If you’ve spent any time in the networking trenches, you’ve no doubt spent many hours puzzling over an assortment of network topology charts. These visual representations of a network tell an important story of how the various components in a network are connected to each other and how data is transferred between its constituent nodes.

These topologies are more than just fancy diagrams – they essentially serve as a living blueprint that describes how a network functions and data is routed. Choosing the right topology will go a long way towards improving the performance and efficiency of your network, as well as help to rationalize how certain resources should be allocated and can provide a roadmap that’s essential for troubleshooting when network connectivity issues arise.

Over the past few decades, a wide variety of network topologies have been established, each of which caters to a specific environment or use case. However, as the network continues its inexorable march towards the edge – where connectivity can be intermittent and skilled resources are scarce – we will likely see a number of new topologies arise that take these constraints into consideration.

As Alan R. Earls, author of The Gorilla Guide to: Enabling IT at the Edge, notes in his explanation of the most likely edge topologies: “While the never-ending evolution of information technologies makes it hard to predict exactly what topologies will emerge or seem most appealing in the future, there are currently several strong contenders for edge computing.” These five edge topologies include:

1. Regional Data Center Edge: CDN, Telecom DC, Colocation.

This might be a service provider configuration with multiple tenants and, in comparison with other edge computing scenarios, is typically a very large-scale operation that differs from a traditional data center only in its relationship to an even larger central data center and in usually having a narrower focus.

2. Local Data Center Edge: Small Data Center, Micro Data Center.

This type of edge computing is likely general-service-oriented, perhaps for a remote office or branch office and is characterized by low or no staffing.

3. Gateway Edge: Intelligent Local/Field Gateway

This typically comprises a small cell or access point, such as a video management software (VMS) surveillance system and offers zero touch provisioning (ZTP) and configuration management.

4. Device Edge: Embedded Computing Devices and Traditional PLCs.

This type of edge, typically a single machine or work cell, has only enough intelligence to assist with a specific operation and provide some de- gree of reporting.

5. Compute Edge: Edge Server/Storage Outside of a Data Center.

Examples of this type of true edge computing potentially have the ability to include specialized services, such as video analytics-based applications and likely include ZTP.

It’s important to note that these topologies aren’t rigid. There are gray areas and some edge implementations can actually include multiple topologies. However, in most instances, one is clearly predominant.

To learn more about what future edge topologies might look like, download Scale Computing’s free ebook: “The Gorilla Guide to: Enabling IT at the Edge”

As the old Irish saying goes, the luck is in believing you’re lucky. But you don’t need luck with Scale Computing…you just need edge computing. With edge computing, you can run applications and process data outside centralized data centers, at the edge of your network closest to where that data is created and utilized. Centrally monitor and manage hundreds or thousands of distributed edge infrastructure deployments with few or no on-site IT personnel.

The award winning Scale Computing HC3 Edge series brings on-premises edge computing with high availability and disaster recovery to remote locations at an affordable entry level cost. All edge models can be deployed quickly, managed locally or remotely, and can self-heal almost instantly. Enjoy affordable edge computing infrastructure that is reliable, easy to deploy, and easy to use.

Take advantage today of Scale Computing’s HC3 Edge Computing Trial, a no cost program for qualified customers to try the Scale Computing HE150 edge computing platform. Built specifically for multi-site deployments that need highly available infrastructure on-premises, with remote management, the HE150 can be deployed almost anywhere, without requiring a rack or server closet. Get hands-on experience with self-healing, right-sized infrastructure that runs critical applications right where they’re needed.

Scale Computing joined forces with select reseller partners from the award-winning Scale Computing Partner Community to offer this innovative, right-sized, all-flash, NVMe storage-based compute appliance that delivers all of the simplicity, efficiency, and enterprise-ready virtualization associated with Scale Computing’s HC3 platform. Built specifically for multi-site deployments that need highly available infrastructure on-premises and remote management, the HE150 can be deployed almost anywhere, without requiring a rack or server closet. Taking up only the space needed to stack three smartphones, it also includes disaster recovery, high availability clustering, rolling upgrades and integrated data protection.

Details of the Edge Trial include:

• HC3 self-healing technology that keeps applications running
• Simplified deployment and management
• Minimal training, with no onsite IT expertise needed
• Do more with less hardware costs and fewer resources
• Single vendor support experience
• Available as a 3+ node cluster or 1 node platform
• Qualification criteria required (10+ locations)
• The trial offer is only valid in North America, United Kingdom, Benelux, Germany, France, Switzerland, Austria and South Africa

Edge computing has been one of the hottest buzzwords in IT over the past year, and it’s easy to see why. Businesses are implementing innovative workloads using new technologies that require on-premises processing of data due to the requirements of lower latencies, the volume of data being generated, autonomy or even regulation that requires it to run outside the cloud or primary data center. In this article, we’ll take a closer look at how edge computing is transforming the industry—including how enterprises can best utilize edge computing to fuel innovation in their business strategies while protecting their data assets at the same time.

Organizations looking to deploy edge computing solutions on hyperconverged infrastructure are attracted by three main advantages of edge computing: performance, security, and cost-efficiency.

Edge computing can boost application performance in several ways: The speed at which data is processed increases by reducing latency and allowing critical operations to occur at local nodes. All of these benefits improve the overall end-user experience.

In terms of flexibility, edge computing technologies offer clear benefits over their more traditional counterparts deployed in conventional data centers.

Where Edge Computing and Hyperconverged Infrastructure Intersect

Edge computing is one of those terms that’s been thrown around a lot lately, but what does it mean? Edge computing involves placing compute resources closer to where data is generated and used rather than sending all data back to centralized servers or the public cloud. This enables the adoption of new applications and use cases such as AI/ML, augmented reality, computer vision, etc. where additional data generated and processed at the edge has a direct impact on the organization (higher revenues, lower costs, or potentially both depending on the environment). The benefit is clear: lower latency times and better performance for applications.

Edge computing requires businesses to rethink their relationship with managing infrastructure, but many CIOs may not fully understand how an enterprise can leverage edge computing. Often unique in edge computing deployments are the lack of on-premises IT expertise to deploy and manage infrastructure, and legacy workloads that need to be run on-premises with newer workloads – challenges solved by edge-ready HCI.

What is hyperconverged infrastructure (HCI)? HCI pools together resources into an infrastructure that can be managed with cloud-like ease for the entire stack (hypervisor, storage, etc.). Virtualization software turns many high-performing processors into multiple virtual machines with their own virtual processors, thus allowing each OS to run its own set of programs independent of other OS running on other processors. This means that if you need more processing power in an application or system, you can add more virtual processor cores to an existing virtual machine (VM) without affecting other processes running on other VMs.

Enterprise Use Cases

Edge computing offers many use cases for hyperconverged infrastructure in addition to those already mentioned above, including cloud services, mobile/IoT device data collection and storage, business continuity/disaster recovery, and Industry 4.0 Manufacturing Automation.

Edge computing can take advantage of HCI by using shared storage between compute nodes and allowing users to manage all their edge computing workloads from a single management interface (like that of Scale Computing’s HC3). This streamlined process removes network latency caused by transferring data between sites. By storing data on edge servers that reside as close as possible to its point of origin, we reduce network traffic and make business insights actionable faster than ever before.

Today’s enterprises rapidly move away from managing isolated IT systems. They’re modernizing to gain operational excellence through integrated systems with built-in cybersecurity protections and designed for digital transformation with multiple application profiles. Using edge computing infrastructure platforms with built-in high availability (HA) will decrease costly downtime at major companies that rely on highly distributed equipment assets in each global region where they operate.

Edge Computing in Action with HCI

Now that edge computing has become a reality for enterprises, and as HCI continues to demonstrate its viability in enterprise data centers, there’s no doubt that we’ll see more and more edge computing use cases in years to come.

Edge computing has several advantages over centralized cloud architectures (which involve transferring large amounts of data from sites to a central location), including cost savings, improved performance, and higher levels of security. This makes it an ideal solution for both large businesses—companies with multiple sites that are tired of paying expensive bandwidth bills—and smaller companies that can’t afford traditional cloud costs.

The downside is that storing all your data on-premises means you have limited access to it if something goes wrong or needs maintenance. In situations like these, having an edge hyperconverged infrastructure could be just what the enterprise needs to ensure business continuity at every level. With HCI, everything sits onsite; system components are close by, so they can easily communicate with each other and quickly respond when problems arise.

HCI Changes Everything

Companies are still trying to figure out what edge computing is and how it works for them. Luckily, you don’t have to learn edge computing from scratch. The best way for most enterprises to start leveraging HCI for edge computing can be done by deploying software on edge-ready hardware that scales up when necessary, but scales down if the number of workloads decreases.

All of these advantages come with minimal costs — so much so that leading industry experts think edge computing will make hyperconverged infrastructure ubiquitous in companies of any size. And if there’s one sure thing about pervasive hyperconvergence, it’s going to change everything we know about business as usual.

Want to see edge computing and HCI in action? Request a demo today!