Edge Computing vs On-Premises: A Comparison

Organizations across industries are expanding their digital capabilities and global reach by deploying Internet of Things (IoT) devices, automated operational technology (OT) sites, branch offices, and other tech at the network’s edges. Edge technology transmits vast quantities of data to and from data warehouses, machine learning training systems, and software applications. Traditionally, organizations host some or all of these services in centralized data centers, which is known as on-premises computing.

This approach creates challenges that impact the efficiency and safety of edge operations. As edge data volumes grow, so do MPLS bandwidth costs. Large data transmissions to and from the edge are also at risk of interception by malicious actors. The best way to solve this problem is with edge computing, which moves data processing applications and systems to the edges of the network to run alongside the devices that generate most of the edge data.

This guide defines edge computing vs on-premises computing in detail before analyzing the advantages and challenges involved with each approach.

Defining edge computing vs on-premises computing

On-premises computing systems are physical or virtual resources that live in a traditional data center. Despite the name, these systems don’t necessarily reside in the same physical premises as the main business, with many companies using colocation data centers owned by third parties. Organizations have complete control over the physical and virtual infrastructure, unlike in private or public cloud deployments. The defining characteristic of on-premises computing is that most or all enterprise applications and digital services reside in a centralized location, with most network traffic and data transmissions flowing through it.

Edge computing systems are physical and virtual data processing resources that companies deploy alongside the edge devices that generate the most data. Examples include installing machine learning software at a remote manufacturing site to gain maintenance insights into remote SCADA (supervisory control and data acquisition) systems, or running a data analytics app on a chip installed in a wearable medical sensor to provide patients with real-time health feedback. Edge computing has many potential use cases and deployment models, but the defining characteristic is proximity to the sources of edge-generated data.

The advantages of edge computing vs on-premises

The benefits of edge computing compared to on-premises include:

• Improved workload efficiency – Edge computing reduces network traffic bottlenecks and latency because data stays on the local network or even on the same device. This improves the overall speed, performance, and efficiency of all enterprise applications and services.

• Bandwidth cost reduction – Edge computing reduces the volume of data transmitted over MPLS links between edge sites and the central data center. The cost for MPLS bandwidth is typically very high, so edge computing decreases operational costs at branch offices and other edge business sites.

• Better data security – Any time companies transmit data off-site, there’s a risk of interception by cybercriminals. Edge computing reduces the attack surface by keeping valuable data on the local network, which improves data security and simplifies data privacy compliance.

The challenges of edge computing vs on-premises

The challenges of edge computing compared to on-premises include:

• Data storage restraints – The typical edge deployment is much smaller than a centralized data center and has fewer data storage resources, making it difficult to hold on to data long enough to process it with edge applications.

• Fewer security controls – Edge deployments often lack the robust physical security controls utilized by data centers, such as security guards and biometric door locks, creating the need for edge-specific security solutions to protect data and devices.

• Edge management and orchestration – Edge sites are difficult for centralized IT operations teams to monitor and troubleshoot, especially if an equipment failure, ransomware attack, or natural disaster takes down the network.

Comparing edge computing vs on-premises

 

Edge computing solves many of the challenges involved in processing data at the edges of the network, but it also creates new problems. The best way to ensure edge computing success is to start with a comprehensive strategy that identifies potential hurdles and the technology and operational practices needed to overcome them. For example, zero trust security policies, proactive patch management, and isolated management infrastructure (IMI) help organizations defend edge deployments without the benefit of secure data center facilities. Environmental monitoring, out-of-band (OOB) management, and edge management and orchestration (EMO) platforms all give teams greater control over remote edge infrastructure.

ZPE Systems provides edge network solutions to help you overcome your biggest challenges. Nodegrid integrated edge routers support VM and Docker hosting for your choice of third-party edge computing and security applications, allowing you to devote more hardware budget (and rack space) to data storage and other critical infrastructure. Robust onboard security features like TPM and geofencing defend Nodegrid hardware from tampering and compromise for better edge security coverage.

All Nodegrid devices provide OOB management to give teams continuous remote access to edge infrastructure, allowing them to quickly recover from outages, equipment failures, and cyberattacks. Plus, our vendor-neutral management software seamlessly integrates all your edge solutions to create a unified EMO platform that streamlines edge operations.

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