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What hyperscale storage really means

Rob Whiteley | March 3, 2016
Commodity-based and software-defined, hyperscale infrastructure picks up where hyperconvergence leaves off

Let's be clear: Hyperscale isn't about how large you are.

Organizations don't have to be huge to leverage hyperscale solutions. But that's exactly what many IT infrastructure, operations, and devops pros think when they first learn about hyperscale.

The prevailing belief is that hyperscale architecture is meant for extremely large infrastructures -- like those operated by LinkedIn, Amazon, or Netflix -- because it scales to thousands of instances and petabytes of data. As it turns out, it's better to think of hyperscale as describing an approachrather than size. It's about automation, orchestration, and building IT that intelligently scales as and when the business needs it. Hyperscale deployments can and should start small, then scale indefinitely. They should also allow you to independently scale only the portion of the infrastructure that needs it, which is counter to another emerging enterprise data center trend, hyperconvergence.

Confused yet? If so, you're not alone. Let's dive in a bit deeper.

Defining hyperscale

The concept of building a hyperscale architecture is muddied by many tangential terms. In particular, we see customers confused about hyperconverged, hyperscale (or Web-scale), converged, software-defined, and commodity-based infrastructure.

Let's take a moment to clarify definitions on these ingredient terms:

  • Software-defined: Infrastructure where the functionality is completely decoupled from the underlying hardware and is both extensible and programmatic. Read this post for our elaboration on software-defined storagein particular.
  • Commodity-based: Infrastructure built atop commodity or industry-standard infrastructure, usually an x86 rack-mount or blade server. As we've written in the past, don't conflate commodity with cheap.
  • Converged: A scale-out architecture where server, storage, network, and virtualization/containerization components are tied together as a pretested, pre-integrated solution. Components are still distinct in this architecture.
  • Hyperconverged: A scale-out architecture that takes converged infrastructure one step further by combining software-defined components atop commodity hardware, packaged as a single solution -- often a single appliance. Components are no longer distinct.
  • Hyperscale: A scale-out architecture that is also software-defined and commodity-based, but where the server, storage, network, and virtualization/containerization resources remain separate. Each component is distinct and can be independently scaled.

In summary, think of hyperconverged infrastructure as the modern, logical extreme of converged systems, whereas hyperscale is the modern, logical extreme of how we've been building data centers for 30 years. Both make sense for specific environments, as shown below.

hyperconverged vs hyperscale

Hyperscale and hyperconverged

At Hedvig, we strive to deliver a storage solution that can be flexibly tailored for any workload, from private clouds, including Docker and OpenStack, to big data deployments running Hadoop or NoSQL to more traditional server virtualization, disaster recovery, backup, and archiving. The Hedvig Distributed Storage Platform virtualizes and aggregates flash and spinning disk in a server cluster or cloud, presenting it as a single, elastic storage system that can be accessed by file, block, or object interfaces.


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