Providing Out-of-Band Connectivity to Mission-Critical IT Resources

What is Passive Optical Networking?

What is Passive Optical Networking (PON)?

Passive optical networking (PON) is a high-speed broadband technology that enables the delivery of multiple services over a single fiber optic cable. XGS-PON – 10G Symmetrical PON –  offers speeds of up to 10 Gbps downstream and 10 Gbps upstream (hence the term ‘symmetrical’), making it ideal for applications such as video streaming, online gaming, and cloud computing.

 

What Problems Does PON Solve for Out-of-Band Management?

PON addresses the issue of efficiency in terms of both uplink costs and bandwidth usage. Traditional POTS lines and dedicated circuits rely on legacy infrastructure that requires regular maintenance. This infrastructure must scale as more out-of-band devices are added to the network, which increases costs and energy consumption. On top of this, using a 10G uplink for a serial console’s 10K traffic is like throwing away 99% of that high bandwidth. Per Gartner’s Market Guide for Optical Transport Systems report (Published 20 November 2023) the best way to “lower cost and energy per transported bit” is by using technologies such as passive optical networking.

Because PON uses passive optical splitters that have no moving parts or powered components between the central hub and end users, PON is much more efficient for deploying serial consoles close to target assets. These out-of-band devices can be deployed in large quantities and close to the network edge, with up to 256 devices sharing one uplink. This reduces cabling and power requirements, and is ideal for MSP and campus operators, where there are many out-of-band devices distributed over long distances. 

 

More About PON: GPON and XGS-PON Technologies

Passive Optical Networking (PON) leverages time-division multiplexing (TDM) and different wavelengths of light to transmit and receive data on a single fiber strand. This allows efficient communication among up to 256 devices over a single fiber. Initially developed for fiber-to-the-home (FTTH) deployments, PON technology has evolved to facilitate the addition of network nodes with minimal infrastructure changes. GPON (gigabit-capable PON) and XGS-PON use different frequencies for upstream and downstream data transmission. The upstream headend, known as the Optical Line Terminal (OLT), manages and coordinates the time slots allocated to downstream Optical Network Units (ONUs) for data transmission.

 

GPON and XGS-PON Support on ZPE Systems’ Nodegrid SR Gateway

ZPE Systems’ Nodegrid SR appliances, which are used as out-of-band access nodes or complete branch gateways, now support GPON and XGS-PON technology (patent pending) via SFP and SFP+ ports. The Nodegrid SR family is offered in multiple form factors to be right-sized for deployments in branch offices, factories, smart buildings, and industrial environments (such as for SCADA).

Having support for GPON and XGS-PON means network engineers now have a flexible choice of high-speed uplink technologies. This versatility makes the Nodegrid SR gateway suitable for edge deployments, where it can establish an OOBI-WAN™ (out-of-band infrastructure WAN) link, and for data centers, where it enhances uplink efficiency. Given the low bandwidth requirements of serial console and out-of-band communications, PON technology is well-suited for these applications. A single fiber strand can be shared among hundreds of out-of-band and serial console devices using passive optical splitters. Organizations can deploy out-of-band devices close to the racks and edges of the network in a cost- and energy-efficient manner. Additionally, ZPE devices support ONU SFPs compatible with third-party OLT headends, ensuring broad interoperability and integration.

 

Benefits of Using XGS-PON with ZPE Systems’ Nodegrid SR Gateway

The benefits of using XGS-PON with ZPE Systems’ Nodegrid SR gateway include:

  • High-Speed Connectivity: XGS-PON delivers symmetrical speeds of up to 10 Gbps, making it ideal for high-bandwidth applications like video streaming, online gaming, and cloud computing. This ensures consistent and high-quality service for end-users.
  • Cost-Effectiveness: Deploying XGS-PON is a cost-effective solution for delivering high-speed broadband services, especially in scenarios where upgrading existing infrastructure may be challenging.
  • Scalability: The Nodegrid SR Gateway, acting as an ONU, can connect up to 256 serial consoles through a single fiber strand. PON’s use of asymmetric wavelengths and TDM enables multiple devices to share the same fiber strand efficiently. Optical splitters, which require no external power, facilitate the sharing of fiber between multiple ONUs, which makes scaling much more cost and energy efficient.
  • Reliability: The Nodegrid SR gateway is proven by service providers worldwide. Its robust design and compatibility with various network configurations make it a reliable choice for delivering high-quality broadband services.

A network diagram showing a PON Uplink on Nodegrid SR Gateway

Figure 1: ZPE Nodegrid SR gateway with XGS-PON ONU support

 

XGS-PON Enhances Efficiency of Out-of-Band

XGS-PON is a significant advancement over traditional, copper-based uplinks. The integration of XGS-PON support in the ZPE Systems Nodegrid SR Gateway allows network architects to deploy a dedicated out-of-band ring that is not only high-speed but also cost-effective, energy-efficient, and capable of covering longer distances. PON technology, with its ability to handle the lower data rates of out-of-band transmissions, is an ideal uplink medium for serial console transmission. The combination of XGS-PON and the Nodegrid SR Gateway provides a powerful and flexible solution for modern network infrastructure.

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Comparing Console Server Hardware

Console servers – also known as serial consoles, console server switches, serial console servers, serial console routers, or terminal servers – are critical for data center infrastructure management. They give administrators a single point of control for devices like servers, switches, and power distribution units (PDUs) so they don’t need to log in to each piece of equipment individually. It also uses multiple network interfaces to provide out-of-band (OOB) management, which creates an isolated network dedicated to infrastructure orchestration and troubleshooting. This OOB network remains accessible during production network outages, offering remote teams a lifeline to recover systems without costly and time-consuming on-site visits. 

Console server hardware can vary significantly across different vendors and use cases. This guide compares console server hardware from the three top vendors and examines four key categories: large data centers, mixed environments, break-fix deployments, and modular solutions.

Console server hardware for large data center deployments

Large and hyperscale data centers can include hundreds or even thousands of individual devices to manage. Teams typically use infrastructure automation, like infrastructure as code (IaC), because managing devices at such a large scale is impossible to do manually. The best console server hardware for high-density data centers will include plenty of managed serial ports, support hundreds of concurrent sessions, and provide support for infrastructure automation.

Click here to compare the hardware specs of the top providers, or read below for more information.

Nodegrid Serial Console Plus (NSCP)

The Nodegrid Serial Console Plus (NSCP) from ZPE Systems is the only console server providing up to 96 RS-232 serial ports in a 1U rack-mounted form factor. Its quad-core Intel processor and robust (as well as upgradable) internal storage and RAM options, as well as its Linux-based Nodegrid OS, support Guest OS and Docker containers for third-party applications. That means the NSCP can directly host infrastructure automation (like Ansible, Puppet, and Chef), security (like Palo Alto’s next-generation firewalls and Secure Access Service Edge), and much more. Plus, it can extend zero-touch provisioning (ZTP) to legacy and mixed-vendor devices that otherwise wouldn’t support automation.

The NSCP also comes packed with hardware security features including BIOS protection, UEFI Secure Boot, self-encrypted disk (SED), Trusted Platform Module (TPM) 2.0, and a multi-site VPN using IPSec, WireGuard, and OpenSSL protocols. Plus, it supports a wide range of USB environmental monitoring sensors to help remote teams control conditions in the data center or colocation facility.

Advantages:

  • Up to 96 managed serial ports in a 1U appliance
  • Intel x86 CPU and 4GB of RAM for 3rd-party Docker and VM apps
  • Extends ZTP and automation to legacy and mixed-vendor infrastructure
  • Robust on-board security features like BIOS protection and TPM 2.0
  • Supports a wide range of USB environmental monitoring sensors
  • Wi-Fi and 5G/4G LTE options available
  • Supports over 1,000 concurrent sessions

Disadvantages:

  • USB ports limited on 96-port model

Opengear CM8100

The Opengear CM8100 comes in two models: the 1G version includes up to 48 managed serial ports, while the 10G version supports up to 96 serial ports in a 2U form factor. Both models have a dual-core ARM Cortex processor and 2GB of RAM, allowing for some automation support with upgraded versions of the Lighthouse management software. They also come with an embedded firewall, IPSec and OpenVPN protocols for a single-site VPN, and TPM 2.0 security.

Advantages:

  • 10G model comes with software-selectable serial ports
  • Supports OpenVPN and IPSec VPNs
  • Fast port speeds

Disadvantages:

  • Automation and ZTP require Lighthouse software upgrade
  • No cellular or Wi-Fi options
  • 96-port model requires 2U of rack space

Perle IOLAN SCG (fixed)

The IOLAN SCG is Perle’s fixed-form-factor console server solution. It supports up to 48 managed serial ports and can extend ZTP to end devices. It comes with onboard security features including an embedded firewall, OpenVPN and IPSec VPN, and AES encryption. However, the IOLAN SCG’s underpowered single-core ARM processor, 1GB of RAM, and 4GB of storage limit its automation capabilities, and it does not integrate with any third-party automation or orchestration solutions. 

Advantages:

  • Supports ZTP for end devices
  • Comprehensive firewall functionality

Disadvantages

  • Very limited CPU, RAM, and flash storage
  • Does not support third-party automation

Comparison Table: Console Server Hardware for Large Data Centers

Nodegrid NSCP Opengear CM8100 Perle IOLAN SCG
Serial Ports 16 / 32 / 48 / 96x RS-232 16 / 32 / 48 / 96x RS-232 16 / 32 / 48x RS-232
Max Port Speed 230,400 bps 230,400 bps 230,000 bps
Network Interfaces

2x SFP+ 

2x ETH

1x Wi-Fi (optional)

2x Dual SIM LTE (optional)

2x ETH 1x ETH
Additional Interfaces

1x RS-232 console

2x USB 3.0 Type A

1x HDMI Output

1x RS-232 console

2x USB 3.0

1x RS-232 console

1x Micro USB w/DB9 Adapter

Environmental Monitoring Any USB sensors
CPU Intel x86_64 Quad-Core ARM Cortex-A9 1.6 GHz Dual-Core ARM 32-bit 500MHz Single-Core
Storage 32GB SSD (upgrades available) 32GB eMMC 4GB Flash
RAM 4GB DDR4 (upgrades available) 2GB DDR4 1GB
Power

Single or Dual AC

Dual DC

Dual AC

Dual DC

Single AC
Form Factor 1U Rack Mounted

1U Rack Mounted (up to 48 ports)

2U Rack Mounted (96 ports)

1U Rack Mounted
Data Sheet Download

CM8100 1G

CM8100 10G

Download

Console server hardware for mixed environments

Data center deployments that include a mix of legacy and modern solutions from multiple vendors benefit from console server hardware that includes software-selectable serial ports. This feature allows administrators to manage devices with straight or rolled RS-232 pinouts from the same console server. 

Click here to compare the hardware specs of the top providers, or read below for more information.

Nodegrid Serial Console S Series

The Nodegrid Serial Console S Series has up to 48 auto-sensing RS-232 serial ports and 14 high-speed managed USB ports, allowing for the control of up to 62 devices. Like the NSCP, the S Series has a quad-core Intel CPU and upgradeable storage and RAM, supporting third-party VMs and containers for automation, orchestration, security, and more. It also comes with the same robust security features to protect the management network.

Advantages:

  • Includes 14 high-speed managed USB ports
  • Intel x86 CPU and 4GBof RAM for 3rd-party Docker and VM apps
  • Supports a wide range of USB environmental monitoring sensors
  • Extends ZTP and automation to legacy and mixed-vendor infrastructure
  • Robust on-board security features like BIOS protection and TPM 2.0
  • Supports 250+ concurrent sessions

Disadvantages

  • Only offers 1Gbps and Ethernet connectivity for OOB

Opengear OM2200

The Opengear OM2200 comes with 16, 32, or 48 software-selectable RS-232 ports, or, with the OM2224-24E model, 24 RS-232 and 24 managed Ethernet ports. It also includes 8 managed USB ports and the option for a V.92 analog modem. It has impressive storage space and 8GB of DDR4 RAM for automated workflows, though, as with all Opengear solutions, the upgraded version of the Lighthouse management software is required for ZTP and NetOps automation support.

Advantages:

  • Optional managed Ethernet ports
  • Optional V.92 analog modem for OOB
  • 64GB of storage and 8GB DDR4 RAM

Disadvantages:

  • Automation and ZTP require Lighthouse software upgrade
  • No cellular or Wi-Fi options

Comparison Table: Console Server Hardware for Mixed Environments

  Nodegrid S Series Opengear OM2200
Serial Ports

16 / 32 / 48x Software Selectable RS-232

14x USB-A serial

16 / 32 / 48x Software Selectable RS-232
8x USB 2.0 serial

 

 

 

(OM2224-24E) 24x Software Selectable RS-232 and 24x Managed Ethernet

Max Port Speed

230,400 bps (RS-232)

921,600 bps (USB)

230,400 bps
Network Interfaces 2x1Gbps or 2x ETH

2x SFP+ or 2x ETH

1x V.92 modem (select models)

Additional Interfaces

1x RS-232 console

1x USB 3.0 Type A

1x HDMI Output

1x RS-232 console

1x Micro USB

2x USB 3.0

Environmental Monitoring Any USB sensors
CPU Intel x86_64 Dual-Core AMD GX-412TC 1.4 GHz Quad-Core
Storage 32GB SSD (upgrades available) 64GB SSD
RAM 4GB DDR4 (upgrades available) 8GB DDR3
Power

Single or Dual AC

Dual DC

Dual AC

Dual DC

Form Factor 1U Rack Mounted 1U Rack Mounted
Data Sheet Download Download

Console server hardware for break-fix deployments

A full-featured console server solution may be too complicated and expensive for certain use cases, especially for organizations just looking for “break-fix” OOB access to remotely troubleshoot and recover from issues. The best console server hardware for this type of deployment provides fast and reliable network access to managed devices without extra features that increase the price and complexity.

Click here to compare the hardware specs of the top providers, or read below for more information.

Nodegrid Serial Console Core Edition (NSCP-CE)

The Nodegrid Serial Console Core Edition (NSCP-CE) provides the same hardware and security features as the NSCP, as well as ZTP, but without the advanced automation capabilities. Its streamlined management and affordable price tag make it ideal for lean, budget-conscious IT departments. And, like all Nodegrid solutions, it comes with the most comprehensive hardware security features in the industry. 

Advantages:

  • Up to 48 managed serial ports in a 1U appliance
  • Extends ZTP and automation to legacy and mixed-vendor infrastructure
  • Robust on-board security features like BIOS protection and TPM
  • Supports a wide range of USB environmental monitoring sensors
  • Analog modem and 5G/4G LTE options available
  • Supports over 100 concurrent sessions

Disadvantages

  •  Supports automation only via ZPE Cloud

Opengear CM7100

The Opengear CM7100 is the previous generation of the CM8100 solution. Its serial and network interface options are the same, but it comes with a weaker, Armada 800 MHz CPU, and there are options for smaller storage and RAM configurations to reduce the price. As with all Opengear console servers, the CM7100 doesn’t support ZTP without paying for an upgraded Lighthouse license, however.

Advantages:

  • Can reduce storage and RAM to save money
  • Supports OpenVPN and IPSec VPNs
  • Fast port speeds

Disadvantages:

  • Automation and ZTP require Lighthouse software upgrade
  • No cellular or Wi-Fi options
  • 96-port model requires 2U of rack space

Comparison Table: Console Server Hardware for Break-Fix Deployments

  Nodegrid NSCP-CE Opengear CM7100
Serial Ports 16 / 32 / 48 / RS-232 16 / 32 / 48 / 96x RS-232
Max Port Speed 230,400 bps 230,400 bps
Network Interfaces

2x SFP ETH

1x Analog modem (optional)

2x 5G/4G LTE (optional)

2x ETH
Additional Interfaces

1x RS-232 console

2x USB 3.0 Type A

1x RS-232 console

2x USB 2.0

Environmental Monitoring Any USB sensors Smoke, water leak, vibration
CPU Intel x86_64 Dual-Core Armada 370 ARMv7 800 MHz
Storage 16GB Flash (upgrades available) 4-64GB storage
RAM 4GB DDR4 (upgrades available) 256MB-2GB DDR3
Power

Dual AC

Dual DC

Single or Dual AC
Form Factor 1U Rack Mounted

1U Rack Mounted (up to 48 ports)

2U Rack Mounted (96 ports)

Data Sheet Download Download

Modular console server hardware for flexible deployments

Modular console servers allow organizations to create customized solutions tailored to their specific deployment and use case. They also support easy scaling by allowing teams to add more managed ports as the network grows, and provide the flexibility to swap-out certain capabilities and customize their hardware and software as the needs of the business change. 

Click here to compare the hardware specs of the top providers, or read below for more information.

Nodegrid Net Services Router (NSR)

The Nodegrid Net Services Router (NSR) has up to five expansion bays that can support any combination of 16 RS-232 or 16 USB serial modules. In addition to managed ports, there are NSR modules for Ethernet (with or without PoE – Power over Ethernet) switch ports, Wi-Fi and dual-SIM cellular, additional SFP ports, extra storage, and compute. 

The NSR comes with an eight-core Intel CPU and 8GB DDR4 RAM, offering the same vendor-neutral Guest OS/Docker support and onboard security features as the NSCP. It can also run virtualized network functions to consolidate an entire networking stack in a single device. This makes the NSR adaptable to nearly any deployment scenario, including hyperscale data centers, edge computing sites, and branch offices.

Advantages:

  • Up to 5 expansion bays provide support for up to 80 managed devices
  • 8GB of DDR4 RAM
  • Robust on-board security features like BIOS protection and TPM 2.0
  • Supports a wide range of USB environmental monitoring sensors
  • Wi-Fi and 5G/4G LTE options available
  • Optional modules for various interfaces, extra storage, and compute

Disadvantages

  • No V.92 modem support

Perle IOLAN SCG L/W/M

The Perle IOLAN SCG modular series is customizable with cellular LTE, Wi-Fi, a V.92 analog modem, or any combination of the three. It also has three expansion bays that support any combination of 16-port RS-232 or 16-port USB modules. Otherwise, this version of the IOLAN SCG comes with the same security features and hardware limitations as the fixed form factor models.

Advantages:

  • Cellular, Wi-Fi, and analog modem options
  • Supports ZTP for end devices
  • Comprehensive firewall functionality

Disadvantages

  • Very limited CPU, RAM, and flash storage
  • Does not support third-party automation

Comparison Table: Modular Console Server Hardware

  Nodegrid NSR Perle IOLAN SCG R/U
Serial Ports

16 / 32 / 48 / 64 / 80x RS-232 with up to 5 serial modules

16 / 32 / 48 / 64 / 80x USB with up to 5 serial modules

Up to 50x RS-232/422/485

Up to 50x USB

Max Port Speed 230,400 bps 230,000 bps
Network Interfaces

1x SFP+ 

1x ETH with PoE in

1x Wi-Fi (optional)

1x Dual SIM LTE (optional)

2x SFP or 2x ETH
Additional Interfaces

1x RS-232 console

2x USB 2.0 Type A

2x GPIO

2x Digital Out

1x VGA

Optional Modules (up to 5):

16x ETH

8x PoE+

16x SFP

8x SFP+

16x USB OCP Debug

1x RS-232 console

1x Micro USB w/DB9 adapter

 

Environmental Monitoring Any USB sensors
CPU Intel x86_64 Quad- or Eight-Core ARM 32-bit 500MHz Single-Core
Storage 32GB SSD (upgrades available) 4GB Flash
RAM 8GB DDR4 (upgrades available 1GB
Power

Dual AC

Dual DC

Dual AC

Dual DC

Form Factor 1U Rack Mounted 1U Rack Mounted
Data Sheet Download Download

Get the best console server hardware for your deployment with Nodegrid

The vendor-neutral Nodegrid platform provides solutions for any use case, deployment size, and pain points. Schedule a free Nodegrid demo to learn more.

Want to see Nodegrid in action?

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Data Center Scalability Tips & Best Practices

Data center scalability is the ability to increase or decrease workloads cost-effectively and without disrupting business operations. Scalable data centers make organizations agile, enabling them to support business growth, meet changing customer needs, and weather downturns without compromising quality. This blog describes various methods for achieving data center scalability before providing tips and best practices to make scalability easier and more cost-effective to implement.

How to achieve data center scalability

There are four primary ways to scale data center infrastructure, each of which has advantages and disadvantages.

 

4 Data center scaling methods

Method Description Pros and Cons
1. Adding more servers Also known as scaling out or horizontal scaling, this involves adding more physical or virtual machines to the data center architecture. Can support and distribute more workloads

Eliminates hardware constraints

Deployment and replication take time

Requires more rack space

Higher upfront and operational costs

2. Virtualization Dividing physical hardware into multiple virtual machines (VMs) or virtual network functions (VNFs) to support more workloads per device. Supports faster provisioning

Uses resources more efficiently

Reduces scaling costs

Transition can be expensive and disruptive

Not supported by all hardware and software

3. Upgrading existing hardware Also known as scaling up or vertical scaling, this involves adding more processors, memory, or storage to upgrade the capabilities of existing systems. Implementation is usually quick and non-disruptive

More cost-effective than horizontal scaling

Requires less power and rack space

Scalability limited by server hardware constraints

Increases reliance on legacy systems

4. Using cloud services Moving some or all workloads to the cloud, where resources can be added or removed on-demand to meet scaling requirements. Allows on-demand or automatic scaling

Better support for new and emerging technologies

Reduces data center costs

Migration is often extremely disruptive

Auto-scaling can lead to ballooning monthly bills

May not support legacy software

It’s important for companies to analyze their requirements and carefully consider the advantages and disadvantages of each method before choosing a path forward. 

Best practices for data center scalability

The following tips can help organizations ensure their data center infrastructure is flexible enough to support scaling by any of the above methods.

Run workloads on vendor-neutral platforms

Vendor lock-in, or a lack of interoperability with third-party solutions, can severely limit data center scalability. Using vendor-neutral platforms ensures that teams can add, expand, or integrate data center resources and capabilities regardless of provider. These platforms make it easier to adopt new technologies like artificial intelligence (AI) and machine learning (ML) while ensuring compatibility with legacy systems.

Use infrastructure automation and AIOps

Infrastructure automation technologies help teams provision and deploy data center resources quickly so companies can scale up or out with greater efficiency. They also ensure administrators can effectively manage and secure data center infrastructure as it grows in size and complexity. 

For example, zero-touch provisioning (ZTP) automatically configures new devices as soon as they connect to the network, allowing remote teams to deploy new data center resources without on-site visits. Automated configuration management solutions like Ansible and Chef ensure that virtualized system configurations stay consistent and up-to-date while preventing unauthorized changes. AIOps (artificial intelligence for IT operations) uses machine learning algorithms to detect threats and other problems, remediate simple issues, and provide root-cause analysis (RCA) and other post-incident forensics with greater accuracy than traditional automation. 

Isolate the control plane with Gen 3 serial consoles

Serial consoles are devices that allow administrators to remotely manage data center infrastructure without needing to log in to each piece of equipment individually. They use out-of-band (OOB) management to separate the data plane (where production workflows occur) from the control plane (where management workflows occur). OOB serial console technology – especially the third-generation (or Gen 3) – aids data center scalability in several ways:

  1. Gen 3 serial consoles are vendor-neutral and provide a single software platform for administrators to manage all data center devices, significantly reducing management complexity as infrastructure scales out.
  2. Gen 3 OOB can extend automation capabilities like ZTP to mixed-vendor and legacy devices that wouldn’t otherwise support them.
  3. OOB management moves resource-intensive infrastructure automation workflows off the data plane, improving the performance of production applications and workflows.
  4. Serial consoles move the management interfaces for data center infrastructure to an isolated control plane, which prevents malware and cybercriminals from accessing them if the production network is breached. Isolated management infrastructure (IMI) is a security best practice for data center architectures of any size.

How Nodegrid simplifies data center scalability

Nodegrid is a Gen 3 out-of-band management solution that streamlines vertical and horizontal data center scalability. 

The Nodegrid Serial Console Plus (NSCP) offers 96 managed ports in a 1RU rack-mounted form factor, reducing the number of OOB devices needed to control large-scale data center infrastructure. Its open, x86 Linux-based OS can run VMs, VNFs, and Docker containers so teams can run virtualized workloads without deploying additional hardware. Nodegrid can also run automation, AIOps, and security on the same platform to further reduce hardware overhead.

Nodegrid OOB is also available in a modular form factor. The Net Services Router (NSR) allows teams to add or swap modules for additional compute, storage, memory, or serial ports as the data center scales up or down.

Want to see Nodegrid in action?

Watch a demo of the Nodegrid Gen 3 out-of-band management solution to see how it can improve scalability for your data center architecture.

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Comparing Edge Security Solutions

A user at an edge site with a virtual overlay of SASE and related edge security concepts
The continuing trend of enterprise network decentralization to support Internet of Things (IoT) deployments, automation, and edge computing is resulting in rapid growth for the edge security market. Recent research predicts it will reach $82.4 billion by 2031 at a compound annual growth rate (CAGR) of 19.7% from 2024.

Edge security solutions decentralize the enterprise security stack, delivering key firewall capabilities to the network’s edges. This prevents companies from funneling all edge traffic through a centralized data center firewall, reducing latency and improving overall performance.

This guide compares the most popular edge security solutions and offers recommendations for choosing the right vendor for your use case.

Executive summary

There are six single-vendor SASE solutions offering the best combination of features and capabilities for their targeted use cases.
.

Single-Vendor SASE Product

Key Takeaways

Palo Alto Prisma SASE

Prisma SASE’s advanced feature set, high price tag, and granular controls make it well-suited to larger enterprises with highly distributed networks, complex edge operations, and personnel with previous SSE and SD-WAN experience.

Zscaler Zero Trust SASE

Zscaler offers fewer security features than some of the other vendors on the list, but its capabilities and feature roadmap align well with the requirements of many enterprises, especially those with large IoT and operational technology (OT) deployments.

Netskope ONE

Netskope ONE’s flexible options allow mid-sized companies to take advantage of advanced SASE features without paying a premium for the services they don’t need, though the learning curve may be a bit steep for inexperienced teams.

Cisco

Cisco Secure Connect makes SASE more accessible to smaller, less experienced IT teams, though its high price tag could be prohibitive to these companies. Cisco’s unmanaged SASE solutions integrate easily with existing Cisco infrastructures, but they offer less flexibility in the choice of features than other options on this list.

Forcepoint ONE

Forcepoint’s data-focused platform and deep visibility make it well-suited for organizations with complicated data protection needs, such as those operating in the heavily regulated healthcare, finance, and defense industries. However, Forcepoint ONE has a steep learning curve, and integrating other services can be challenging. 

Fortinet FortiSASE

FortiSASE provides comprehensive edge security functionality for large enterprises hoping to consolidate their security operations with a single platform. However, the speed of some dashboards and features – particularly those associated with the FortiMonitor DEM software – could be improved for a better administrative experience.

The best edge security solution for Gen 3 out-of-band (OOB) management, which is critical for infrastructure isolation, resilience, and operational efficiency, is Nodegrid from ZPE Systems. Nodegrid provides secure hardware and software to host other vendors’ tools on a secure, Gen 3 OOB network. It creates a control plane for edge infrastructure that’s completely isolated from breaches on the production network and consolidates an entire edge networking stack into a single solution. Disclaimer: This comparison was written by a third party in collaboration with ZPE Systems using publicly available information gathered from data sheets, admin guides, and customer reviews on sites like Gartner Peer Insights, as of 6/09/2024. Please email us if you have corrections or edits, or want to review additional attributes, at matrix@zpesystems.com.

What are edge security solutions?

Edge security solutions primarily fall into one (or both) of two categories:

  • Security Service Edge (SSE) solutions deliver core security features as a managed service. SSE does not come with any networking capabilities, so companies still need a way to securely route edge traffic through the (often cloud-based) security stack. This usually involves software-defined wide area networking (SD-WAN), which was traditionally a separate service that had to be integrated with the SSE stack.
  • Secure Access Service Edge (SASE) solutions package SSE together with SD-WAN, preventing companies from needing to deploy and manage multiple vendor solutions.

All the top SSE providers now offer fully integrated SASE solutions with SD-WAN. SASE’s main tech stack is in the cloud, but organizations must install SD-WAN appliances at each branch or edge data center. SASE also typically uses software agents deployed at each site and, in some cases, on all edge devices. Some SASE vendors also sell physical appliances, while others only provide software licenses for virtualized SD-WAN solutions. A third category of edge security solutions offers a secure platform to run other vendors’ SD-WAN and SASE software. These solutions also provide an important edge security capability: management network isolation. This feature ensures that ransomware, viruses, and malicious actors can’t jump from compromised IoT devices to the management interfaces used to control vital edge infrastructure.

Comparing edge security solutions

Palo Alto Prisma SASE

A screenshot from the Palo Alto Prisma SASE solution. Palo Alto Prisma was named a Leader in Gartner’s 2023 SSE Magic Quadrant for its ability to deliver best-in-class security features. Prisma SASE is a cloud-native, AI-powered solution with the industry’s first native Autonomous Digital Experience Management (ADEM) service. Prisma’s ADEM has built-in AIOps for automatic incident detection, diagnosis, and remediation, as well as self-guided remediation to streamline the end-user experience. Prisma SASE’s advanced feature set, high price tag, and granular controls make it well-suited to larger enterprises with highly distributed networks, complex edge operations, and personnel with previous SSE and SD-WAN experience.

Palo Alto Prisma SASE Capabilities:

  • Zero Trust Network Access (ZTNA) 2.0 – Automated app discovery, fine-grained access controls, continuous trust verification, and deep security inspection.
  • Cloud Secure Web Gateway (SWG) – Inline visibility and control of web and SaaS traffic.
  • Next-Gen Cloud Access Security Broker (CASB) – Inline and API-based security controls and contextual policies.
  • Remote Browser Isolation (RBI) – Creates a secure isolation channel between users and remote browsers to prevent web threats from executing on their devices.
  • App acceleration – Application-aware routing to improve “first-mile” connection performance.
  • Prisma Access Browser – Policy management for edge devices.
  • Firewall as a Service (FWaaS) – Advanced threat protection, URL filtering, DNS security, and other next-generation firewall (NGFW) features.
  • Prisma SD-WAN – Elastic networks, app-defined fabric, and Zero Trust security.

Zscaler Zero Trust SASE

Zscaler is another 2023 SSE Magic Quadrant Leader offering a robust single-vendor SASE solution based on its Zero Trust ExchangeTM platform. Zscaler SASE uses artificial intelligence to boost its SWG, firewall, and DEM capabilities. It also offers IoT device management and OT privileged access management, allowing companies to secure unmanaged devices and provide secure remote access to industrial automation systems and other operational technology. Zscaler offers fewer security features than some of the other vendors on the list, but its capabilities and future roadmap align well with the requirements of many enterprises, especially those with large IoT and operational technology deployments.

Zscaler Zero Trust SASE Capabilities:

  • Zscaler Internet AccessTM (ZIA) SWG cyberthreat protection and zero-trust access to SaaS apps and the web.
  • Zscaler Private AccessTM (ZPA) ZTNA connectivity to private apps and OT devices.
  • Zscaler Digital ExperienceTM (ZDX) –  DEM with Microsoft Copilot AI to streamline incident management.
  • Zscaler Data Protection CASB/DLP secures edge data across platforms.
  • IoT device visibility – IoT device, server, and unmanaged user device discovery, monitoring, and management.
  • Privileged OT access – Secure access management for third-party vendors and remote user connectivity to OT systems.
  • Zero Trust SD-WAN – Works with the Zscaler Zero Trust Exchange platform to secure edge and branch traffic.

Netskope ONE

Netskope is the only 2023 SSE Magic Quadrant Leader to offer a single-vendor SASE targeted to mid-market companies with smaller budgets as well as larger enterprises. The Netskope ONE platform provides a variety of security features tailored to different deployment sizes and requirements, from standard SASE offerings like ZTNA and CASB to more advanced capabilities such as AI-powered threat detection and user and entity behavior analytics (UEBA). Netskope ONE’s flexible options allow mid-sized companies to take advantage of advanced SASE features without paying a premium for the services they don’t need, though the learning curve may be a bit steep for inexperienced teams.

Netskope ONE Capabilities:

  • Next-Gen SWG Protection for cloud services, applications, websites, and data.
  • CASB Security for both managed and unmanaged cloud applications.
  • ZTNA Next –  ZTNA with integrated software-only endpoint SD-WAN.
  • Netskope Cloud Firewall (NCF) Outbound network traffic security across all ports and protocols.
  • RBI – Isolation for uncategorized and risky websites.
  • SkopeAI – AI-powered threat detection, UEBA, and DLP
  • Public Cloud Security – Visibility, control, and compliance for multi-cloud environments.
  • Advanced analytics – 360-degree risk analysis.
  • Cloud Exchange – Multi-cloud integration tools.
  • DLP – Sensitive data discovery, monitoring, and protection.
  • Device intelligence – Zero trust device discovery, risk assessment, and management.
  • Proactive DEM – End-to-end visibility and real-time insights.
  • SaaS security posture management – Continuous monitoring and enforcement of SaaS security settings, policies, and best practices.
  • Borderless SD-WAN – Zero trust connectivity for edge, branch, cloud, remote users, and IoT devices.

Cisco

Cisco is one of the only edge security vendors to offer SASE as a managed service for companies with lean IT operations and a lack of edge networking experience. Cisco Secure Connect SASE-as-a-service includes all the usual SSE capabilities, such as ZTNA, SWG, and CASB, as well as native Meraki SD-WAN integration and a generative AI assistant. Cisco also provides traditional SASE by combining Cisco Secure Access SSE – which includes the Cisco Umbrella Secure Internet Gateway (SIG) – with Catalyst SD-WAN. Cisco Secure Connect makes SASE more accessible to smaller, less experienced IT teams, though its high price tag could be prohibitive to these companies. Cisco’s unmanaged SASE solutions integrate easily with existing Cisco infrastructures, but they offer less flexibility in the choice of features than other options on this list.

Cisco Secure Connect SASE-as-a-Service Capabilities:

  • Clientless ZTNA
  • Client-based Cisco AnyConnect secure remote access
  • SWG
  • Cloud-delivered firewall
  • DNS-layer security
  • CASB
  • DLP
  • SAML user authentication
  • Generative AI assistant
  • Network interconnect intelligent routing
  • Native Meraki SD-WAN integration
  • Unified management

Cisco Secure Access SASE Capabilities

  • ZTNA 
  • SWG
  • CASB
  • DLP
  • FWaaS
  • DNS-layer security
  • Malware protection
  • RBI
  • Catalyst SD-WAN

Forcepoint ONE

A screenshot from the Forcepoint ONE SASE solution. Forcepoint ONE is a cloud-native single-vendor SASE solution placing a heavy emphasis on edge and multi-cloud visibility. Forcepoint ONE aggregates live telemetry from all Forcepoint security solutions and provides visualizations, executive summaries, and deep insights to help companies improve their security posture. Forcepoint also offers what they call data-first SASE, focusing on protecting data across edge and cloud environments while enabling seamless access for authorized users from anywhere in the world. Forcepoint’s data-focused platform and deep visibility make it well-suited for organizations with complicated data protection needs, such as those operating in the heavily regulated healthcare, finance, and defense industries. However, Forcepoint ONE has a steep learning curve, and integrating other services can be challenging.

Forcepoint ONE Capabilities:

  • CASB – Access control and data security for over 800,000 cloud apps on managed and unmanaged devices.
  • ZTNA – Secure remote access to private web apps.
  • SWG – Includes RBI, content disarm & reconstruction (CDR), and a cloud firewall.
  • Data Security – A cloud-native DLP to help enforce compliance across clouds, apps, emails, and endpoints.
  • Insights – Real-time analysis of live telemetry data from Forcepoint ONE security products.
  • FlexEdge SD-WAN – Secure access for branches and remote edge sites.

Fortinet FortiSASE

Fortinet’s FortiSASE platform combines feature-rich, AI-powered NGFW security functionality with SSE, digital experience monitoring, and a secure SD-WAN solution. Fortinet’s SASE offering includes the FortiGate NGFW delivered as a service, providing access to FortiGuard AI-powered security services like antivirus, application control, OT security, and anti-botnet protection. FortiSASE also integrates with the FortiMonitor DEM SaaS platform to help organizations optimize endpoint application performance. FortiSASE provides comprehensive edge security functionality for large enterprises hoping to consolidate their security operations with a single platform. However, the speed of some dashboards and features – particularly those associated with the FortiMonitor DEM software – could be improved for a better administrative experience.

Fortinet FortiSASE Capabilities:

  • Antivirus – Protection from the latest polymorphic attacks, ransomware, viruses, and other threats.
  • DLP – Prevention of intentional and accidental data leaks.
  • AntiSpam – Multi-layered spam email filtering.
  • Application Control – Policy creation and management for enterprise and cloud-based applications.
  • Attack Surface Security – Security Fabric infrastructure assessments based on major security and compliance frameworks.
  • CASB – Inline and API-based cloud application security.
  • DNS Security – DNS traffic visibility and filtering.
  • IPS – Deep packet inspection (DPI) and SSL inspection of network traffic.
  • OT Security – IPS for OT systems including ICS and SCADA protocols.
  • AI-Based Inline Malware Prevention – Real-time protection against zero-day exploits and sophisticated, novel threats.
  • URL Filtering – AI-powered behavior analysis and correlation to block malicious URLs.
  • Anti-Botnet and C2 – Prevention of unauthorized communication attempts from compromised remote servers.
  • FortiMonitor DEM – SaaS-based digital experience monitoring.
  • Secure SD-WAN – On-premises and cloud-based SD-WAN integrated into the same OS as the SSE security solutions.

Edge isolation and security with ZPE Nodegrid

The Nodegrid platform from ZPE Systems is a different type of edge security solution, providing secure hardware and software to host other vendors’ tools on a secure, Gen 3 out-of-band (OOB) management network. Nodegrid integrated branch services routers use alternative network interfaces (including 5G/4G LTE) and serial console technology to create a control plane for edge infrastructure that’s completely isolated from breaches on the production network. It uses hardware security features like secure boot and geofencing to prevent physical tampering, and it supports strong authentication methods and SAML integrations to protect the management network. A screenshot from the Forcepoint ONE SASE solution. Nodegrid’s OOB also ensures remote teams have 24/7 access to manage, troubleshoot, and recover edge deployments even during a major network outage or ransomware infection. Plus, Nodegrid’s ability to host Guest OS, including Docker containers and VNFs, allows companies to consolidate an entire edge networking stack in a single platform. Nodegrid devices like the Gate SR with Nvidia Jetson Nano can even run edge computing and AI/ML workloads alongside SASE. .

ZPE Nodegrid Edge Security Capabilities

  • Vendor-neutral platform – Hosting for third-party applications and services, including Docker containers and virtualized network functions.
  • Gen 3 OOB – Management interface isolation and 24/7 remote access during outages and breaches.
  • Branch networking – Routing and switching, VNFs, and software-defined branch networking (SD-Branch).
  • Secure boot – Password-protected BIO/Grub and signed software.
  • Latest kernel & cryptographic modules – 64-bit OS with current encryption and frequent security patches.
  • SSO with SAML, 2FA, & remote authentication – Support for Duo, Okta, Ping, and ADFS.
  • Geofencing – GPS tracking with perimeter crossing detection.
  • Fine-grain authorization – Role-based access control.
  • Firewall – Native IPSec & Fail2Ban intrusion prevention and third-party extensibility.
  • Tampering protection – Configuration checksum and change detection with a configuration ‘reset’ button.
  • TPM encrypted storage – Software encryption for SSD hardware storage.

Deploy edge security solutions on the vendor-neutral Nodegrid OOB platform

Nodegrid’s secure hardware and vendor-neutral OS make it the perfect platform for hosting other vendors’ SSE, SD-WAN, and SASE solutions. Reach out today to schedule a free demo.

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Applications of Edge Computing

A healthcare worker presents various edge computing concepts to highlight some of the applications of edge computing

The edge computing market is huge and continuing to grow. A recent study projected that spending on edge computing will reach $232 billion in 2024. Organizations across nearly every industry are taking advantage of edge computing’s real-time data processing capabilities to get immediate business insights, respond to issues at remote sites before they impact operations, and much more. This blog discusses some of the applications of edge computing for industries like finance, retail, and manufacturing, and provides advice on how to get started.

What is edge computing?

Edge computing involves decentralizing computing capabilities and moving them to the network’s edges. Doing so reduces the number of network hops between data sources and the applications that process and use that data, which mitigates latency, bandwidth, and security concerns compared to cloud or on-premises computing.

Learn more about edge computing vs cloud computing or edge computing vs on-premises computing.

Edge computing often uses edge-native applications that are built from the ground up to harness edge computing’s unique capabilities and overcome its limitations. Edge-native applications leverage some cloud-native principles, such as containers, microservices, and CI/CD. However, unlike cloud-native apps, they’re designed to process transient, ephemeral data in real time with limited computational resources. Edge-native applications integrate seamlessly with the cloud, upstream resources, remote management, and centralized orchestration, but can also operate independently as needed.
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Applications of edge computing

Industry

Applications

Financial services

  • Mitigate security and compliance risks of off-site data transmission

  • Gain real-time customer and productivity insights

  • Analyze surveillance footage in real-time

Industrial manufacturing

  • Monitor and respond to OT equipment issues in real-time

  • Create more efficient maintenance schedules

  • Prevent network outages from impacting production

Retail operations

  • Enhance the in-store customer experience

  • Improve inventory management and ordering

  • Aid loss prevention with live surveillance analysis

Healthcare

  • Monitor and respond to patient health issues in real-time

  • Mitigate security and compliance risks by keeping data on-site

  • Reduce networking requirements for wearable sensors

Oil, gas, & mining

  • Ensure continuous monitoring even during network disruptions

  • Gain real-time safety, maintenance, and production recommendations

  • Enable remote troubleshooting and recovery of IT systems

AI & machine learning

  • Reduce the costs and risks of high-volume data transmissions

  • Unlock near-instantaneous AI insights at the edge

  • Improve AIOps efficiency and resilience at branches

Financial services

The financial services industry collects a lot of edge data from bank branches, web and mobile apps, self-service ATMs, and surveillance systems. Many firms feed this data into AI/ML-powered data analytics software to gain insights into how to improve their services and generate more revenue. Some also use AI-powered video surveillance systems to analyze video feeds and detect suspicious activity. However, there are enormous security, regulatory, and reputational risks involved in transmitting this sensitive data to the cloud or an off-site data center.

Financial institutions can use edge computing to move data analytics applications to branches and remote PoPs (points of presence) to help mitigate the risks of transmitting data off-site. Additionally, edge computing enables real-time data analysis for more immediate and targeted insights into customer behavior, branch productivity, and security. For example, AI surveillance software deployed at the edge can analyze live video feeds and alert on-site security personnel about potential crimes in progress.

Industrial manufacturing

Many industrial manufacturing processes are mostly (if not completely) automated and overseen by operational technology (OT), such as supervisory control and data acquisition systems (SCADA). Logs from automated machinery and control systems are analyzed by software to monitor equipment health, track production costs, schedule preventative maintenance, and perform quality assurance (QA) on components and products. However, transferring that data to the cloud or centralized data center increases latency and creates security risks.

Manufacturers can use edge computing to analyze OT data in real time, gaining faster insights and catching potential issues before they affect product quality or delivery schedules. Edge computing also allows industrial automation and monitoring processes to continue uninterrupted even if the site loses Internet access due to an ISP outage, natural disaster, or other adverse event in the region. Edge resilience can be further improved by deploying an out-of-band (OOB) management solution like Nodegrid that enables control plane/data plane isolation (also known as isolated management infrastructure), as this will give remote teams a lifeline to access and recover OT systems.

Retail operations

In the age of one-click online shopping, the retail industry has been innovating with technology to enhance the in-store experience, improve employee productivity, and keep operating costs down. Retailers have a brief window of time to meet a customer’s needs before they look elsewhere, and edge computing’s ability to leverage data in real time is helping address that challenge. For example, some stores place QR codes on shelves that customers can scan if a product is out of stock, alerting a nearby representative to provide immediate assistance.

Another retail application of edge computing is enhanced inventory management. An edge computing solution can make ordering recommendations based on continuous analysis of purchasing patterns over time combined with real-time updates as products are purchased or returned. Retail companies, like financial institutions, can also use edge AI/ML solutions to analyze surveillance data and aid in loss prevention.

Healthcare

The healthcare industry processes massive amounts of data generated by medical equipment like insulin pumps, pacemakers, and imaging devices. Patient health data can’t be transferred over the open Internet, so getting it to the cloud or data center for analysis requires funneling it through a central firewall via MPLS (for hospitals, clinics, and other physical sites), overlay networks, or SD-WAN (for wearable sensors and mobile EMS devices). This increases the number of network hops and creates a traffic bottleneck that prevents real-time patient monitoring and delays responses to potential health crises.

Edge computing for healthcare allows organizations to process medical data on the same local network, or even the same onboard chip, as the sensors and devices that generate most of the data. This significantly reduces latency and mitigates many of the security and compliance challenges involved in transmitting regulated health data offsite. For example, an edge-native application running on an implanted heart-rate monitor can operate without a network connection much of the time, providing the patient with real-time alerts so they can modify their behavior as needed to stay healthy. If the app detects any concerning activity, it can use multiple cellular and ATT FirstNet connections to alert the cardiologist without exposing any private patient data.

Oil, gas, & mining

Oil, gas, and other mining operations use IoT sensors to monitor flow rates, detect leaks, and gather other critical information about equipment deployed in remote sites, drilling rigs, and offshore platforms all over the world. Drilling rigs are often located in extremely remote or even human-inaccessible locations, so ensuring reliable communications with monitoring applications in the cloud or data center can be difficult. Additionally, when networks or systems fail, it can be time-consuming and expensive – not to mention risky – to deploy IT teams to fix the issue on-site.

The energy and mining industries can use edge computing to analyze data in real time even in challenging deployment environments. For example, companies can deploy monitoring software on cellular-enabled edge computing devices to gain immediate insights into equipment status, well logs, borehole logs, and more. This software can help establish more effective maintenance schedules, uncover production inefficiencies, and identify potential safety issues or equipment failures before they cause larger problems. Edge solutions with OOB management also allow IT teams to fix many issues remotely, using alternative cellular interfaces to provide continuous access for troubleshooting and recovery.

AI & machine learning

Artificial intelligence (AI) and machine learning (ML) have broad applications across many industries and use cases, but they’re all powered by data. That data often originates at the network’s edges from IoT devices, equipment sensors, surveillance systems, and customer purchases. Securely transmitting, storing, and preparing edge data for AI/ML ingestion in the cloud or centralized data center is time-consuming, logistically challenging, and expensive. Decentralizing AI/ML’s computational resources and deploying them at the edge can significantly reduce these hurdles and unlock real-time capabilities.

For example, instead of deploying AI on a whole rack of GPUs (graphics processing units) in a central data center to analyze equipment monitoring data for all locations, a manufacturing company could use small edge computing devices to provide AI-powered analysis for each individual site. This would reduce bandwidth costs and network latency, enabling near-instant insights and providing an accelerated return on the investment into artificial intelligence technology.

AIOps can also be improved by edge computing. AIOps solutions analyze monitoring data from IT devices, network infrastructure, and security solutions and provide automated incident management, root-cause analysis, and simple issue remediation. Deploying AIOps on edge computing devices enables real-time issue detection and response. It also ensures continuous operation even if an ISP outage or network failure cuts off access to the cloud or central data center, helping to reduce business disruptions at vital branches and other remote sites.

Getting started with edge computing

The edge computing market has focused primarily on single-use-case solutions designed to solve specific business problems, forcing businesses to deploy many individual applications across the network. This piecemeal approach to edge computing increases management complexity and risk while decreasing operational efficiency.

The recommended approach is to use a centralized edge management and orchestration (EMO) platform to monitor and control edge computing operations. The EMO should be vendor-agnostic and interoperate with all the edge computing devices and edge-native applications in use across the organization. The easiest way to ensure interoperability is to use vendor-neutral edge computing platforms to run edge-native apps and AI/ML workflows.

For example, the Nodegrid platform from ZPE Systems provides the perfect vendor-neutral foundation for edge operations. Nodegrid integrated branch services routers like the Gate SR with integrated Nvidia Jetson Nano use the open, Linux-based Nodegrid OS, which can host Docker containers and edge-native applications for third-party AI, ML, data analytics, and more. These devices use out-of-band management to provide 24/7 remote visibility, management, and troubleshooting access to edge deployments, even in challenging environments like offshore oil rigs. Nodegrid’s cloud-based or on-premises software provides a single pane of glass to orchestrate operations at all edge computing sites.

Streamline your edge computing deployment with Nodegrid

The vendor-neutral Nodegrid platform can simplify all applications of edge computing with easy interoperability, reduced hardware overhead, and centralized edge management and orchestration. Schedule a Nodegrid demo to learn more.
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Edge Computing Examples

Interlocking cogwheels containing icons of various edge computing examples are displayed in front of racks of servers

The edge computing market is growing fast, with experts predicting edge computing spending to reach almost $350 billion in 2027. Companies use edge computing to leverage data from Internet of Things (IoT) sensors and other devices at the periphery of the network in real-time, unlocking faster insights, accelerating ROIs for artificial intelligence and machine learning investments, and much more. This blog highlights 7 edge computing examples from across many different industries and provides tips and best practices for each use case.

What is edge computing?

Edge computing involves moving compute capabilities – processing units, RAM, storage, data analysis software, etc. – to the network’s edges. This allows companies to analyze or otherwise use edge data in real-time, without transmitting it to a central data center or the cloud.

Edge Computing Learning Center

Edge computing shortens the physical and logical distance between data-generating devices and the applications that use that data, which reduces bandwidth costs and network latency while simplifying many aspects of data security and compliance.

7 Edge computing examples

Below are 7 examples of how organizations use edge computing, along with best practices for overcoming the typical challenges involved in each use case. Click the links in the table for more information about each example.

Examples Best Practices
Monitoring inaccessible equipment in the oil & gas industry Use a vendor-neutral edge computing & networking platform to reduce the tech stack at each site.
Remotely managing and securing automated Smart buildings Isolate the management interfaces for automated building management systems from production to reduce risk.
Analyzing patient health data generated by mobile devices Protect patient privacy with strong hardware roots-of-trust, Zero Trust Edge integrations, and control plane/data plane separation.
Reducing latency for live streaming events and online gaming Use all-in-one, vendor-neutral devices to minimize hardware overhead and enable cost-effective scaling.
Improving performance and business outcomes for AI/ML Streamline operations by using a vendor-neutral platform to remotely monitor and orchestrate edge AI/ML deployments.
Enhancing remote surveillance capabilities at banks and ATMs Isolate the management interfaces for all surveillance systems using Gen 3 OOB to prevent compromise.
Extending data analysis to agriculture sites with limited Internet access Deploy edge gateway routers with environmental sensors to monitor operating conditions and prevent equipment failures.

1. Monitoring and managing inaccessible equipment in the oil and gas industry

The oil and gas industry uses IoT sensors to monitor flow rates, detect leaks, and gather other critical information about human-inaccessible equipment and operations. With drilling rigs located offshore and in extremely remote locations, ensuring reliable internet access to communicate with cloud-based or on-premises monitoring applications can be tricky. Dispatching IT teams to diagnose and repair issues is also costly, time-consuming, and risky. Edge computing allows oil and gas companies to process data on-site and in real-time, so safety issues and potential equipment failures are caught and remediated as soon as possible, even when Internet access is spotty.

Best practice: Use a vendor-neutral edge computing & networking platform like the Nodegrid Gate SR to reduce the tech stack at each site. The Gate SR can host other vendors’ software for SD-WAN, Secure Access Service Edge (SASE), equipment monitoring, and more. It also provides out-of-band (OOB) management and built-in cellular failover to improve network availability and resilience. Read this case study to learn more.

2. Remotely managing and securing fully automated Smart buildings

Smart buildings use IoT sensors to monitor and control building functions such as HVAC, lighting, power, and security. Property management companies and facilities departments use data analysis software to automatically determine optimal conditions, respond to issues, and alert technicians when emergencies occur. Edge computing allows these automated processes to respond to changing conditions in real-time, reducing the need for on-site personnel and improving operational efficiency.

Best practice: Keep the management interfaces for automated building management systems isolated from the production environment to reduce the risk of compromise or ransomware infection. Use edge computing platforms with Gen 3 out-of-band (OOB) management for control plane/data plane separation to improve resilience and ensure continuous remote access for troubleshooting and recovery. 

3. Analyzing patient health data generated by mobile devices in the healthcare industry

Healthcare organizations use data analysis software, including AI and machine learning, to analyze patient health data generated by insulin pumps, pacemakers, imaging devices, and other IoT medical technology. Keeping that data secure is critical for regulatory compliance, so it must be funneled through a firewall on its way to cloud-based or data center applications, increasing latency and preventing real-time response to potentially life-threatening health issues. Edge computing for healthcare moves patient monitoring and data analysis applications to the same local network (or even the same onboard chip) as the sensors generating most of the data, reducing security risks and latency. Some edge computing applications for healthcare can operate without a network connection most of the time, using built-in cellular interfaces and ATT FirstNet connections to send emergency alerts as needed without exposing any private patient data.

Best practice: Protect patient privacy by deploying healthcare edge computing solutions like Nodegrid with strong hardware roots-of-trust, Zero Trust Edge integrations, and control plane/data plane separation. Nodegrid secures management interfaces with the Trusted Platform Module 2.0 (TPM 2.0), multi-factor authentication (MFA), secure boot, built-in firewall intrusion prevention, and more.

4. Reducing latency for live streaming events and online gaming

Streaming live content requires low-latency processing for every user regardless of their geographic location, which is hard to deliver from a few large, strategically placed data centers. Edge computing decentralizes computing resources, using relatively small deployments in many different locations to bring services closer to audience members and gamers. Edge computing reduces latency for streaming sports games, concerts, and other live events, as well as online multiplayer games where real-time responses are critical to the customer experience.

Best practice: Use all-in-one, vendor-neutral devices like the Nodegrid Gate SR to combine SD-WAN, OOB management, edge security, service delivery, and more. Nodegrid services routers reduce the tech stack at each edge computing site, allowing companies to scale out as needed while minimizing hardware overhead.

5. Improving performance and business outcomes for artificial intelligence/machine learning

Artificial intelligence and machine learning applications provide enhanced data analysis capabilities for essentially any use case, but they must ingest vast amounts of data to do so. Securely transmitting and storing edge and IoT data and preparing it for ingestion in data lakes or data warehouses located in the cloud or data center takes significant time and effort, which may prevent companies from getting the most out of their AI investment. Edge computing for AI/ML eliminates transmission and storage concerns by processing data directly from the sources. Edge computing lets companies leverage their edge data for AI/ML much faster, enabling near-real-time insights, improving application performance, and providing accelerated business value from AI investments.

Best practice: Use a vendor-neutral OOB management platform like Nodegrid to remotely monitor and orchestrate edge AI/ML deployments. Nodegrid OOB ensures 24/7 remote management access to AI infrastructure even during network outages. It also supports third-party automation for mixed-vendor devices to help streamline edge operations. 

6. Enhancing remote surveillance capabilities at banks and ATMs

Constantly monitoring video surveillance feeds from banks and ATMs is very tedious for people, but machines excel at it. AI-powered video surveillance systems use advanced machine-learning algorithms to analyze video feeds and detect suspicious activity with far greater vigilance and accuracy than human security teams. With edge computing, these solutions can analyze surveillance data in real-time, so they could potentially catch a crime as it’s occurring. Edge computing also keeps surveillance data on-site, reducing bandwidth costs, network latency, and the risk of interception.

Best practice: Isolate the management interfaces for all surveillance systems using a Gen 3 OOB solution like Nodegrid to keep malicious actors from hijacking the security feeds. OOB control plane/data plane separation also makes it easier to establish a secure environment for regulated financial data, simplifying PCI DSS 4.0 and DORA compliance.

7. Extending data analysis to agriculture sites with limited Internet access

The agricultural sector uses IoT technology to monitor growing conditions, equipment performance, crop yield, and much more. Many of these devices use cellular connections to transmit data to the cloud for analysis which, as we’ve already discussed ad nauseam, introduces latency, increases bandwidth costs, and creates security risks. Edge computing moves this data processing on-site to reduce delays in critical applications like livestock monitoring and irrigation control. It also allows farms to process data on a local network, reducing their reliance on cellular networks that aren’t always reliable in remote and rural areas.

Best practice: Deploy all-in-one edge gateway routers with environmental sensors, like the Nodegrid Mini SR, to monitor operating conditions where your critical infrastructure is deployed. Nodegrid’s environmental sensors alert remote teams when the temperature, humidity, or airflow falls outside of established baselines to prevent equipment failure. 

Edge computing for any use case

The potential uses for edge computing are nearly limitless. A shift toward distributed, real-time data analysis allows companies in any industry to get faster insights, reduce inefficiencies, and see more value from AI initiatives.

Simplify your edge deployment with Nodegrid

The Nodegrid line of integrated services routers delivers all-in-one edge networking, computing, security, and more. For more edge computing examples using Nodegrid, reach out to ZPE Systems today. Contact Us