7 Critical Differences: Cloud vs Hyperconvergence vs Converged

Adding "hyper" to convergence allows IT organizations to lower costs and increase performance using intelligent software and standard hardware.

By Dipti Parmar

By Dipti Parmar March 13, 2020

What is convergence in technology? For the uninitiated, it is the eventual merging of computing, storage, and networking technologies – whether previously related or not – which operate as an integrated and unified system that performs one or more business functions. As a result of sustained technological convergence over the past three decades, today, IT is inseparable from the internet, telecom, media, and consumer electronics.

When it comes to IT in the enterprise, convergence is personified by today’s multicloud systems that enable IT management from a single interface with lower operational costs, improved performance for every application, better data governance, and no vendor lock-in. A Hyperconverged Infrastructure (HCI) is the most recent development in Data Center Management (DCM) that enables data centers to go from "cost centers" to sources of innovation, revenue, and business value.

Source: Data Center Frontier

So what puts the “hyper” in HCI? What makes hyperconvergence worth the effort to migrate from a converged configuration that already consolidates hardware and software, improves integration between different systems, and simplifies IT management?

The difference between HCI and CI is that hyperconvergence removes the few remaining downsides of convergence, moving infrastructure into a truly software-defined data center (SDDC), optimizing utilization rates, increasing IT agility, and enabling management from a single console. Here are some of the major benefits for enterprises ready to shift their focus – and dollars – from converged infrastructure to HCI with more resources dedicated to business goals.

Accelerated performance with integrated virtualization

HCI configurations have multiple nodes connected to Direct Access Storage. BMC informs us that the “converged architecture storage is attached directly to the physical server” whereas HCI “has a storage controller function that runs as a service on every node in the cluster.”

This shows HCI’s advantage in two key ways:

  • Improved throughput and I/O speeds: Less cabling and shorter travel time mean the read/write functions don’t slow down processing too much.

  • Data availability assurance: With the storage structures in HCI, data is available to the processing partners that need it most based on data-usage habits, not assumptions. This includes Data Path Redundancy, which creates alternate paths for access should a specific VM become unavailable.

Higher efficiency in DCM from the shop floor to the top floor

Increased system resource utilization and true hardware independence are the immediately visible benefits of HCI compared to CI. Since hyperconvergence is 100% software-defined, there is no lock-in to proprietary hardware. This will become more significant as businesses continue to evolve and utilize more HCI features while making better and increased use of cloud technology.

Here’s how your data center becomes more efficient with hyperconvergence:

  • Time to market goes down, and agility goes up as the lead-time is minimized. This is made possible by VM replication through known good images and templates with or without changes to configuration settings.

  • Self-service provisioning allows staff working on development, data science, application testing, and other workloads to request and receive environments as needed.

Reduce complexity with a “Single Pane of Glass” to manage resources

A single view of multiple configurations, both for administration and analysis, is what HCI brings to the table. This can include on-premise, hybrid and private clouds, native cloud apps, remote and branch locations, as well as multicloud environments.

Source: GigaOm Hybrid & Multicloud Complexity Whitepaper

The abstraction layer that sits above the multiple public and private cloud interfaces, as well as automation services, means that management can account for differences in disparate systems and centrally govern them from a unified console.

Staff can focus more on business goals and less on firefighting

Companies that have adopted HCI are seeing a drop in the overtime that management and support staff put in each week. This bit of work-life balance takes specialists out of constant firefighting mode and opens the opportunity to focus on more proactive initiatives for the business. How much value that may provide to the enterprise overall isn’t easy to calculate but falls into the “known benefits” category of business values.

Source: Actual Tech Media

For digital transformation efforts, companies need business analysts and IT generalists more than infrastructure specialists. Those enterprises engaged in HCI implementation are more likely to see a redistribution in hiring, with an increase in both the generalist and data analyst categories. Conversely, specialist jobs in security, database and storage administration, and application development might see decreases in hiring.

Support more differentiated workloads

Being completely software-defined, HCI doesn't have the limitations that keep a CI directed to Virtual Desktop Infrastructure (VDI) applications. CI configurations were generally put together for a specific purpose, each with its own support requirements. 

While CI is still being used for more applications at present, HCI can be optimized to run virtually any type of business application out there (and still hit operational target metrics):

  • Business-critical applications

  • Messaging and collaboration applications

  • Server virtualization and private cloud

  • Big Data and cloud-native applications

  • Virtual Desktop Infrastructure (VDI)

  • Remote Office and Branch Office (ROBO)

  • Development and testing applications

Upgrades and maintenance with zero downtime

In a true HCI, there is no “spare” hardware for separate environments. Adding and removing nodes is done on-demand and in minutes. Migrating specific processing functions to a different node for maintenance is part of built-in functionality that most HCI solution providers offer – processing is simply moved to the optimal resource without disruption. Once the components being updated are addressed, the maintenance window is closed, and processing returns to its “normal” state.

Source: Nutanix

Workload balancing based on data utilization

An HCI facilitates virtual computing platforms that scale-out linearly, have the ability to self-heal, are always available, and with the capability to handle prolonged workload bursts at optimized capacity. Nodes can be rapidly added to incorporate new applications and workloads. Scaling down is just as straightforward. Further, the workload can be shifted to compatible nodes on demand.

All of these capabilities allow the enterprise to maintain a “right-sized” data center all the time. HCI software can highlight processing surplus and shortages based on actual usage and peak times. The addition of AI – which is part of most HCI configurations and products these days – can anticipate issues and recommend course corrections for resource usage, improving TCO in the process.

Adding the “Hyper” to Convergence

Migrating to an HCI in phases is a best practice supported by the ability to run infrastructure resiliency and reliability tests continuously. HCI is truly a different kind of data center – smaller, tighter, leaner, and more robust than the standard data center configurations, including CI.

Understanding the differences and knowing some of the benefits is just the first step. At this point, there is still a place for CI in specific instances. However, operational requirements and technological advances are making the shift to HCI inevitable. The question for the enterprise is when, not if.

Featured Image: Pixabay

Dipti Parmar is a contributing writer. She has written for CIO.com, Entrepreneur, CMO.com and Inc. magazine. Follow her on Twitter @dipTparmar.

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