CONTACT US
1-844-4ZPE-SYS
ZPE CLOUD
Request a Quote
Schedule a Demo

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

Edge Computing vs On-Premises: A Comparison

by | Feb 23, 2024 | Application Hosting, Edge Computing, EdgeOps, Remote Network Management

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

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

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

Defining edge computing vs on-premises computing

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

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

Edge Computing vs. On-Premises Computing

Edge Computing

On-Premises Computing

  • Deployed at the edges of the network

  • Processes data on-site

  • Decentralizes enterprise network traffic

  • Deployed in centralized data centers

  • Processes data off-site

  • Requires network traffic and data to flow through a single location

The advantages of edge computing vs on-premises

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

  • Improved workload efficiency – Edge computing reduces network traffic bottlenecks and latency because data stays on the local network or even on the same device. This improves the overall speed, performance, and efficiency of all enterprise applications and services.
  • Bandwidth cost reduction – Edge computing reduces the volume of data transmitted over MPLS links between edge sites and the central data center. The cost for MPLS bandwidth is typically very high, so edge computing decreases operational costs at branch offices and other edge business sites.
  • Better data security – Any time companies transmit data off-site, there’s a risk of interception by cybercriminals. Edge computing reduces the attack surface by keeping valuable data on the local network, which improves data security and simplifies data privacy compliance.

The challenges of edge computing vs on-premises

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

  • Data storage restraints – The typical edge deployment is much smaller than a centralized data center and has fewer data storage resources, making it difficult to hold on to data long enough to process it with edge applications.
  • Fewer security controls – Edge deployments often lack the robust physical security controls utilized by data centers, such as security guards and biometric door locks, creating the need for edge-specific security solutions to protect data and devices.
  • Edge management and orchestration – Edge sites are difficult for centralized IT operations teams to monitor and troubleshoot, especially if an equipment failure, ransomware attack, or natural disaster takes down the network.

Comparing edge computing vs on-premises

 

The Pros and Cons of Edge Computing vs On-Premises Computing

Pros of Edge Computing

Cons of Edge Computing

  • Reduces network bottlenecks and latency for greater workload efficiency across the enterprise

  • Decreases MPLS bandwidth usage to make edge sites more cost-effective

  • Keeps edge data on the local network to prevent interception

  • Edge deployments have less data storage capacity

  • Edge sites lack the physical security provided by a data center

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

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

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

Want to learn more about how Nodegrid simplifies your network edge?

Request a free demo to learn how Nodegrid can help you overcome the challenges of edge computing vs on-premises computing.

Watch Demo

Network Resilience Doesn’t Mean What it Did 20 Years Ago

by | Jan 25, 2024 | Application Hosting, Data Center Management, DevOps, Edge Computing, Improve Network Security, Micro-segmentation, Minimize Impact of Disruptions, NetDevOps, Network Automation, Remote Network Management, Virtualization, Zero Touch Provisioning (ZTP), Zero Trust Security

Network resilience requirements have changed

Enterprise networks are like air. When they’re running smoothly, it’s easy to take them for granted, as business users and customers are able to go about their normal activities. But when customer service reps are suddenly cut off from their ticketing system, or family movie night turns into a game of “Is it my router, or the network?”, everyone notices. This is why network resilience is critical.

But, what exactly does resilience mean today? Let’s find out by looking at some recent real-world examples, the history of network architectures, and why network resilience doesn’t mean what it did 20 years ago.

Why does network resilience matter?

There’s no shortage of real-world examples showing why network resilience matters. The takeaway is that network resilience is directly tied to business, which means that it impacts revenue, costs, and risks. Here is a brief list of resilience-related incidents that occurred in 2023 alone:

  • FAA (Federal Aviation Administration) – An overworked contractor unintentionally deleted files, which delayed flights nationwide for an entire day.
  • Southwest Airlines – A firewall configuration change caused 16,000 flight cancellations and cost the company about $1 billion.
  • MOVEit FTP exploit – Thousands of global organizations fell victim to a MOVEit vulnerability, which allowed attackers to steal personal data for millions.
  • MGM Resorts – A human exploit and lack of recovery systems let an attack persist for weeks, causing millions in losses per day.
  • Ragnar Locker attacks – Several large organizations were locked out of IT systems for days, which slowed or halted customer operations worldwide.

What does network resilience mean?

Based on the examples above, it might seem that network resilience could mean different things. It might mean having backups of golden configs that you could easily restore in case of a mistake. It might mean beefing up your security and/or replacing outdated systems. It might mean having recovery processes in place.

So, which is it?

The answer is, it’s all of these and more.

Donald Firesmith (Carnegie Mellon) defines resilience this way: “A system is resilient if it continues to carry out its mission in the face of adversity (i.e., if it provides required capabilities despite excessive stresses that can cause disruptions).”

Network resilience means having a network that continues to serve its essential functions despite adversity. Adversity can stem from human error, system outages, cyberattacks, and even natural disasters that threaten to degrade or completely halt normal network operations. Achieving network resilience requires the ability to quickly address issues ranging from device failures and misconfigurations, to full-blown ISP outages and ransomware attacks.

The problem is, this is now much more difficult than it used to be.

How did network resilience become so complicated?

Twenty years ago, IT teams managed a centralized architecture. The data center was able to serve end-users and customers with the minimal services they needed. Being “constantly connected” wasn’t a concern for most people. For the business, achieving resilience was as simple as going on-site or remoting-in via serial console to fix issues at the data center.

Network architecture showing simplicity of data center connected via MPLS to branch office

Then in the mid-2000s, the advent of the cloud changed everything. Infrastructure, data, and computing became decentralized into a distributed mix of on-prem and cloud solutions. Users could connect from anywhere, and on-demand services allowed people to be plugged in around-the-clock. Services for work, school, and entertainment could be delivered anytime, no matter where users were.

Network architecture showing complexity of data center, CDN, remote user, branch office, all connected via many paths

Behind the scenes, this explosion of architecture created three problems for achieving network resilience, which a simple serial could no longer fix:

Too Much Work

Infrastructure, data, and computing are widely distributed. Systems inevitably break and require work, but teams don’t have the staff to keep up.

Too Much Complexity

Pairing cloud and box-based stacks creates complex networks. Teams leave systems outdated, because they don’t want to break this delicate architecture.

Too Much Risk

Unpatched, outdated systems are prime targets for packaged attacks that move at machine speed. Defense requires recovery tools that teams don’t have.

Enabling businesses to be resilient in the modern age requires an approach that’s different than simply deploying a serial console for remote troubleshooting. Gen 1 and 2 serial consoles, which have dominated the market for 20 years, were designed to solve basic issues by offering limited remote access and some automation. The problem is, these still leave teams lacking the confidence to answer questions like:

  • “How can we guarantee access to fix stuff that breaks, without rolling trucks?”
  • “Can we automate change management, without fear of breaking the network?”
  • “Attacks are inevitable — How do we stop hackers from cutting off our access?”

Hyperscalers, Internet Service Providers, Big Tech, and even the military have a resilience model that they’ve proven over the last decade. Their approach involves fully isolating command and control from data and user environments. This allows them to not only gain low-level remote access to maintain and fix systems, but also to “defend the hill” and maintain control if systems are compromised or destroyed.

This approach uses something called Isolated Management Infrastructure (IMI).

Isolated Management Infrastructure is the best practice for network resilience

Isolated Management Infrastructure is the practice of creating a management network that is completely separate from the production network. Most IT teams are familiar with out-of-band management as this network; IMI, however, provides many capabilities that can’t be hosted on a traditional serial console or OOB network. And with increasing vulnerabilities, CISA issued a binding directive specifically calling for organizations to implement IMI.

Isolated Management Infrastructure using Gen 3 serial consoles, like ZPE Systems’ Nodegrid devices, provides more than simple remote access and automation. Similar to a proper out-of-band network, IMI is completely isolated from production assets. This means there are no dependencies on production devices or connections, and management interfaces are not exposed to the internet or production gear. In the event of an outage or attack, teams retain management access, and this is just the beginning of the benefits of having IMI.

A network architecture diagram showing Isolated Management Infrastructure next to production infrastructure

IMI includes more than nine functions that are required for teams to fully service their production assets. These include:

  • Low-level access to all management interfaces, including serial, Ethernet, USB, IPMI, and others, to guarantee remote access to the entire environment
  • Open, edge-native automation to ensure services can continue operating in the event of outages or change errors
  • Computing, storage, and jumpbox capabilities that can natively host the apps and tools to deploy an IRE, to ensure fast, effective recovery from attacks

Get the guide to build IMI

ZPE Systems has worked alongside Big Tech to fulfill their requirements for IMI. In doing so, we created the Network Automation blueprint as a technical guide to help any organization build their own Isolated Management Infrastructure. Download the blueprint now to get started.

Download blueprint

Edge Computing Requirements

by | Jan 18, 2024 | Consolidation, Edge Computing, Increase Productivity, Network Automation, Network Edge Orchestration, Remote Network Management, Security Service Edge (SSE), Simplify Branch Infrastructure, Vendor Neutral Platform, Zero Touch Provisioning (ZTP)

Edge computing requirements displayed in a digital interface wheel.

The Internet of Things (IoT) and remote work capabilities have allowed many organizations to conduct critical business operations at the enterprise network’s edges. Wearable medical sensors, automated industrial machinery, self-service kiosks, and other edge devices must transmit data to and from software applications, machine learning training systems, and data warehouses in centralized data centers or the cloud. Those transmissions eat up valuable MPLS bandwidth and are attractive targets for cybercriminals.

Edge computing involves moving data processing systems and applications closer to the devices that generate the data at the network’s edges. Edge computing can reduce WAN traffic to save on bandwidth costs and improve latency. It can also reduce the attack surface by keeping edge data on the local network or, in some cases, on the same device.

Running powerful data analytics and artificial intelligence applications outside the data center creates specific challenges. For example, space is usually limited at the edge, and devices might be outdoors where power and climate control are more complex. This guide discusses the edge computing requirements for hardware, networking, availability, security, and visibility to address these concerns.

Edge computing requirements

The primary requirements for edge computing are:

7 Edge Computing Requirements
    1. Compute (processing, memory, and storage)
    2. Small, ruggedized chassis
    3. Power
    4. Wired & wireless connectivity
    5. Out-of-band (OOB) management
    6. Security
    7. Visibility

1. Compute

As the name implies, edge computing requires enough computing power to run the applications that process edge data. The three primary concerns are:

  • Processing power: CPUs (central processing units), GPUs (graphics processing units), or SoCs (systems on chips)
  • Memory: RAM (random access memory)
  • Storage: SSDs (solid state drives), SCM (storage class memory), or Flash memory
  • Coprocessors: Supplemental processing power needed for specific tasks, such as DPUs (data processing units) for AI

The specific edge computing requirements for each will vary, as it’s essential to match the available compute resources with the needs of the edge applications.

2. Small, ruggedized chassis

Space is often quite limited in edge sites, and devices may not be treated as delicately as they would be in a data center. Edge computing devices must be small enough to squeeze into tight spaces and rugged enough to handle the conditions they’ll be deployed in. For example, smart cities connect public infrastructure and services using IoT and networking devices installed in roadside cabinets, on top of streetlights, and in other challenging deployment sites. Edge computing devices in other applications might be subject to constant vibrations from industrial machinery, the humidity of an offshore oil rig, or even the vacuum of outer space.

3. Power

In some cases, edge deployments can use the same PDUs (power distribution units) and UPSes (uninterruptible power supplies) as a data center deployment. Non-traditional implementations, which might be outdoors, underground, or underwater, may require energy-efficient edge computing devices using alternative power sources like batteries or solar.

4. Wired & wireless connectivity

Edge computing systems must have both wired and wireless network connectivity options because organizations might deploy them somewhere without access to an Ethernet wall jack. Cellular connectivity via 4G/5G adds more flexibility and ideally provides network failover/out-of-band capabilities.

5. Out-of-band (OOB) management

Many edge deployment sites don’t have any IT staff on hand, so teams manage the devices and infrastructure remotely. If something happens to take down the network, such as an equipment failure or ransomware attack, IT is completely cut off and must dispatch a costly and time-consuming truck roll to recover. Out-of-band (OOB) management creates an alternative path to remote systems that doesn’t rely on any production infrastructure, ensuring teams have continuous access to edge computing sites even during outages.

6. Security

Edge computing reduces some security risks but can create new ones. Security teams carefully monitor and control data center solutions, but systems at the edge are often left out. Edge-centric security platforms such as SSE (Security Service Edge) help by applying enterprise Zero Trust policies and controls to edge applications, devices, and users. Edge security solutions often need hardware to host agent-based software, which should be factored into edge computing requirements and budgets. Additionally, edge devices should have secure Roots of Trust (RoTs) that provide cryptographic functions, key management, and other features that harden device security.

7. Visibility

Because of a lack of IT presence at the edge, it’s often difficult to catch problems like high humidity, overheating fans, or physical tampering until they affect the performance or availability of edge computing systems. This leads to a break/fix approach to edge management, where teams spend all their time fixing issues after they occur rather than focusing on improvements and innovations. Teams need visibility into environmental conditions, device health, and security at the edge to fix issues before they cause outages or breaches.

Edge Computing Learning Center

Streamlining edge computing requirements

An edge computing deployment designed around these seven requirements will be more cost-effective while avoiding some of the biggest edge hurdles. Another way to streamline edge deployments is with consolidated, vendor-neutral devices that combine core networking and computing capabilities with the ability to integrate and unify third-party edge solutions. For example, the Nodegrid platform from ZPE Systems delivers computing power, wired & wireless connectivity, OOB management, environmental monitoring, and more in a single, small device. ZPE’s integrated edge routers use the open, Linux-based Nodegrid OS capable of running Guest OSes and Docker containers for your choice of third-party AI/ML, data analytics, SSE, and more. Nodegrid also allows you to extend automated control to the edge with Gen 3 out-of-band management for greater efficiency and resilience.

Want to learn more about how Nodegrid makes edge computing easier and more cost-effective?

To learn more about consolidating your edge computing requirements with the vendor-neutral Nodegrid platform, schedule a free demo!

Request a Demo

Gartner Market Guide for Edge Computing

by | Dec 15, 2023 | Consolidation, Edge Computing, Simplify Branch Infrastructure, Vendor Neutral Platform, Virtualization

Edge-computing-strategy
In today’s highly distributed enterprise environment, a large portion of business data is generated by devices at the edges of the network. For example, many industries, from healthcare to finance, use IoT (Internet of Things) devices to collect essential and sensitive data. Transmitting this data back to a centralized data center for processing creates network latency and introduces security risks. 

Edge computing moves processing power and applications closer to the sources of data at the edges of the network, which improves performance and reduces risk. This approach is gaining popularity, with recent Gartner research finding that 69% of CIOs have already deployed edge technologies or would deploy by mid-2025. However, most edge deployments focus on individual use cases and lack a cohesive strategy, resulting in “edge sprawl”: many disparate solutions deployed all over the enterprise without centralized control or visibility.

“Edge computing without a strategy will eventually cause digital gridlock.” Thomas Bittman, Gartner Distinguished VP Analyst, in Building an Edge Computing Strategy

Edge sprawl increases complexity, reduces resilience, and ultimately hampers digital transformation. In a report published earlier this year titled “Building an Edge Computing Strategy,” Gartner provides recommendations for reducing edge sprawl with a comprehensive strategy. As we await the next Gartner Market Guide for Edge Computing, let’s discuss their recommendations for building a strategy to manage and orchestrate your edge solutions.

Building a Gartner-approved edge computing strategy

Gartner recommends building an edge computing strategy around five elements: vision, use cases, challenges, standards, and execution.

Gartner’s “Five Elements of an Edge Computing Strategy”

Edge computing vision

An edge computing vision describes the overall organizational goals and provides direction for teams and stakeholders. It should explain how edge computing supports and relates to other technology initiatives, such as cloud computing, IoT/OT devices, and artificial intelligence/machine learning, as well as how it fits into the overall digital transformation strategy.

Key components of an edge computing vision:

  • The business impact of edge computing in objective terms, such as the amount of money saved
  • How edge computing will accelerate digital transformation
  • A discussion of the digital experience improvements enabled by edge computing
  • The anticipated number of automation projects supported by edge computing
  • What edge computing use cases will be deployed
  • The targeted deployment agility in measurable terms, such as the time to deploy a new site

The edge computing vision provides the target your organization wants to reach in the next five years, and should be continuously updated as goals are met and strategies evolve. It’s crucial to clearly communicate the edge computing vision to get buy-in from executives and staff.

Edge computing use cases

There are often many edge computing use cases within an organization, and an effective edge computing strategy must identify and account for them all in order to avoid sprawl. There are three aspects to consider – the edge computing drivers, the existing edge computing use-case landscape, and potential edge computing use cases.

Edge computing drivers

Edge computing evolved to solve problems other computing architectures can’t handle. Understanding what those problems are will help you identify existing use cases and determine when edge computing should be pursued for a particular use case in the future. Gartner identifies four main edge computing drivers.

Gartner’s four edge computing drivers
Latency/Determinism
 A rapid response is required, or the response time needs to be predictable, and current latency is unacceptable 
Data/Bandwidth
 The cost of transmitting noisy, short-lived data is higher than the cost of moving compute to the edge 
Limited Autonomy
 Operations at the edge must continue even if the connection to the central data center or cloud is interrupted 
Privacy/Security
 The privacy and security risks of transmitting edge data are too high, or regulatory requirements prevent it 
An edge computing strategy should describe the organization’s specific needs and drivers that edge computing will address.

Existing edge computing use-case landscape

Many organizations already use edge computing in some form, even if they don’t call it by that name. Examples include operational technology (OT) deployments in the manufacturing industry and smart check-out systems in retail stores. An edge computing strategy must identify all existing solutions and discuss how they’ll be integrated with the chosen management technologies and best practices (more on those later).

Potential edge computing use cases

An effective edge computing strategy should also describe how the business will identify new use cases in the future. This proactive process should use the previously established edge computing drivers and involve collaboration between IT and the various business units within the organization. Gartner recommends creating a “clearinghouse” for new use case ideas, a structured process for identifying, reviewing, and prioritizing potential edge use cases.

Edge computing challenges

Even as edge computing solves business problems, it creates additional challenges that the strategy must address with new technologies and processes. Gartner identifies six major edge computing challenges to focus on while you develop an edge computing strategy.

  1. Enabling extensibility – Purpose-built edge computing solutions can’t adapt when workloads change or grow, so an edge computing strategy should leave room for growth by using extensible, vendor-neutral platforms that allow for expansion and integration.
  2. Extracting value from edge data – As edge devices generate more and more data, the difficulty of quickly extracting value from that data rises, so organizations should look for ways to deploy AI training and data analytics solutions alongside edge computing units.
  3. Governing edge data – Edge computing sites often have more significant data storage constraints than traditional data centers, so quickly distinguishing between valuable data and destroyable junk is critical to edge ROIs and requires careful governance.
  4. Securing the edge – Edge deployments are highly distributed in locations that lack many security features in a traditional data center, adding risk and increasing the attack surface, so organizations should protect edge computing nodes with a multi-layered defense including zero-trust policies, strong authentication, and network micro-segmentation. Orgs also need a way to take back control of edge infrastructure during ransomware attacks, such as an isolated recovery environment (IRE).
  5. Supporting edge-native applications – Edge-native applications are designed for the edge from the bottom up, so organizations should deploy platforms that support these applications without increasing the technical debt, meaning they should use familiar technologies and interoperate with existing systems.
  6. Managing and orchestrating the edge – Environmental issues, power failures, and network outages can cut technical teams off from critical edge infrastructure, so organizations need edge management and orchestration (EMO) with environmental monitoring and out-of-band (OOB) connectivity.

Gartner recommends focusing your edge computing strategy on mitigating the specific risks, challenges, and inhibitors.

Edge computing standards

Edge computing use cases are often highly diverse, even within a single organization, so it’s critical to establish a set of unifying standards and guidelines to reduce edge sprawl. Many organizations use a cloud center of excellence (CCOE) to govern their cloud computing architecture, so Gartner recommends establishing a similar edge center of excellence (ECOE) based on three pillars.

Gartner’s Edge Center of Excellence (ECOE)
Governance:
  • Maintain the edge computing strategy
  • Develop security, data, and adoption policies
  • Establish metrics to measure value and ROI
Technologies:
  • Reference architectures
  • Technology and architecture standards
  • Trusted vendor list
  • Vendor selection process
Best Practices/Skills:
  • Solutions consulting
  • Training and role definition
  • Expertise evangelization

For an effective edge computing strategy, Gartner recommends creating a unifying set of standards, guidelines, and best practices to be used across all edge computing deployments.

Edge computing execution

An edge computing strategy should include process documentation for the initial deployment of new edge rollouts. Gartner identifies six steps that help ensure successful edge computing launches.

  • Proof of Concept – Test edge deployments in non-production and get feedback from stakeholders
  • Proof of Production – Conduct a pilot to evaluate how you’ll operate, manage, and monitor an edge project at full scale
  • Phased Rollout – Have a phased deployment plan including scale, regions, and functionality
  • Surprises – Expect the unexpected by including guidelines in your edge computing strategy for monitoring and managing changes
  • Evolution – Edge projects frequently change direction based on evolving requirements or unexpected changes, so extensibility is crucial
  • Next-Best Action – Plans for the future frequently change direction, so have alternatives in your strategy to help guide these evolutions

An edge computing strategy that covers all six steps will streamline deployments and improve the agility of edge execution.

What to Expect from the Gartner Market Guide for Edge Computing

Last year, the Gartner Market Guide for Edge Computing discussed the issue of companies deploying individual edge solutions to handle individual use cases without any unified management and oversight. Part of the problem is that the edge computing market is still immature, and another hurdle is vendor lock-in. When edge computing solutions can’t interoperate with other vendors’ hardware and software, teams cannot deploy the universal hardware and unifying orchestration platforms to manage edge architectures efficiently.

Based on the market analysis provided in “Building an Edge Computing Strategy,” Gartner still heavily emphasizes the need to reduce edge sprawl with centralized, vendor-neutral edge management and orchestration (EMO). You can expect Gartner’s next market guide for edge computing to continue pushing for unified management and to highlight vendors with scalable, extensible, open edge computing solutions.

Building an edge computing strategy with Nodegrid

Nodegrid is a vendor-neutral edge infrastructure orchestration platform from ZPE Systems that can help you solve all six of Gartner’s edge computing challenges.

  • Enabling extensibility – Nodegrid’s modular, extensible devices are easy to scale and adapt to handle changing workloads. Nodegrid management hardware runs the open, Linux-based Nodegrid OS, which can host your choice of third-party edge computing applications, so you can deploy and change edge software without buying additional hardware.
  • Extracting value from edge data – Nodegrid’s powerful, extensible computing hardware can run data analysis, machine learning, and artificial intelligence applications to help extract additional value from the massive quantities of data at the edge.
  • Governing edge data – Nodegrid’s ZPE Cloud platform offers a data lake application that helps process and organize edge data.
  • Securing the edge – Nodegrid uses innovative hardware security and advanced, zero-trust authentication methods to defend edge networks, devices, and applications.
  • Supporting edge-native applications – Nodegrid supports Docker containers and other edge-native technologies, allowing teams to use their choice of software platforms to reduce technical debt.
  • Managing and orchestrating the edge – Nodegrid’s environmental monitoring sensors give remote teams real-time insights into conditions in edge deployment sites so they can respond to climate issues and power fluctuations as they occur. Nodegrid’s out-of-band (OOB) management creates an isolated management infrastructure that doesn’t rely on production network resources, giving teams a lifeline to troubleshoot and recover from outages, failures, and cyberattacks faster and more cost-effectively.

Nodegrid is a vendor-neutral Services Delivery Platform that brings all the components of your edge computing strategy under one management umbrella so you can overcome your biggest edge computing challenges.

Get streamlined edge computing with Nodegrid

To learn more about vendor-neutral edge management and orchestration (EMO) as described in the Gartner market guide for edge computing, contact ZPE Systems.

Request a Demo

What is a Hyperscale Data Center?

by | Dec 13, 2023 | Consolidation, Data Center Management, Edge Computing, EdgeOps, Improve Network Security, Increase Productivity, NetDevOps, NetDevOps Transformation, Network Automation, Network Edge Orchestration, Security Service Edge (SSE), Vendor Neutral Platform, Zero Touch Provisioning (ZTP)

shutterstock_2204212039(1)

As today’s enterprises race toward digital transformation with cloud-based applications, software-as-a-service (SaaS), and artificial intelligence (AI), data center architectures are evolving. Organizations rely less on traditional server-based infrastructures, preferring the scalability, speed, and cost-efficiency of cloud and hybrid-cloud architectures using major platforms such as AWS and Google. These digital services are supported by an underlying infrastructure comprising thousands of servers, GPUs, and networking devices in what’s known as a hyperscale data center.

The size and complexity of hyperscale data centers present unique management, scaling, and resilience challenges that providers must overcome to ensure an optimal customer experience. This blog explains what a hyperscale data center is and compares it to a normal data center deployment before discussing the unique challenges involved in managing and supporting a hyperscale deployment.

What is a hyperscale data center?

As the name suggests, a hyperscale data center operates at a much larger scale than traditional enterprise data centers. A typical data center houses infrastructure for dozens of customers, each containing tens of servers and devices. A hyperscale data center deployment supports at least 5,000 servers dedicated to a single platform, such as AWS. These thousands of individual machines and services must seamlessly interoperate and rapidly scale on demand to provide a unified and streamlined user experience.

The biggest hyperscale data center challenges

Operating data center deployments on such a massive scale is challenging for several key reasons.

 
 

Hyperscale Data Center Challenges

Complexity

Hyperscale data center infrastructure is extensive and complex, with thousands of individual devices, applications, and services to manage. This infrastructure is distributed across multiple facilities in different geographic locations for redundancy, load balancing, and performance reasons. Efficiently managing these resources is impossible without a unified platform, but different vendor solutions and legacy systems may not interoperate, creating a fragmented control plane.

Scaling

Cloud and SaaS customers expect instant, streamlined scaling of their services, and demand can fluctuate wildly depending on the time of year, economic conditions, and other external factors. Many hyperscale providers use serverless, immutable infrastructure that’s elastic and easy to scale, but these systems still rely on a hardware backbone with physical limitations. Adding more compute resources also requires additional management and networking hardware, which increases the cost of scaling hyperscale infrastructure.

Resilience

Customers rely on hyperscale service providers for their critical business operations, so they expect reliability and continuous uptime. Failing to maintain service level agreements (SLAs) with uptime requirements can negatively impact a provider’s reputation. When equipment failures and network outages occur - as they always do, eventually - hyperscale data center recovery is difficult and expensive.

Overcoming hyperscale data center challenges requires unified, scalable, and resilient infrastructure management solutions, like the Nodegrid platform from ZPE Systems.

How Nodegrid simplifies hyperscale data center management

The Nodegrid family of vendor-neutral serial console servers and network edge routers streamlines hyperscale data center deployments. Nodegrid helps hyperscale providers overcome their biggest challenges with:

  • A unified, integrated management platform that centralizes control over multi-vendor, distributed hyperscale infrastructures.
  • Innovative, vendor-neutral serial console servers and network edge routers that extend the unified, automated control plane to legacy, mixed-vendor infrastructure.
  • The open, Linux-based Nodegrid OS which hosts or integrates your choice of third-party software to consolidate functions in a single box.
  • Fast, reliable out-of-band (OOB) management and 5G/4G cellular failover to facilitate easy remote recovery for improved resilience.

The Nodegrid platform gives hyperscale providers single-pane-of-glass control over multi-vendor, legacy, and distributed data center infrastructure for greater efficiency. With a device like the Nodegrid Serial Console Plus (NSCP), you can manage up to 96 devices with a single piece of 1RU rack-mounted hardware, significantly reducing scaling costs. Plus, the vendor-neutral Nodegrid OS can directly host other vendors’ software for monitoring, security, automation, and more, reducing the number of hardware solutions deployed in the data center.

Nodegrid’s out-of-band (OOB) management creates an isolated control plane that doesn’t rely on production network resources, giving teams a lifeline to recover remote infrastructure during outages, equipment failures, and ransomware attacks. The addition of 5G/4G LTE cellular failover allows hyperscale providers to keep vital services running during recovery operations so they can maintain customer SLAs.

Want to learn more about Nodegrid hyperscale data center solutions from ZPE Systems?

Nodegrid’s vendor-neutral hardware and software help hyperscale cloud providers streamline their operations with unified management, enhanced scalability, and resilient out-of-band management. Request a free Nodegrid demo to see our hyperscale data center solutions in action.

Request a Demo

Healthcare Network Design

by | Nov 20, 2023 | Consolidation, Edge Computing, EdgeOps, Improve Network Security, Increase Productivity, NetDevOps, NetDevOps Transformation, Network Automation, Network Edge Orchestration, Security Service Edge (SSE), Vendor Neutral Platform, Zero Touch Provisioning (ZTP)

Edge Computing in Healthcare
In a healthcare organization, IT’s goal is to ensure network and system stability to improve both patient outcomes and ROI. The National Institutes of Health (NIH) provides many recommendations for how to achieve these goals, and they place a heavy focus on resilience engineering (RE). Resilience engineering enables a healthcare organization to resist and recover from unexpected events, such as surges in demand, ransomware attacks, and network failures. Resilient architectures allow the organization to continue operating and serving patients during major disruptions and to recover critical systems rapidly.

This guide to healthcare network design describes the core technologies comprising a resilient network architecture before discussing how to take resilience engineering to the next level with automation, edge computing, and isolated recovery environments.

Table of Contents
  1. Core healthcare network resilience technologies
  2. Extending automated control over healthcare networks
  3. Improving performance and security with edge computing
  4. Increasing resilience with isolated recovery environments
  5. Resilient healthcare network design with Nodegrid

Core healthcare network resilience technologies

A resilient healthcare network design includes resilience systems that perform critical functions while the primary systems are down. The core technologies and capabilities required for resilience systems include:

  • Full-stack networking – Routing, switching, Wi-Fi, voice over IP (VoIP), virtualization, and the network overlay used in software-defined networking (SDN) and software-defined wide area networking (SD-WAN)
  • Full compute capabilities – The virtual machines (VMs), containers, and/or bare metal servers needed to run applications and deliver services
  • Storage – Enough to recover systems and applications as well as deliver content while primary systems are down

These are the main technologies that allow healthcare IT teams to reduce disruptions and streamline recovery. Once organizations achieve this base level of resilience, they can evolve by adding more automation, edge computing, and isolated recovery infrastructure.

Extending automated control over healthcare networks

Automation is one of the best tools healthcare teams have to reduce human error, improve efficiency, and ensure network resilience. However, automation can be hard to learn, and scripts take a long time to write, so having systems are easily deployable with low technical debt is critical. Tools like ZTP (zero-touch provisioning), and the integration of technology like Infrastructure as Code (IaC), accelerate recovery by automating device provisioning. Healthcare organizations can use automation technologies such as AIOps with resilience systems technologies like out-of-band (OOB) management to monitor, maintain, and troubleshoot critical infrastructure.

Using automation to observe and control healthcare networks helps prevent failures from occuring, but when trouble does actually happen, resilience systems ensure infrastructure and services are quickly returned to health or rerouted when needed.

Improving performance and security with edge computing

The healthcare industry is one of the biggest adopters of IoT (Internet of Things) technology. Remote, networked medical devices like pacemakers, insulin pumps, and heart rate monitors collect a large volume of valuable data that healthcare teams use to improve patient care. Transmitting that data to a software application in a data center or cloud adds latency and increases the chances of interception by malicious actors. Edge computing for healthcare eliminates these problems by relocating applications closer to the source of medical data, at the edges of the healthcare network. Edge computing significantly reduces latency and security risks, creating a more resilient healthcare network design.

Note that teams also need a way to remotely manage and service edge computing technologies. Find out more in our blog Edge Management & Orchestration.

Increasing resilience with isolated recovery environments

Ransomware is one of the biggest threats to network resilience, with attacks occurring so frequently that it’s no longer a question of ‘if’ but ‘when’ a healthcare organization will be hit.

Recovering from ransomware is especially difficult because of how easily malicious code can spread from the production network into backup data and systems. The best way to protect your resilience systems and speed up ransomware recovery is with an isolated recovery environment (IRE) that’s fully separated from the production infrastructure.

 

A diagram showing the components of an isolated recovery environment.

An IRE ensures that IT teams have a dedicated environment in which to rebuild and restore critical services during a ransomware attack, as well as during other disruptions or disasters. An IRE does not replace a traditional backup solution, but it does provide a safe environment that’s inaccessible to attackers, allowing response teams to conduct remediation efforts without being detected or interrupted by adversaries. Isolating your recovery architecture improves healthcare network resilience by reducing the time it takes to restore critical systems and preventing reinfection.

To learn more about how to recover from ransomware using an isolated recovery environment, download our whitepaper, 3 Steps to Ransomware Recovery.

Resilient healthcare network design with Nodegrid

A resilient healthcare network design is resistant to failures thanks to resilience systems that perform critical functions while the primary systems are down. Healthcare organizations can further improve resilience by implementing additional automation, edge computing, and isolated recovery environments (IREs).

Nodegrid healthcare network solutions from ZPE Systems simplify healthcare resilience engineering by consolidating the technologies and services needed to deploy and evolve your resilience systems. Nodegrid’s serial console servers and integrated branch/edge routers deliver full-stack networking, combining cellular, Wi-Fi, fiber, and copper into software-driven networking that also includes compute capabilities, storage, vendor-neutral application & automation hosting, and cellular failover required for basic resilience. Nodegrid also uses out-of-band (OOB) management to create an isolated management and recovery environment without the cost and hassle of deploying an entire redundant infrastructure.

Ready to see how Nodegrid can improve your network’s resilience?

Nodegrid streamlines resilient healthcare network design with consolidated, vendor-neutral solutions. Request a free demo to see Nodegrid in action.

Request a Demo