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.
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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

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 Access^TM (ZIA) – SWG cyberthreat protection and zero-trust access to SaaS apps and the web.
• Zscaler Private Access^TM (ZPA) – ZTNA connectivity to private apps and OT devices.
• Zscaler Digital Experience^TM (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

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. 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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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

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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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 vs On-Premises: A Comparison Edge Computing vs Cloud Computing Edge Computing Requirements Gartner Market Guide for Edge Computing

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.

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.

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.

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.

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.

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.

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.

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

Both edge computing and cloud computing involve moving computational resources – such as CPUs (central processing units), GPUs (graphics processing units), RAM (random access memory), and data storage – out of the centralized, on-premises data center. As such, both represent massive shifts in enterprise network designs and how companies deploy, manage, secure, and use computing resources. Edge and cloud computing also create new opportunities for data processing, which is sorely needed as companies generate more data than ever before, thanks in no small part to an explosion in Internet of Things (IoT) and artificial intelligence (AI) adoption. By 2025, IoT devices alone are predicted to generate 80 zettabytes of data, much of it decentralized around the edges of the network. AI, machine learning, and other data analytics applications, meanwhile, require vast quantities of data (and highly scalable infrastructure) to provide accurate insights. This guide compares edge computing vs cloud computing to help organizations choose the right deployment model for their use case.

Table of Contents

Defining edge computing vs cloud computing Examples of edge computing vs cloud computing The advantages of edge computing over cloud computing The disadvantages of edge computing compared to cloud computing Edge native applications vs cloud native applications Choosing edge computing vs cloud computing

Defining edge computing vs cloud computing

Edge computing involves deploying computing capabilities to the network’s edges to enable on-site data processing for Internet of Things (IoT) sensors, operational technology (OT), automated infrastructure, and other edge devices and services. Edge computing deployments are highly distributed across remote sites far from the network core, such as oil & gas rigs, automated manufacturing plants, and shipping warehouses. Ideally, organizations use a centralized (usually cloud-based) orchestrator to oversee and conduct operations across the distributed edge computing architecture.

Diagram showing an example edge computing architecture controlled by a cloud-based edge orchestrator.

Reducing the number of network hops between edge devices and the applications that process and use edge data enables real-time data processing, reduces MPLS bandwidth costs, improves performance, and keeps private data within the security micro-perimeter. Cloud computing involves using remote computing resources over the Internet to run applications, process and store data, and more. Cloud service providers manage the physical infrastructure and allow companies to easily scale their virtual computing resources with the click of a button, significantly reducing operational costs and complexity over on-premises and edge computing deployments.

Examples of edge computing vs cloud computing

Edge computing works best for workloads requiring real-time data processing using fairly lightweight applications, especially in locations with inconsistent or unreliable Internet access or where privacy/compliance is a major concern. Example edge computing use cases include:

• Orchestrating operational technology (OT) in remote manufacturing plants
• Monitoring safety and production data from sensors inside gas lines
• Analyzing patient data from wearable health monitors to provide real-time emergency alerts

Cloud computing is well-suited to workloads requiring extensive computational resources that can scale on-demand, but that aren’t time-sensitive. Example use cases include:

• Running large artificial intelligence and machine learning solutions
• Centralizing collaboration tools like source code version control
• Orchestrating distributed edge operations from a single platform

The advantages of edge computing over cloud computing

Using cloud-based applications to process edge device data involves transmitting that data from the network’s edges to the cloud provider’s data center, and vice versa. Transmitting data over the open Internet is too risky, so most organizations route the traffic through a security appliance such as a firewall to encrypt and protect the data. Often these security solutions are off-site, in the company’s central data center, or, best-case scenario, a SASE point-of-presence (PoP), adding more network hops between edge devices and the cloud applications that service them.  This process increases bandwidth usage and introduces latency, preventing real-time data processing and negatively affecting performance.

Edge computing moves data processing resources closer to the source, eliminating the need to transmit this data over the Internet. This improves performance by reducing (or even removing) network hops and preventing network bottlenecks at the centralized firewall. Edge computing also lets companies use their valuable edge data in real time, enabling faster insights and greater operational efficiencies.

Edge computing mitigates the risk involved in storing and processing sensitive or highly regulated data in a third-party computing environment, giving companies complete control over their data infrastructure. It can also help reduce bandwidth costs by eliminating the need to route edge data through VPNs or MPLS links to apply security controls.

Edge computing advantages:

• Improves network and application performance
• Enables real-time data processing and insights
• Simplifies security and compliance
• Reduces MPLS bandwidth costs

The disadvantages of edge computing compared to cloud computing

Cloud computing resources are highly scalable, allowing organizations to meet rapidly changing requirements without the hassle of purchasing, installing, and maintaining additional hardware and software licenses. Edge computing still involves physical, on-premises infrastructure, making it far less scalable than the cloud. However, it’s possible to improve edge agility and flexibility by using vendor-neutral platforms to run and manage edge resources. An open platform like Nodegrid allows teams to run multiple edge computing applications from different vendors on the same box, swap out services as business needs evolve, and deploy automation to streamline multi-vendor edge device provisioning from a single orchestrator.

Diagram showing how the Nodegrid Mini SR combines edge computing and networking capabilities on a small, affordable, flexible platform.

Organizations often deploy edge computing in less-than-ideal operating environments, such as closets and other cramped spaces that lack the strict HVAC controls that maintain temperature and humidity in cloud data centers. These environments also typically lack the physical security controls that prevent unauthorized individuals from tampering with equipment, such as guarded entryways, security cameras, and biometric locks. The best way to mitigate this disadvantage is with an environmental monitoring system that uses sensors to detect temperature and humidity changes that could cause equipment failures as well as proximity alarms to notify administrators when someone gets too close. It’s also advisable to use hermetically sealed edge computing devices capable of operating in extreme temperatures and with built-in security features making them tamper-proof.

Cloud computing is often more resilient than edge computing because cloud service providers must maintain a certain level of continuous uptime to meet service level agreements (SLAs). Edge computing operations could be disrupted by network equipment failures, ISP outages, ransomware attacks, and other adverse events, so it’s essential to implement resilience measures that keep services running (if in a degraded state) and allow remote teams to fix problems without having to be on site. Edge resilience measures include Gen 3 out-of-band management, control plane/data plane separation (also known as isolated management infrastructure or IMI), and isolated recovery environments (IRE).

Edge computing disadvantages:

• Less scalable than cloud infrastructure
• Lack of environmental and security controls
• Requires additional resilience measures

Edge-native applications vs cloud-native applications

Edge-native applications and cloud-native applications are similar in that they use containers and microservices architectures, as well as CI/CD (continuous integration/continuous delivery) and other DevOps principles.

Cloud-native applications leverage centralized, scalable resources to perform deep analysis of long-lived data in long-term hot storage environments. Edge-native applications are built to leverage limited resources distributed around the network’s edges to perform real-time analysis of ephemeral data that’s constantly moving. Typically, edge-native applications are highly contextualized for a specific use case, whereas cloud-native applications offer broader, standardized capabilities. Another defining characteristic of edge-native applications is the ability to operate independently when needed while still integrating seamlessly with the cloud, upstream resources, remote management, and centralized orchestration.

Choosing edge computing vs cloud computing

Both edge computing and cloud computing have unique advantages and disadvantages that make them well-suited for different workloads and use cases. Factors like increasing data privacy regulations, newsworthy cloud provider outages, greater reliance on human-free IoT and OT deployments, and an overall trend toward decentralizing business operations are pushing organizations to adopt edge computing. However, most companies still rely heavily on cloud resources and will continue to do so, making it crucial to ensure seamless interoperability between the edge and the cloud.

The best way to ensure integration is by using vendor-neutral platforms. For example, Nodegrid integrated services routers like the Gate SR provide multi-vendor out-of-band serial console management for edge infrastructure and devices, using an embedded Jetson Nano card to support edge computing and AI workloads. The ZPE Cloud management platform unifies orchestration for the entire Nodegrid-connected architecture, delivering 360-degree control over complex and highly distributed networks. Plus, Nodegrid easily integrates – or even directly hosts – other vendors’ solutions for edge data processing, IT automation, SASE, and more, making edge operations more cost-effective. Nodegrid also provides the complete control plane/data plane separation needed to ensure edge resilience.

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The Nodegrid platform from ZPE Systems helps companies across all industries streamline their edge operations with resilient, vendor-neutral, Gen 3 out-of-band management. Request a free Nodegrid demo to learn more. REQUEST A DEMO

Edge computing is rapidly gaining popularity as more  organizations see the benefits of decentralizing data processing for Internet of Things (IoT) deployments, machine learning applications, operational technology (OT), AI and machine learning, and other edge use cases. This guide defines edge computing and edge-native applications, highlights a few key use cases, describes the typical components of an edge deployment, and provides additional resources for building your own edge computing architecture.

Table of Contents

What is edge computing? Edge-native applications Edge computing use cases Edge computing architecture design How to build an edge computing architecture with Nodegrid

What is edge computing?

The Open Glossary of Edge Computing defines it as deploying computing capabilities to the edges of a network to improve performance, reduce operating costs, and increase resilience. Edge computing reduces the number of network hops between data-generating devices and the applications that process and use that data, mitigating latency, bandwidth, and security concerns compared to cloud or on-premises computing.

Image: A diagram showing the migration path from on-premises computing to edge computing, along with the associated level of security risk.

Edge-native applications

Edge-native applications are built from the ground up to harness edge computing’s unique capabilities while mitigating the limitations. They leverage some cloud-native principles, such as containers, microservices, and CI/CD (continuous integration/continuous delivery), with several key differences.

Edge-Native vs. Cloud-Native Applications

	Edge-Native	Cloud-Native
Topology	Distributed	Centralized
Compute	Real-time processing with limited resources	Deep processing with scalable resources
Data	Constantly changing and moving	Long-lived and at rest in a centralized location
Capabilities	Contextualized	Standardized
Location	Anywhere	Cloud data center

Source: Gartner

Edge-native applications integrate seamlessly with the cloud, upstream resources, remote management, and centralized orchestration, but can also operate independently as needed. Crucially, they allow organizations to actually leverage their edge data in real-time, rather than just collecting it for later processing.

Edge computing use cases

Nearly every industry has potential use cases for edge computing, including:

Industry	Edge Computing Use Cases
Healthcare	Mitigating security, privacy, and HIPAA compliance concerns with local data processing Improving patient health outcomes with real-time alerts that don’t require Internet access Enabling emergency mobile medical intervention while reducing mistakes
Finance	Reducing security and regulatory risks through local computing and edge infrastructure isolation Getting fast, localized business insights to improve revenue and customer service Deploying AI-powered surveillance and security solutions without network bottlenecks
Energy	Enabling network access and real-time data processing for airgapped and isolated environments Improving efficiency with predictive maintenance recommendations and other insights Proactively identifying and remediating safety, quality, and compliance issues
Manufacturing	Getting real-time, data-driven insights to improve manufacturing efficiency and product quality Reducing the risk of confidential production data falling into the wrong hands in transit Ensuring continuous operations during network outages and other adverse events Using AI with computer vision to ensure worker safety and quality control of fabricated components/products
Utilities/Public Services	Using IoT technology to deliver better services, improve public safety, and keep communities connected Reducing the fleet management challenges involved in difficult deployment environments Aiding in disaster recovery and resilience with distributed redundant edge resources

To learn more about the specific benefits and uses of edge computing for each industry, read Distributed Edge Computing Use Cases.

Edge computing architecture design

An edge computing architecture consists of six major components:

Edge Computing Components	Description	Best Practices
Devices generating edge data	IoT devices, sensors, controllers, smartphones, and other devices that generate data at the edge	Use automated patch management to keep devices up-to-date and protect against known vulnerabilities
Edge software applications	Analytics, machine learning, and other software deployed at the edge to use edge data	Look for edge-native applications that easily integrate with other tools to prevent edge sprawl
Edge computing infrastructure	CPUs, GPUs, memory, and storage used to process data and run edge applications	Use vendor-neutral, multi-purpose hardware to reduce overhead and management complexity
Edge network infrastructure and logic	Wired and wireless connectivity, routing, switching, and other network functions	Deploy virtualized network functions and edge computing on common, vendor-neutral hardware
Edge security perimeter	Firewalls, endpoint security, web filtering, and other enterprise security functionality	Implement edge-centric security solutions like SASE and SSE to prevent network bottlenecks while protecting edge data
Centralized management and orchestration	An EMO (edge management and orchestration) platform used to oversee and conduct all edge operations	Use a cloud-based, Gen 3 out-of-band (OOB) management platform to ensure edge resilience and enable end-to-end automation

Click here to learn more about the infrastructure, networking, management, and security components of an edge computing architecture.

How to build an edge computing architecture with Nodegrid

Nodegrid is a Gen 3 out-of-band management platform that streamlines edge computing with vendor-neutral solutions and a centralized, cloud-based orchestrator.

Image: A diagram showing all the edge computing and networking capabilities provided by the Nodegrid Gate SR.

Nodegrid integrated services routers deliver all-in-one edge computing and networking functionality while taking up 1RU or less. A Nodegrid box like the Gate SR provides Ethernet and Serial switching, serial console/jumpbox management, WAN routing, wireless networking, and 5G/4G cellular for network failover or out-of-band management. It includes enough CPU, memory, and encrypted SSD storage to run edge computing workflows, and the x86-64bit Linux-based Nodegrid OS supports virtualized network functions, VMs, and containers for edge-native applications, even those from other vendors. The new Gate SR also comes with an embedded NVIDIA Jetson Orin NanoTM module featuring dual CPUs for EMO of AI workloads and infrastructure isolation.

Nodegrid SRs can also host SASE, SSE, and other security solutions, as well as third-party automation from top vendors like Redhat and Salt. Remote teams use the centralized, vendor-neutral ZPE Cloud platform (an on-premises version is available) to deploy, monitor, and orchestrate the entire edge architecture. Management, automation, and orchestration workflows occur over the Gen 3 OOB control plane, which is separated and isolated from the production network. Nodegrid OOB uses fast, reliable network interfaces like 5G cellular to enable end-to-end automation and ensure 24/7 remote access even during major outages, significantly improving edge resilience.

Streamline your edge deployment

The Nodegrid platform from ZPE Systems reduces the cost and complexity of building an edge computing architecture with vendor-neutral, all-in-one devices and centralized EMO. Request a free Nodegrid demo to learn more.

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NIS2 – an update of the EU’s Network and Information Security Directive – seeks to enhance the cybersecurity level and resilience of EU member states. Compared to the original NIS, it significantly increases risk management, corporate accountability, business continuity, and reporting requirements. NIS2 becomes law in all EU member states by 17 October 2024, so affected organizations must take action soon to avoid fines and other penalties. This guide describes the 10 minimum cybersecurity requirements mandated by NIS2 and provides tips to simplify NIS2 compliance. Citation: Directive (EU) 2022/2555 of the European Parliament and of the Council of 14 December 2022 on measures for a high common level of cybersecurity across the Union, amending Regulation (EU) No 910/2014 and Directive (EU) 2018/1972, and repealing Directive (EU) 2016/1148 (NIS 2 Directive)

Who does NIS2 apply to, and what are the consequences for noncompliance?

NIS2 applies to organizations providing services deemed “essential” or “important” to the European economy and society. Essential Entities (EE) generally have at least 250 employees, annual turnover of €50 million, or balance sheets of €43 million. Essential sectors include:

• Energy
• Transport
• Finance
• Public administration
• Health
• Space
• Water supply (drinking & wastewater)
• Digital infrastructure (e.g., cloud computing providers)

Important Entities (IE) generally have at least 50 employees, annual turnover of €10 million, or balance sheets of €10 million. Important sectors include:

• Postal services
• Waste management
• Chemicals
• Research
• Food
• Manufacturing (e.g., medical devices and other equipment)
• Digital providers (e.g., social networks, online marketplaces)

The NIS2 Directive outlines three types of penalties for noncompliance: non-monetary remedies, administrative fines, and criminal sanctions. Non-monetary remedies include things like compliance orders, binding instructions, security audit orders, and customer threat notification orders. Financial penalties for Essential Entities max out at €10 million or 2% of the global annual revenue, whichever is higher; for Important Entities, the maximum is €7 million or 1.4% of the global annual revenue, whichever is higher. NIS2 also directs member states to hold top management personally responsible for gross negligence in a cybersecurity incident, which could involve:

• Ordering organizations to notify the public of compliance violations
• Publicly identifying the people and/or entities responsible for the violation
• Temporarily banning an individual from holding management positions (EEs only)

Even the nonfinancial penalties of NIS2 noncompliance can affect revenue by causing reputational damage and potential lost business, so it’s crucial for IEs and EEs to be prepared when this directive takes effect in their state.

10 Minimum requirements for NIS2 compliance

The NIS2 directive requires essential and important entities to take “appropriate and proportional” measures to manage security and resilience risks and minimize the impact of incidents. It mandates an “all-hazards approach,” which means creating a comprehensive business continuity framework that accounts for any potential disruptions, whether they be natural disasters, ransomware attacks, or anything in between. Organizations must implement “at least” the following requirements as a baseline for NIS2 compliance (click links for more info):

1. Risk analysis and information system security policies

Organizations must create and update comprehensive policies covering cybersecurity risk analysis and overall IT system security practices. These policies should cover all the topics listed below and include specific consequences and/or corrective measures for failing to follow the outlined processes.

Tip: Keeping all company policies in a centralized, version-controlled repository will help track updates over time and prevent anyone from making unauthorized changes.

2. Security incident handling

Entities must implement incident-handling tools and practices to help accelerate resolution and minimize the impact on end users and other essential or important services. This includes mechanisms for identifying problems, triaging according to severity, remediating issues, and notifying relevant parties. NIS2 outlines a specific timeline for reporting significant security incidents to the relevant authorities:

• Within 24 hours – Entities must provide an early warning indicating whether they suspect an unlawful or malicious attack or whether it could have a cross-border impact.

• Within 72 hours – Entities must update the relevant authorities with an assessment of the attack, including its severity, impact, and indicators of compromise.

• Within one month – Organisations must submit a final report including a detailed description of the incident, the most likely root cause or type of threat, what mitigation measures were taken, and, if applicable, the cross-border impact. If the incident is still ongoing, entities must submit an additional report within one month of resolution.

Tip: AIOps (artificial intelligence for IT operations) analyzes monitoring logs using machine learning to identify threat indicators and other potential issues that less sophisticated tools might miss. It can also generate, triage, and assign incidents, perform root-cause analysis (RCA) and other automated troubleshooting, and take other actions to streamline security incident handling.

3. Business continuity and crisis management

Essential and important entities must establish comprehensive business continuity and crisis management strategies to minimize service disruptions. These strategies should include redundancies and backups as part of a resilience system that can keep operations running, if in a degraded state, during major cybersecurity incidents. It’s also crucial to maintain continuous access to management, troubleshooting, and recovery infrastructure during an attack.

Tip: Serial consoles with out-of-band (OOB) management provide an alternative path to systems and infrastructure that doesn’t rely on the production network, ensuring 24/7 management and recovery access during outages and other major incidents. OOB serial consoles can also be used to create an isolated recovery environment (IRE) where teams can safely restore and rebuild critical services without risking ransomware reinfection.

4. Supply chain security

Organizations must implement supply chain security risk management measures to limit the risk of working with third-party suppliers. These include performing regular risk assessments based on the supplier’s security and compliance history, applying zero-trust access control policies to third-party accounts, and keeping third-party software and dependencies up-to-date.

Tip: User and entity behavior analytics (UEBA) software uses machine learning to analyze account activity on the network and detect unusual behavior that could indicate compromise. It establishes baselines for normal behavior based on real user activity, reducing false positives and increasing detection accuracy even with vendors and contractors who operate outside of normal business hours and locations.

5. Secure network and IT system acquisition, development, and maintenance

Entities must ensure the security of network and IT systems during acquisition, development, and maintenance. This involves, among other things, inspecting hardware for signs of tampering before deployment, changing default settings and passwords on initial startup, performing code reviews on in-house software to check for vulnerabilities, and applying security patches as soon as vulnerabilities are discovered.

Tip: Automation can streamline many of these practices while reducing the risk of human error. For example, zero-touch provisioning automatically configures devices as soon as they come online, reducing the risk of attackers compromising a system-default admin account. Automated vulnerability scanning tools can help detect security flaws in software and systems; automated patch management ensures third-party updates are applied as soon as possible.

6. Cybersecurity and risk-management assessments

Organizations must have a way to objectively assess their cybersecurity and risk-management practices and remediate any identified weaknesses. These assessments involve identifying all the physical and logical assets used by the company, scanning for potential threats, determining the severity or potential impact of any identified threats, taking the necessary mitigation steps, and thoroughly documenting everything to streamline any reporting requirements.

Tip: An AI-powered cybersecurity risk assessment tool uses large language models (LLMs) and other machine learning technology to automate assessments with greater accuracy than older solutions. These tools are often better at identifying novel threats than human assessors or signature-based detection methods, and they typically provide automated reporting to aid in NIS2 compliance.

7. Cybersecurity training

Essential and important entities must enforce cybersecurity training and basic security hygiene policies for all staff. This training should include information about the most common social engineering attacks, such as email phishing or vishing (voice phishing), compliant data handling practices, and how to securely create and manage account credentials.

Tip: Some cybersecurity training programs include attack simulations – such as fake phishing emails – to test trainees’ knowledge and give them practice identifying social engineering attempts. These programs help companies identify users who need additional education and periodically reinforce what they have learned.

8. Cryptography and encryption

NIS2 requires organizations to use cryptography to protect systems and data from tampering. This includes encrypting sensitive data and communications when necessary.

Tip: Roots of Trust (RoTs) are hardware security mechanisms providing cryptographic functions, key management, and other important security features. RoTs are inherently trusted, so it’s important to choose up-to-date solutions offering strong cryptographic algorithms, such as Trusted Platform Module (TPM) 2.0.

9. User access control and asset management

Entities must establish policies and procedures for employees accessing sensitive data, including least-privilege access control and secure asset management. This also includes mechanisms for revoking access and locking down physical assets when users violate safe data handling policies, or malicious outsiders compromise privileged credentials.

Tip: Zero trust security uses network micro-segmentation and highly specific security policies to protect sensitive resources. MFA and continuous authentication controls seek to re-establish trust each time a user requests access to a new resource, making it easier to catch malicious actors and preventing lateral movement on the network.

10. Multi-factor authentication (MFA) and encrypted communications

The final minimum requirement for NIS2 compliance is using multi-factor authentication (MFA) and continuous authentication solutions to verify identities, as described above. Additionally, entities must be able to encrypt voice, video, text, and internal emergency communications when needed.

Tip: MFA, continuous authentication, and other zero-trust controls should also extend to management interfaces, resilience systems, and isolated recovery environments to prevent malicious actors from compromising these critical resources. The best practice is to isolate management interfaces and resilience systems using OOB serial consoles to prevent lateral movement from the production network.

How ZPE streamlines NIS2 compliance

EU-based entities classified as essential or important have limited time to implement all the security policies, practices, and tools required for NIS2 compliance. Using vendor-neutral, multi-purpose hardware platforms to deploy new security controls can help reduce the hassle and expense, making it easier to meet the October deadline. For example, a Nodegrid serial console from ZPE Systems combines out-of-band management, routing, switching, cellular failover, SSL VPN and secure tunnel capabilities, and environmental monitoring in a single device. The vendor-neutral Nodegrid OS supports GuestOS and containers for any third-party software, including next-generation firewalls (NGFWs), Secure Access Service Edge (SASE), automation tools like Puppet and Ansible, and UEBA. Nodegrid devices have strong hardware Roots of Trust with TPM 2.0, selectable encrypted cryptographic protocols and cipher suite levels, and configuration checksumTM. Plus, Nodegrid’s Gen 3 OOB creates the perfect foundation for infrastructure isolation, resilience systems, and isolated recovery environments.

Looking to Upgrade to a Nodegrid serial console?

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The European Union’s Digital Operational Resilience Act (DORA) creates a regulatory framework for information and communication technology (ICT) risk management and network resilience. It entered into EU law on 16 January 2023 and takes effect on 17 January 2025, applying to any firm operating within the European financial sector. This guide outlines the technical requirements for DORA compliance and provides tips and best practices to streamline implementation.

Citation: Digital Operational Resilience Act (DORA)

Which organizations does DORA affect, and what are the consequences of non-compliance?

DORA applies to financial entities operating in the European Union, including:

• Financial services
• Payment institutions
• Crypto-asset service providers
• Crowdfunding service providers
• Investment firms
• Insurance companies
• Data analytics and audit services
• Fintech companies
• Trading venues
• Credit institutions
• Credit rating agencies

Crucially, DORA also applies to third-party digital service providers that work with financial institutions, such as colocation data centers and cloud service providers.

Once DORA takes effect, each EU state will designate “competent authorities” to enforce compliance. Each state determines its own penalties, but potential consequences for non-compliance include fines, remediation, and withdrawal of DORA authorization.

ICT service providers (such as cloud vendors) labeled “critical” by the European Commission face additional oversight and non-compliance penalties, including fines of up to 1% of the provider’s average daily worldwide turnover the previous business year. Overseers can levy fines on a provider every day for up to six months until compliance requirements are met. These steep penalties make it essential for service providers to ensure their systems and processes are DORA-compliant ahead of the 2025 deadline.

What are DORA’s technical requirements?

ICT risk management

DORA requires financial institutions to develop a comprehensive ICT risk management framework containing strategies and tools for business resilience, recovery, and communication. In addition to written policies and documented procedures, financial entities must implement technology such as security hardware and software, redundancies and backups, and resilience systems. Best practices for DORA-compliant risk management technologies include:

• Control plane/data plane separation
• Isolated recovery environments

ICT third-party risk management

Financial organisations in the EU must manage the risk of working with third-party vendors to prevent supply chain attacks such as the MOVEit breach. ICT third-party risk management (TPRM) involves performing vendor due diligence to validate compliance with security standards and ensuring contractual provisions are in place to hold vendors accountable for security failures. On the technical side, financial entities should implement security policies and controls to limit third-party access and use monitoring tools that detect vulnerabilities, apply patches, and identify suspicious account behavior. Best practices for DORA-compliant TPRM technologies include:

• Automated patch management
• AIOps security monitoring

Digital operational resilience testing

DORA requires financial entities to establish a resilience testing program to validate their security defenses, backups, redundancies, and recovery systems once per year. Examples of resilience tests include vulnerability scans, network security assessments, open-source software analyses, physical security reviews, penetration testing, and source code reviews. Financial entities deemed “critical,” as well as their critical ICT providers, must also undergo threat-led penetration testing (TLPT) every three years. DORA stipulates that these tests be performed by independent parties, though they can be internal so long as the organization takes steps to eliminate any conflict of interest. Technical best practices include:

• Control plane/data plane separation

ICT incident reporting

DORA streamlines and consolidates the incident reporting requirements that are currently fragmented across EU states. The takeaway from this section is a requirement for financial firms to submit a root cause report within one month of a major incident. Technical best practices for meeting this requirement involve using AIOps for:

• Anomaly detection
• Incident management
• Root-cause analysis (RCA)

Information sharing

This is less of a requirement than a suggestion, but DORA both allows and encourages financial institutions to share cyber threat information within the community to help raise awareness and mitigate risks. Best practices involve using (anonymized) logs from some of the technologies mentioned above, such as UEBA and AIOps.

Oversight of critical third-party providers

DORA requires “critical” digital service providers to follow the same compliance rules as the financial institutions they work with. Regulators may deem a provider critical if a large number of financial entities rely on them for business continuity or if they are difficult to replace/substitute when a failure occurs. Any cloud vendors, colocation data centers, or other digital service providers working in the EU’s financial sector should prepare for DORA by implementing:

• Control/data plane separation
• Isolated recovery environments
• Automated patch management
• AIOps

Best practices for DORA compliance

Some of the technologies that can help simplify DORA compliance for financial institutions and critical service providers include:

Control/data plane separation

Separating the data plane (i.e., production network traffic) from the control plane (i.e., management and troubleshooting traffic) simplifies DORA compliance in two key ways:

1. It isolates the management interfaces used to control ICT systems, making them inaccessible to malicious actors who breach the production network and aiding in resilience.
2. It prevents resource-intensive automation, security monitoring, and resilience testing workflows from affecting the speed or availability of the production network.

The best practice for control and data plane separation is to use Gen 3 out-of-band (OOB) serial consoles, such as the Nodegrid product line from ZPE Systems. Gen 3 OOB provides a dedicated network for management traffic that doesn’t depend on production network resources, ensuring remote teams always have access, even during outages or ransomware attacks. It’s also vendor-neutral, allowing administrators to deploy third-party monitoring, automation, security, troubleshooting, and testing tools on the isolated control plane. Gen 3 OOB helps financial institutions and ICT service providers meet resilience and testing requirements cost-effectively.

Isolated recovery environments

Ransomware continues to be one of the biggest threats to resilience, with ransomware cases increasing by 73% in 2023 despite heightened awareness and additional cybersecurity spending. Preventing an attack may be nearly impossible, and full recovery often takes weeks due to the high rate of reinfection. The best way to reduce recovery time and meet DORA resilience requirements is with an isolated recovery environment (IRE) that’s fully separated from the production infrastructure.

An IRE contains systems dedicated to recovering from ransomware and other breaches, where teams can rebuild and restore applications, data, and other resources before deploying them back to the production network. It uses designated network infrastructure that’s completely separate from the production environment to mitigate the risk of malware reinfection. It also contains technologies like Retention Lock, role-based access control, and out-of-band management so teams can quickly and safely recover critical services and reduce DORA penalties.

Automated patch management

Cybercriminals often breach networks by exploiting known vulnerabilities in outdated software and firmware, as happened with 2023’s Ragnar Locker attacks. For large financial institutions and critical ICT providers, manually tracking and installing patches for all the third-party hardware and software used across the organization is too difficult and time-consuming, leaving potential vulnerabilities exposed for years. The best practice for meeting DORA’s third-party risk management requirement is to use an automated, vendor-agnostic patch management solution.

Automatic patch management tools discover all the software and devices used by the organization, monitor for known exploited vulnerabilities, and notify teams when vendors release updates. They centralize patch management for the entire network to simplify TPRM and aid in DORA compliance.

AIOps

AIOps uses artificial intelligence technology to automate and streamline IT operations. AIOps collects and analyses all the data generated by IT infrastructure, applications, monitoring tools, and security solutions to help identify significant events and make “intelligent” recommendations. AIOps helps with DORA compliance by providing:

• Anomaly detection – Artificial intelligence analyses logs and detects outlier data points that could indicate an in-progress data breach or other problematic event.
• Incident management – AIOps automatically generates, triages, and assigns service desk tickets to the appropriate team for resolution, significantly accelerating incident response.
• Root-cause analysis – AIOps combs through all the relevant logs to determine the most likely cause of adverse events, making it easier to meet DORA’s root-cause reporting requirements.

How ZPE streamlines DORA compliance

The Nodegrid out-of-band management platform from ZPE Systems helps financial institutions and critical service providers meet DORA resilience requirements without increasing network complexity. Vendor-neutral Nodegrid serial consoles and integrated edge services routers deliver control plane isolation, centralized infrastructure patch management, and Guest OS/container hosting for third-party security, recovery, and AIOps tools. The Nodegrid platform provides a secure foundation for an isolated recovery environment that contains all the technology needed to get services back online and stay DORA compliant.

Download our 3 Steps to Ransomware Recovery whitepaper to learn how to improve network resilience with Nodegrid.
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Looking to replace your discontinued, EOL serial console with a Gen 3 out-of-band solution?

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SD-WAN applies software-defined networking (SDN) principles to wide area networks (WANs), which means it decouples networking logic from the underlying WAN hardware. SD-WAN management involves orchestrating and optimizing software-defined WAN workflows across the entire architecture, ideally from a single, centralized platform. This SD-WAN management guide explains how this technology works, the potential benefits of using it, and the best practices to help you get the most out of your SD-WAN deployment.

How does SD-WAN management work?

A typical WAN architecture uses a variety of links, including MPLS, wireless, broadband, and VPNs, to connect branches and other remote locations to enterprise applications and resources. SD-WAN is a virtualized service that overlays this physical architecture, giving software teams a unified software interface from which to manage network traffic and workflows across the enterprise. SD-WAN management decouples network control functions from the gateways and routers installed at remote sites, preventing administrators from having to manage each one individually. It also reduces the reliance on manual CLI rules and prompts, which are time-consuming and prone to human error, allowing teams to deploy policies across an entire network at the same time.

SD-WAN can also use multiple connection types (including 5G LTE, MPLS, and fiber) interchangeably, switching between them as needed to ensure optimal performance. Plus, SD-WAN management enables organizations to use virtualized and cloud-based security technologies (such as SASE) to secure remote traffic to SaaS, web, and cloud resources. This allows organizations to reduce traffic on expensive MPLS links by utilizing less-costly cellular and public internet links to handle cloud-destined traffic.

The benefits of SD-WAN management

Cost reduction

MPLS links provide a secure connection between branches and centralized data center resources, but the bandwidth is far more expensive than fiber or cellular. SD-WAN reduces branch bandwidth costs by using less expensive channels for traffic that’s destined for resources online and in the cloud, reserving MPLS bandwidth for enterprise traffic alone.

Improved performance

To optimize the performance of a traditional WAN, teams must create specific routing, bandwidth utilization, and load-balancing rules for each branch and appliance, and hope these policies adequately predict and resolve any potential issues. SD-WAN management uses technologies like application awareness and guaranteed minimum bandwidth to automatically optimize network performance.

Automation & orchestration

By decoupling network control functions from the underlying WAN hardware, SD-WAN enables automatic device deployments, load balancing, failover, and intelligent routing. Teams can orchestrate automated workflows across the entire network architecture from a centralized software platform, to make deployments and configuration changes more efficient.

Enhanced security

Branch networks often suffer from security gaps due to the difficulty in extending enterprise security policies and controls to remote sites. Securing branch traffic usually means backhauling all traffic through the data center’s firewall, eating up expensive MPLS bandwidth and introducing latency for the rest of the enterprise. Some organizations opt to deploy security appliances at each branch site, which is costly and gives network administrators more moving parts to manage. 

SD-WAN enables the use of cloud-based security solutions like SASE and Zero Trust Edge that extend enterprise security defenses to branch network traffic without backhauling or additional hardware. SD-WAN automatically identifies traffic destined for web or cloud resources and routes it through the cloud-based security stack across less-expensive internet links, saving money and reducing management complexity while improving branch security.

How to get the most out of your SD-WAN deployment

There are a variety of SD-WAN deployment models, each of which solves a different WAN problem, so it’s important to assess your organization’s requirements and capabilities to ensure you build an architecture that meets your needs. It’s also critical to consider the scalability, adaptability, security, and resilience of your SD-WAN deployment to prevent headaches down the road. 

For example, using a vendor-neutral platform like Nodegrid to host SD-WAN allows you to easily expand your branch networking capabilities with third-party software for automation, security, monitoring, troubleshooting, and more without deploying additional hardware, allowing you to easily scale and adapt to changing business requirements. Nodegrid also consolidates branch functions like routing, switching, out-of-band serial console management, SD-WAN management, and SASE network security in a single device for cost-effective branch deployments. Plus, Nodegrid enables isolated management infrastructure that’s resilient to threats and provides a safe recovery environment from ransomware attacks and network failures. 

Ready to get started on your SD-WAN deployment?

Nodegrid unifies control over mixed-vendor hardware and software solutions across the enterprise network architecture for efficient, streamlined SD-WAN management. Request a free demo to learn more.

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The Cisco ISR 2900 series of branch routers went EOS (end-of-sale) on the 9th of December 2017, and Cisco concluded support on the 31st of December 2022. In this guide, we’ll compare migration options for the Cisco ISR 2900 EOL models to help you select a solution that supports your business use case, deployment size, and future growth.

Disclaimer: This comparison was written by a third party in collaboration with ZPE Systems using data gathered from publicly available data sheets and admin guides, as of 5/12/2023. Please email us if you have corrections or edits, or want to review additional attributes: Matrix@zpesystems.com

 

Table of Contents

Cisco ISR 2900 overview Cisco 2900 EOL replacement options Cisco ISR 1100 Cisco Catalyst C8300 Cisco 2900 direct replacement options from ZPE Systems Cisco 2900 EOL product tables with migration SKUs

Cisco ISR 2900 overview

The Cisco ISR 2900 is a line of enterprise gateway routers designed for branch and edge networking. It’s a modular solution that can be expanded with optional Network Interface Modules (NIMs) and Service Modules (SMs) for more functionality. There are two primary use cases for the 2900:

Converged branch networking – The ISR 2900 easily integrates with Cisco’s SD-WAN, SD-Branch, cloud security, and DNA network management software, can be extended with optional modules for added hardware capabilities, and supports NFV (network functions virtualization) for all-in-one branch networking.

Out-of-band (OOB) management – Using serial port modules, the ISR 2900 turns into an out-of-band (OOB) serial console solution that provides remote management access to the control plane of branch infrastructure.

The ISR 2900 is officially EOL as of the 31st of December 2022. The EOL models include all 2901, 2911, 2921, and 2951 ISR product SKUs.

Looking for replacement options for your other Cisco ISR EOL products? Read our guide to Cisco ISR EOL Replacement Options.

 

Cisco 2900 EOL replacement options

The discontinuation of the Cisco 2900 has left many organizations looking for migration options. Let’s compare two direct replacements from Cisco before discussing alternative options that deliver better branch management capabilities and greater opportunities for automation.

Cisco ISR 1100

Cisco ISR 1100 is a series of enterprise branch routers, though in this comparison we’re only looking at the models that support SD-WAN and thus serve as direct replacements for the discontinued 2900 models. The capabilities of the 1100 series vary, mostly because only some of the models are modular. For example, the fixed form-factor 1100-4G/4G LTE models have cellular functionality but offer fewer networking and security features. Conversely, the 1161X-8P and 112x-8P models are modular and can be extended with optional modules (like cellular for the 1161X or terminal server ports for the 112x-8P).

Even with these expansions, the compact ISR 1100s are best suited for smaller deployments in branch offices or small, provider-managed edge data centers. If your organization uses the ISR 2900 for converged branch networking, the 1100s are the closest Cisco replacement, though it supports OOB serial modules as well.

Cisco Catalyst C8300

The Cisco Catalyst C8300 series is a modular branch and edge networking solution, though due to its large size, it’s sometimes used as a primary on-premises gateway router. There are four models to choose from – two 2RU units with 2 SM and 2 NIM slots, and two 1RU units with 1 SM and 1 NIM slot. Each chassis comes with 6 embedded Layer3 Ethernet ports (1 Gbps and/or 10 Gbps) as well as a console port and USB port. All other port configurations and capabilities come via Cisco expansion modules, including options for 5G/4G cellular.

The Catalyst C8300 is a big, robust solution that’s designed for medium to large deployments such as campuses, colocation sites, and AI/machine learning data centers. The C8300 is primarily a converged branch networking solution like the ISR 1100 series, but it provides OOB management with optional serial cards.

Cisco 2900 replacement option comparison table

	Cisco ISR 2900 (EOL)	Cisco ISR 1100	Cisco Catalyst 8300	Nodegrid Net SR	Nodegrid Serial Console Plus
Form Factor	1-2 RU	Desktop-1RU	1-2 RU	1 RU	1 RU
Max IPsec Throughput	Not defined	Up to 18.8 Gbps	Up to 18.8 Gbps	600 Mbps – 1.2 Gbps	600Mbps
Total Onboard WAN or LAN 10/100/1000 Ports	2-3	4-6	4-6	2	2
Total Onboard WAN or LAN 10Gbps Ports	0	0	0-2	2	2
WAN Ports	2-3	0-6	2-6	1+, configurable	0-4
LAN Ports	2-3	0-6	2-6	4-84	0-4
Slots	2-3	0-1	2-4	5	0
Default Memory	512 MB	4 GB	8 GB	8 GB	4 GB
Max Memory	2 GB	8 GB	32 GB	64 GB	16 GB
Compute	–	–	UCS-E Card	On-board, Compute card	On-board
OOB Capabilities	Requires Serial Card	Requires Serial Card	Requires Serial Card	Included	Included
Environmental Monitoring	N/A	N/A	N/A	Included	Included

For users looking for a Cisco solution to replace their EOL ISR 2900, the ISR 1100 series and Catalyst C8300 are the closest direct replacements. However, both product lines suffer from a major limitation – they aren’t vendor-neutral.

While Cisco routers integrate with some third-party partners, they do not support custom or third-party applications for automation and orchestration, which limits you to the automation offered by Cisco’s software. This lack of open integrations increases the chances that a Cisco solution won’t be able to hook into all the hardware and software components of a distributed and multi-vendor network architecture.

For example, if you utilize different SD-WAN and next-generation firewall (NGFW) vendors at some of your remote sites, Cisco’s automation may not extend to these devices. That means you’ll need to send out technicians to all remote sites (which could number in the dozens or hundreds) just to set up these services when you otherwise could have deployed them automatically.

Want to learn more about breaking free of locked ecosystems? Read The Benefits of Vendor Agnostic Platforms in Network Management

When network solutions like the Cisco 2900 go EOL, it’s the perfect opportunity to look for alternative options that provide the functionality you need without locking you into an ecosystem or limiting your automation capabilities.

Cisco 2900 direct replacement options from ZPE Systems

ZPE Systems provides a line of vendor-neutral solutions for branch and edge networking called Nodegrid. The Nodegrid Net Services Router (NSR) and Nodegrid Serial Console Plus (NSCP) serve as direct replacements for Cisco 2900 EOL products.

Nodegrid Net Services Router (NSR)

The Nodegrid NSR is a modular branch networking solution that you can customize to increase your terminal server ports, storage space, processing power, or switch ports. The NSR delivers converged branch networking capabilities like SD-WAN, SD-Branch, and NFVs, plus it can host your choice of custom and third-party applications for automation, security, and more.

While the NSR is the perfect converged branch solution to replace the Cisco ISR 2900, it also provides 3rd generation (or Gen 3) OOB management. That means Nodegrid’s OOB network is completely vendor-neutral and can extend automation capabilities to all your legacy and mixed-vendor infrastructure for efficient deployments, management, and orchestration.

Want to see the Nodegrid converged branch networking solution in action? Watch a Demo

Nodegrid Serial Console Plus (NSCP)

The NSCP is a robust, scalable branch networking and out-of-band serial console solution. The NSCP comes in 16-, 32-, 48-, and 96-port models, so you can choose the solution that’s right-sized to your deployment and use case. Plus, you can get built-in 5G/4G LTE and Wi-Fi options for failover and out-of-band.

Like the NSR, the NSCP is also an open platform that can run your choice of software to expand your capabilities and reduce your tech stack. Like the NSR, the NSCP delivers Gen 3 OOB management of all connected infrastructure, enabling true end-to-end automation in data centers, branches, and other remote sites. The NSCP is the perfect replacement for enterprises utilizing the Cisco 2900 for out-of-band management, though it also provides converged branch networking capabilities at any scale.

All Nodegrid devices run the open, Linux-based Nodegrid OS which can host your choice of third-party or custom applications, freeing you from vendor lock-in. You can even integrate infrastructure orchestration tools like Puppet, Chef, and Ansible to extend automation to end devices, regardless of vendor. This is what makes Nodegrid the world’s first Gen 3 branch networking solution.

Want to see how Nodegrid stacks up against Cisco’s replacement options? Click here to download the services routers comparative matrix.

Global support and supply chain

Leaving a trusted ecosystem behind to adopt alternative options can be risky, so it’s important to find a vendor that offers the support you need to make the transition and keep your operations running smoothly. ZPE Systems offers global product support using the “follow the sun” model, which means you get support when you need it, regardless of your timezone. You also won’t have to worry about supply chain issues causing stock shortages – ZPE supplies hyperscalers in 10K+ units per quarter and has great, consistent supply chain control.

Need to replace your Cisco 2900 EOL?

To learn more about replacing your Cisco 2900 EOL solution with the vendor-neutral Nodegrid platform and our shipping in as little as two weeks, contact ZPE Systems today. Contact Us

Cisco 2900 EOL product tables with migration SKUs

Cisco 2900 EOL Model	In Scope Features	Replacement Product (modular form factor)
Cisco ISR 2901 Cisco ISR 2911 Cisco ISR 2921 Cisco ISR 2951	Serial Console Module, Routing, 16 serial ports	ZPE-NSR-816-DAC with 1 x 16 port serial module 1 x ZPE-NSR-16SRL-EXPN
Cisco ISR 2901 Cisco ISR 2911 Cisco ISR 2921 Cisco ISR 2951	Serial Console Module, Routing, 32 serial ports	ZPE-NSR-816-DAC with 2×16 port serial module 2x ZPE-NSR-16SRL-EXPN
Cisco ISR 2901 Cisco ISR 2911 Cisco ISR 2921 Cisco ISR 2951	Serial Console Module, Routing, 48 serial ports	ZPE-NSR-816-DAC with 3×16 port serial module 3x ZPE-NSR-16SRL-EXPN
Cisco ISR 2901 Cisco ISR 2911 Cisco ISR 2921 Cisco ISR 2951	Serial Console Module, Routing, 60 serial ports	ZPE-NSR-816-DAC with 4×16 port serial module 4x ZPE-NSR-16SRL-EXPN
80 serial port option – no Cisco equivalent	Serial Console Module, Routing, 80 serial ports	ZPE-NSR-816-DAC with 5×16 port serial module 5x ZPE-NSR-16SRL-EXPN

 

Internet of Things (IoT) devices are integral components of many modern businesses. In 2020, there were almost 9 billion active IoT devices—that number is predicted to exceed 25 billion by 2030. Effectively deploying, monitoring, and managing all of these devices in an enterprise environment requires powerful, centralized orchestration using an IoT device management system. This post discusses the best practices and key considerations to keep in mind when planning, designing, and building your IoT device management system.

What is an IoT device management system?

An IoT device management system provides a unified platform from which to manage all of the IoT devices in use by an organization. Many of these devices operate with little-to-no human interaction, in remote sites that may be difficult or even dangerous to access for routine maintenance. For example, IoT sensors are used inside oil pipelines to monitor crucial metrics like flow, pressure, and temperature. In addition, one organization may need to employ dozens or hundreds of different IoT devices to handle specific functions. These devices often come from different vendors, with separate management platforms, patch schedules, and configuration schemes. This results in a lot of management complexity for the IT teams responsible for provisioning, maintaining, and troubleshooting all of these devices, creating the need for an IoT device management system. The goal of such a solution is to bring all of the tasks involved in IoT device management under one roof, including:

• 
  → Onboarding: Bringing new IoT devices onto the network with the proper credentials and security policies
• → Configuration: Provisioning new IoT devices with the necessary settings
• → Maintenance: Updating firmware and applying security patches in a timely manner
• → Security: Applying enterprise security policies to all IoT devices on the network
• → Diagnostics: Collecting and analyzing logs to help identify and fix IoT device issues
• → End-of-life management: Decommissioning EOL devices so they don’t create a security risk by remaining online and unpatched

Nodegrid is a vendor-agnostic IoT device management system that enables end-to-end automation and reliable OOB management access. To see Nodegrid in action, schedule a free demo.

Best practices for building an IoT device management system

Here are some best practices and key considerations to keep in mind when planning, designing, and building your IoT device management system.

Avoid closed ecosystems

There are off-the-shelf software solutions for IoT device management that are designed to work within a single vendor’s ecosystem. While they may offer some support for third-party devices, they generally work best if you’re already operating within that vendor’s environment. For example, AWS IoT Device Management works with third-party IoT devices but requires an existing AWS infrastructure to use it effectively. These types of solutions will usually include a library of features and supported integrations, but you may not be able to integrate your preferred scripting languages, open-source tools, or other third-party components. A vendor-neutral, or vendor-agnostic, IoT device management system does not suffer from these limitations. In addition to the ability to hook into multi-vendor IoT devices, these platforms also allow you to use your choice of third-party software and scripts. A vendor-neutral solution gives you the freedom to build a truly bespoke IoT device management system that makes use of your team’s existing skills, preferred tools, and custom innovations.

Ensure 24/7 remote management access

One of the benefits of IoT devices is they can be deployed anywhere. However, maintaining continuous access to devices in remote and hard-to-reach environments can prove challenging. Natural disasters, LAN failures, ISP outages, political instability, and global pandemics can all occur with little-to-no warning, leaving organizations cut off from their critical remote IoT devices and infrastructure. Out-of-band (OOB) management solves this problem by providing an alternative path to remote network infrastructure. For example, an IoT device management system can use OOB serial consoles to create a management network that’s dedicated to the orchestration, maintenance, and troubleshooting of production network equipment. These serial consoles have multiple redundant network interfaces (e.g., 5G cellular, Fiber, and Wi-Fi) so admins can remotely access the IoT device management system even when the remote site loses its main internet connection. This ensures that organizations can recover from remote network failures faster, continue internal operations during ISP outages, and maintain continuous access to their IoT devices.

Protect IoT infrastructure with Zero Trust Security

IoT device management systems help ensure the security of remote IoT devices by simplifying tasks like firmware updates and vulnerability patch deployment. However, the IoT device management platform itself is a potential target for malicious actors hoping to gain complete control over an organization’s IoT infrastructure. That’s why organizations must protect their IoT device management system using Zero Trust Security. Zero Trust Security follows the principle of “never trust, always verify” by requiring all users, systems, and devices to continuously prove their trustworthiness as they access the network and enterprise resources. It also requires the consistent application of enterprise security policies and controls to every system and application that connects to the network, including the IoT device management system. That means, for example, that you should use technology such as two-factor authentication (2FA) and identity and access management (IAM) to control access and prevent compromised accounts from gaining control.

• ☆ Bonus tip: Zero Trust Security is easier to apply if you use a vendor-neutral IoT device management system that supports integrations with third-party security solutions like next-generation firewalls (NGFWs) and Secure Access Service Edge (SASE). This will also ensure that Zero Trust controls are in place to protect the OOB management network from unauthorized access.

However, it’s important to acknowledge that there’s currently no way to completely prevent a breach from occurring. According to the Sophos State of Ransomware 2022 survey, 66% of organizations were hit by ransomware in 2021 alone, and that number is only expected to trend upwards over time. That’s why another critical aspect of Zero Trust Security for IoT device management is building a resilient network architecture with automation tools that reduce the MTTR (mean time to recovery) when—and not if—a breach occurs. Learn more about how to implement such an architecture with ZPE’s network automation blueprint.

Building an IoT device management system with Nodegrid

An IoT device management system is meant to simplify and streamline the management of remote, hard-to-reach, and complex IoT devices and infrastructure. Vendor-neutral systems allow you to customize your platform with the third-party tools and solutions that work best for your team and your organization’s use case. Out-of-band (OOB) management ensures that IT teams have reliable, 24/7 access to remote IoT systems. Finally, Zero Trust Security protects the IoT device management system and all connected devices from malicious attacks. The Nodegrid platform from ZPE Systems is a completely vendor-agnostic IoT device management system supported by Gen 3 OOB serial consoles like the Nodegrid Serial Console Plus (NSCP) and all-in-one edge gateway routers like the Mini Services Router (MSR). Nodegrid supports integrations with your choice of custom scripts, automation tools, and security solutions so you can build a bespoke IoT device management system that addresses your organization’s unique challenges and use cases.

Ready to learn more about the Nodegrid IoT device management system?

Contact ZPE Systems today to learn more about the Nodegrid IoT device management system, contact ZPE Systems today. Contact Us