If you are planning an infrastructure refresh or designing a greenfield data center from scratch, the hype around converged infrastructure, hyperconverged infrastructure (HCI) and hyperscale might have you scratching your head. In this blog, I'll compare and contrast the three approaches and consider scenarios where one infrastructure architecture would be a better fit than the others.
Converged infrastructure (CI) incorporates compute, storage and networking in a pre-packaged, turnkey solution. The primary driver behind convergence was server virtualization: expanding the flexibility of server virtualization to storage and network components. With CI, administrators could use automation and management tools to control the core components of the data center. This allowed for a single admin to provision, de-provision and make any compute, storage or networking changes on the fly.
Converged infrastructure platforms use the same silo-centric infrastructure components of traditional data centers. They’re simply pre-architected and pre-configured by the manufacturers. The glue that unifies the components is specialized management software. One of the earliest and most popular CI examples is Virtual Computing Environment (VCE). This was a joint venture by Cisco Systems, EMC, and VMware that developed and sold various sized converged infrastructure solutions known as Vblock. Today, Vblock systems are sold by the combined Dell-EMC entity, Dell Technologies.
CI solutions are a great choice for infrastructure pros who want an all-in-one solution that’s easy to buy and pre-packaged direct from the factory. CI is also easier from a support standpoint. If you maintain support contracts on your CI system, the manufacture will assist in troubleshooting end-to-end. That said, many vendors are shifting their focus towards hyperconverged infrastructures.
HCI builds on CI. In addition to combining the three core components of a data center together, hyperconverged infrastructure leverages software to integrate compute, network and storage into a single unit as opposed to using separate components. This architecture design offers performance advantages and eliminates a great deal of physical cabling compared to silo- and CI-based data centers.
Hyperconverged solutions also provide far more capability in terms of unified management and orchestration. The mobility of applications and data is greatly improved, as is the setup and management of functions like backups, snapshots, and restores. These operational efficiencies make HCI architectures more attractive from a cost-benefit analysis when compared to traditional converged infrastructure solutions.
In the end, a hyperconverged solution is all about simplicity and speed. A great use case for HCI would be a new virtual desktop infrastructure (VDI) deployment. Using the orchestration and automation tools available, you have the ideal platform to easily roll out hundreds or thousands of virtual desktops.
The key attribute of hyperscale computing is the de-coupling of compute, network and storage software from the hardware. That’s right, while HCI combined everything into a single chassis, hyperscale decouples the components.
This approach, as practiced by hyperscale companies like Facebook and Google, provides more flexibility than hyperconverged solutions, which tend to grow in a linear fashion. For example, if you need more storage on your HCI system, you typically must add a node blade that includes both compute and built-in storage. Some hyperconverged solutions are better than others in this regard, but most fall prey to linear scaling problems if your workloads don’t scale in step.
Another benefit of hyperscale architectures is that you can manage both virtual and bare metal servers on a single system. This is ideal for databases that tend to operate in a non-virtualized manner. Hyperscale is most useful in situations where you need to scale-out one resource independently from the others. A good example is IoT because it requires a lot of data storage, but not much compute. A hyperscale architecture also helps in situations where it’s beneficial to continue operating bare metal compute resources, yet manage storage resources in elastic pools.