced data services and management functionality. SDS increases overall storage infrastructure value by running on commodity storage or adding centralized data services onto existing ones.

There is no industry-wide SDS standard but the Storage Networking Industry Association (SNIA) has taken a good stab at a definition. SNIA defines SDS as "virtualized storage with a service management interface." The interface pools storage and presents it as storage tiers to applications using appropriate protocols and delivers data services across the virtual infrastructure regardless of the underlying hardware’s capabilities (or the lack thereof). According to SNIA, SDS should also include the following:

  • Automate it. Since one of SDS's big selling points is simplified management, automated storage maintenance is a given. Ideally, simplification extends to the administrative interface, so admins can easily build policies and monitor them.
  • Give it standard interfaces. This is a rock-bottom requirement for SNIA’s SDS definition: centrally managing, provisioning and protecting across multiple storage devices. Not every SDS product will support every type of protocol or data type, but most support file and block, and many support object as well.
  • Scale it. One of the foundational reasons for the existence of SDS is easy scalability. Hot node or drive replacement is critical to scaling the background storage capacity without disrupting availability or performance. Provisioning storage pools for the new hardware should be dynamic and automated.
  • Make storage consumption transparent. Automation is a central SDS capability, but a service portal should also let admins monitor storage consumption against resources and budget.
  • Flexibly deliver it. Storage defined software may execute from a variety of sources and still be SDS. Examples include physical and/or virtual appliances, storage systems built on commodity servers and internal disks, external hosts, and SDS hypervisors that provide advanced data services to all-flash arrays.

What’s the Difference Between SDS and Storage Virtualization?

Some people lump SDS and storage virtualization together. SDS is built on storage virtualization, and the two domains have a lot in common.

But they are not the same thing — not yet anyway.

As product development continues, they may well merge into a single hypervisor-controlled storage virtualization and automation platform. For right now, here’s the difference:

  • Storage virtualization is all about abstracting storage. The virtualization layer provides servers with a logical view of underlying storage resources. The hypervisor combines storage into logical pools and centralizes policy-driven storage management and as-needed provisioning.
  • Software-defined storage enables storage pools too, but it is more about abstracting storage management and data protection capabilities — usually replication, dedupe, and snapshots — from underlying storage to the SDS hypervisor. Centralized automation and management operates across distributed storage devices and provides centralized data services to multiple storage devices.

SDS Market Drivers

The explosive growth of data ultimately drives the move to software-defined storage. Storage must be highly scalable to ingest massive data without sacrificing performance. It also must rapidly provision and pool new storage resources across storage devices — and it needs to do this cost-effectively.

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