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

The Future of Data Centers: Overcoming the Challenges of Lights-Out Operations

Future of lights-out data centers

In a recent article, Y Combinator announced its search for startups aiming to eliminate human intervention in data center development and operation. While one half of this vision seems focused on automating the design and construction of data centers, the other half – focused on fully automating operations (a.k.a. “lights-out”) – is already a reality. ZPE Systems and Legrand are enabling enterprises to achieve this kind of operation by providing the best practices that are already in use in hyperscale data centers for lights-out management.

The Need for Lights-Out Data Centers

The growth of cloud computing, edge deployments, and AI-driven workloads means data centers need to be as efficient, scalable, and resilient as possible. The challenge is that because there is so much infrastructure to manage, the buildout and operation of these data centers becomes very costly and time consuming.

Diane Hu, a YC group partner who previously worked in augmented reality and data science, says, “Hyperscale data center projects take many years to complete. We need more data centers that are created faster and cheaper to build out the infrastructure needed for AI progress. Whether it be in power infrastructure, cooling, procurement of all materials, or project management.”

Dalton Caldwell, a YC managing director who also cofounded App.net, adds, “Software is going to handle all aspects of planning and building a new data center or warehouse. This can include site selection, construction, set up, and ongoing management. They’re going to be what’s called lights-out. There’s going to be robots, autonomously operating 24/7. We want to fund startups to help create this vision.”

In terms of ongoing management and operations, bringing this vision to life will require organizations to overcome several significant problems:

  1. Rising Operational Costs: Staffing and maintaining on-site engineers 24/7 is costly. Labor expenses, training, and turnover increase operational overhead.
  2. Human Error and Downtime: Human error is the leading cause of downtime, so having manual processes often leads to costly outages caused by typos, misconfigurations, and slow response times.
  3. Security Threats: Physical access to data centers increases the risk of insider threats, breaches, and unauthorized interventions.
  4. Remote Site Management: Managing geographically distributed data centers and edge locations requires staff to be on-site. What’s needed is a scalable and efficient solution that lets staff remotely perform every job, outside of physically installing equipment.
  5. Sustainability and Energy Efficiency: On-site workers have specific heating/cooling needs that must be met in order to comfortably perform their jobs. Reducing human presence in data centers enables better energy management, which can lower carbon footprints and reduce cooling requirements.

The Roadblocks to Lights-Out Data Centers

Despite the obvious benefits, organizations struggle to implement fully autonomous data center operations. The obstacles include:

  • Legacy Infrastructure: Many enterprises still rely on outdated equipment that lacks the necessary integrations for automation and remote control. Adding functions or capabilities typically means deploying more physical boxes, which increases costs and complexity.
  • Network Resilience and Connectivity: Traditional in-band network management fails during outages, making it difficult to troubleshoot and recover remotely. Without complete separation of the management network from production networks, organizations are unable to achieve true resilience from errors, outages, and breaches.
  • Integration Challenges: Implementing AI-driven automation, OOB management, and cybersecurity protections requires seamless interoperability between different vendors’ solutions.
  • Security Concerns: A fully automated data center must have robust access controls, zero-trust security frameworks, and remote threat mitigation capabilities.
  • Skill Gaps: The shift to automation necessitates retraining IT staff, who may be unfamiliar with the latest technologies required to maintain a hands-off data center.

Direct remote access is risky

Image: The traditional management approach relies on production assets. This makes it impossible to achieve resilience, because production failures cut off remote admin access.

How ZPE Systems is Powering Lights-Out Operations

ZPE Systems is already helping companies overcome these challenges and transition to lights-out data center operations. As part of Legrand, ZPE is a key component in a total solution offering that includes everything from cabinets and containment to power distribution and remote access. By leveraging out-of-band management, intelligent automation, and zero-trust security, ZPE enables enterprises to manage their infrastructure remotely and securely.

Isolated Management Infrastructure is critical to lights-out data center operations.

Image: ZPE Systems’ Nodegrid creates an Isolated Management Infrastructure. This gives admins secure remote access, even when the production network fails or suffers an attack.

Key benefits of this management infrastructure include:

  • Reliable Remote Access: ZPE’s OOB solutions ensure secure access to critical infrastructure even when primary networks fail. This is made possible by ZPE’s Isolated Management Infrastructure (IMI), which creates a fully separate management network. This single-box solution helps organizations achieve lights-out operations without device sprawl.
  • Automated Remediation: ZPE’s platform hosts third party applications, Docker containers, and AI and automation solutions. Organizations can leverage data about device health, telemetry, environmentals, and in-band performance, to resolve issues fast and prevent downtime.
  • Hardened Security: ZPE’s solutions are built with security in mind, from local MFA, to self-encrypted disk and signed OS. ZPE also has the most security certifications and validations, including SOC2 Type 2, FIPS 140-3, and ISO27001. Read our full supply chain security assurance pdf.
  • Multi-Vendor Integration: ZPE is the only drop-in solution that works across diverse environments, regardless of which vendor solutions are already in place. This makes it easy to deploy IMI and the resilience architecture necessary for achieving lights-out operations.
  • Comprehensive Data Center Solutions: With Legrand’s full suite of data center infrastructure, organizations benefit from a fully integrated approach that ensures efficiency, scalability, and resilience.

Lights-out data centers are an achievable reality. By addressing the key challenges and leveraging advanced remote management solutions, enterprises can reduce operational costs, enhance security, and improve efficiency. As part of Legrand, ZPE Systems continues to lead the charge in enabling this transformation for organizations across the globe.

See How Vapor IO Achieved Lights-Out Operations with ZPE Systems

Vapor IO is re-architecting the internet. They deploy micro data centers at the network edge, serving markets across the U.S. and Europe. When they needed to achieve true lights-out operations, they chose ZPE Systems’ Nodegrid. Find out how this solution reduced deployment times to just one hour and delivered additional time and cost savings. Download the full case study below.

Get in Touch for a Demo of Lights-Out Data Center Operations

Our engineers are ready to walk you through lights-out operations. Click below to set up a demo.

Why Out-of-Band Management Is Critical to AI Infrastructure

Out-of-Band Management for AI

Artificial intelligence is transforming every corner of industry. Machine learning algorithms are optimizing global logistics, while generative AI tools like ChatGPT are reshaping everyday work and communications. Organizations are rapidly adopting AI, with the global AI market expected to reach $826 billion by 2030, according to Statista. While this growth is reshaping operations and outcomes for organizations in every industry, it brings significant challenges for managing the infrastructure that supports AI workloads.

The Rapid Growth of AI Adoption

AI is no longer a technology that lives only in science fiction. It’s real, and it has quickly become crucial to business strategy and the overall direction of many industries. Gartner reports that 70% of enterprise executives are actively exploring generative AI for their organizations, and McKinsey highlights that 72% of companies have already adopted AI in at least one business function.

It’s easy to understand why organizations are rapidly adopting AI. Here are a few examples of how AI is transforming industries:

  • Healthcare: AI-driven diagnostic tools have improved disease detection rates by up to 30x, while drug discovery timelines are being slashed from years to months.
  • Retail: E-commerce platforms use AI to power personalized recommendations, leading to a revenue increase of 5-25%.
  • Manufacturing: AI in predictive maintenance can help increase productivity by 25%, lower maintenance costs by 25%, and reduce machine downtime by 70%.

AI is a powerful tool that can bring profound outcomes wherever it’s used. But it requires a sophisticated infrastructure of power distribution, cooling systems, computing, GPUs, servers, and networking gear, and the challenge lies in managing this infrastructure.

Infrastructure Challenges Unique to AI

AI environments are complex, with workloads that are both resource-intensive and latency-sensitive. This means organizations face several challenges that are unique to AI:

 

  1. Skyrocketing Energy Demands: AI racks consume between 40kW and 200kW of power, which is 10x more than traditional IT equipment. Energy efficiency in the AI data center is a top priority, especially as data centers account for 1% of global electricity consumption.
  2. Cost of Downtime: AI systems are especially vulnerable to interruptions, which can cause a ripple effect and lead to high costs. A single server failure can disrupt entire model training processes, costing enterprises $9,000 per minute in downtime, as estimated by Uptime Institute.
  3. Cybersecurity Risks: AI processes sensitive data, making AI data centers prime targets for attack. Sophos reports that in 2024, 59% of organizations suffered a ransomware attack, and the average cost to recover (excluding ransom payment) was $2.73 million.
  4. Operational Complexity: AI environments rely on a diverse set of hardware and software systems. Monitoring and managing these components effectively requires real-time visibility into thermal conditions, humidity, particulates, and other environmental and device-related factors.

The Role of Out-of-Band Management in AI

Out-of-band (OOB) management is a must-have for organizations scaling their AI capabilities. Unlike traditional in-band systems that rely on the production network, OOB operates independently to give teams uninterrupted access and control. They can remotely perform monitoring and maintenance tasks to AI infrastructure, troubleshooting, and complete system recovery even if the production network goes offline.

 

How OOB Management Solves Key Challenges:

  • Minimized Downtime: With OOB, IT teams can drastically reduce downtime by troubleshooting issues remotely rather than dispatching teams on-site.
  • Energy Efficiency: Real-time monitoring and optimization of power distribution enable organizations to eliminate zombie servers and other inefficiencies.
  • Enhanced Security: OOB systems isolate management traffic from production networks per CISA’s best practice recommendations, which reduces the attack surface and mitigates cybersecurity risks.
  • Operational Efficiency: Remote monitoring via OOB offers a complete view of environmental conditions and device health, so teams can operate proactively and prevent issues before failures happen.

Use Cases: Out-of-Band Management for AI

There’s no shortage of use cases for AI, but organizations often overlook implementing out-of-band in their environment. Aside from using OOB in AI data centers, here are some real-world use cases of out-of-band management for AI.

1. Autonomous Vehicle R&D

Developers of self-driving technology find it difficult to manage their high-density AI clusters, especially because outages delay testing and development. By implementing OOB management, these developers can reduce recovery times from hours to minutes and shorten development timelines.

2. Financial Services Firms

Banks deploy AI to detect and combat fraud, but these power-hungry systems often lead to inefficient energy usage in the data center. With OOB management, they can gain transparency into GPU and CPU utilization. Not only can they eliminate energy waste, but they can optimize resources to improve model processing speeds.

3. University AI Labs

Universities run AI research on supercomputers, but this strains the underlying infrastructure with high temperatures that can cause failures. OOB management can provide real-time visibility into air temperature, device fan speed, and cooling systems to prevent infrastructure failures.

Download Our Guide, Solving AI Infrastructure Challenges with Out-of-Band Management

Out-of-band management is the key to having reliable, high-performing AI infrastructure. But what does it look like? What devices does it work with? How do you implement it?

Download our whitepaper Solving AI Infrastructure Challenges with Out-of-Band Management for answers. You’ll also get Nvidia’s SuperPOD reference design along with a list of devices that integrate with out-of-band. Click the button for your instant download.

Lantronix G520: Alternative Options

The G520 is a series of cellular gateways from Lantronix designed for industrial Internet of Things (IIoT), security, and transport use cases. While it provides redundant networking capabilities, it lacks critical resilience features such as out-of-band management (OOBM). This guide explains where the G520 falls short and why it matters before describing alternative options that deliver multi-functional IIoT capabilities and network resilience.

Why consider Lantronix G520 alternatives?

The Lantronix G520 is a cellular gateway that provides network connectivity, failover, and load balancing for IoT devices. However, it lacks serial console management capabilities, which means you need a separate device for remote management and OOBM. Out-of-band management is a crucial technology that separates the network control plane from the data plane to prevent breaches of management interfaces. OOBM also improves resilience by using a dedicated network (like cellular LTE) that gives remote teams a lifeline to recover from equipment failures, network outages, and breaches.

Percepxion G520

G520 gateways are managed with the Percepxion cloud platform, while cellular data plans and VPN security are managed separately with the cloud-based Connectivity Services software. These software solutions cannot be extended with third-party integrations, so teams must manage two separate Lantronix platforms and use separate software for monitoring, security, etc. Closed software also prevents teams from utilizing third-party automation and orchestration and creates a lot of management complexity, increasing the risk of human error and reducing operational efficiency.

G520 hardware also lacks extensibility due to an ARM architecture and tiny 256MB Flash storage. This essentially makes it a single-purpose device, with organizations needing to deploy additional appliances to run edge workloads, security applications, and other third-party software. There’s another IIoT gateway solution that combines edge networking capabilities with OOBM, the ability to run or integrate third-party applications, and a unified, extensible cloud management platform that extends automation and orchestration to all the devices in your deployment.

Nodegrid alternatives for the G520

Nodegrid is a line of vendor-neutral, edge networking solutions from ZPE Systems. The closest alternative to the Lantronix G520 is the Nodegrid Mini Services Router (or Mini SR). 

Nodegrid Mini SR vs. Lantronix G520

 

Nodegrid Mini SR

Lantronix G520

CPU

x86-64bit Intel Processor

600 MHz ARM-based CPU 

Guest OS

1

0

Docker Apps

1-2

0

Storage

16GB SED

256MB Flash

Wi-Fi

Yes

Yes

Cloud Management

ZPE Cloud

Lantronix Percepxion, Connectivity Services

Cellular 

Dual-SIM

Dual-SIM

Serial

Via USB

No

Network

2 x 1Gb ETH

1 x 10/100 ETH

The Mini SR is a compact, fanless edge gateway small enough to be easily installed in any industrial environment. In addition to gateway, networking, and failover capabilities, the Mini SR provides OOBM for all connected devices, turning it into an IoT device management solution. Nodegrid’s OOBM completely isolates IoT management interfaces and ensures they’re remotely available 24/7 even during ISP outages and ransomware infections.

Mini-SR-Rear

The Mini SR and all connected devices are managed with ZPE Cloud, an intuitive platform that’s easily extensible with third-party integrations for infrastructure automation, edge security, SCADA software, and much more. The best part is that ZPE Cloud is a unified solution that gives administrators a single-pane-of-glass management experience for convenience and efficiency. 

Mini-SR-Diagram-980×748

The Mini SR and all other Nodegrid hardware solutions run on the vendor-neutral, Linux-based Nodegrid OS and come with robust Intel architectures. As a result, they can host Guest OS and even Docker containers for third-party applications, reducing the need for additional hardware appliances in cramped industrial environments. The Mini SR is an all-in-one solution that reduces edge expenses and complexity while improving resilience and operational efficiency.

Other Nodegrid alternatives for the Lantronix G520

Depending on your use case, you may have other reasons to consider G520 alternatives, such as the need for a complete serial console management solution, or the desire to run artificial intelligence (AI) workflows at the edge without deploying expensive single-purpose GPUs. Luckily, the Nodegrid line has solutions for every edge use case and pain point.

Comparing Nodegrid SRs

Nodegrid Mini SR Nodegrid Gate SR Nodegrid Hive SR Nodegrid Link SR Nodegrid Bold SR Nodegrid Net SR
Potential Use Cases Edge IoT, IIoT, OT, and IoMD (Internet of Medical Devices) deployments Branch service delivery and AI Distributed branch and edge sites like manufacturing plants Branch, IoT, and M2M (Machine-to-Machine) deployments Branch and edge deployments like telecom, retail, and oil & gas Large branches, edge data centers
CPU x86-64bit Intel Processor x86-64bit Intel Processor x86-64bit Intel Processor x86-64bit Intel Processor x86-64bit Intel Processor x86-64bit Intel Processor
Guest OS 1 1-3 1-2 1 1 1-6
Docker Apps 1-2 1-4 1-3 1-2 1-2 1-4
Storage 16GB SED 32GB – 128GB 16GB – 128GB 16GB – 128GB 32GB – 128GB 32GB – 128GB
Secondary Additional Storage – Up to 4TB Up to 4TB Up to 4TB Up to 4TB Up to 4TB
PoE+ Output – Yes – – – Yes
Wi-Fi Yes Yes Yes Yes Yes Yes
ZPE Cloud Support Yes Yes Yes Yes Yes Yes
Cellular (Dual-SIM) 1 1-2 1-2 1 1-2 1-4
Serial Via USB 8 8 1 8 16-80
Network 2 x 1Gb ETH 2 x SFP+, 5 x Gb ETH, 4 x 1Gb ETH PoE+ 2x GbE ETH, 2x 10 Gbps, 4x 10/100/1000/2.5 Gbps RJ-45 1 x Gb ETH 1 x SFP 5 x Gb ETH 2 1Gb ETH, 2 SFP+, Multiple Cards
GPIO – 2 DIO, 1 OUT, 1 Relay – 2 DIO, 2 OUT – –
Power Single Single or Redundant Single Single Single Single or Redundant
Data Sheet Download Download Download Download Download Download

Get a complete IIoT solution with Nodegrid

The Nodegrid Mini SR improves upon the Lantronix G520 by consolidating edge networking capabilities and offering a vendor-neutral platform to host and integrate all your third-party applications. Schedule a demo to see Nodegrid in action!

Edge Computing Platforms: Insights from Gartner’s 2024 Market Guide

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

Edge computing allows organizations to process data close to where it’s generated, such as in retail stores, industrial sites, and smart cities, with the goal of improving operational efficiency and reducing latency. However, edge computing requires a platform that can support the necessary software, management, and networking infrastructure. Let’s explore the 2024 Gartner Market Guide for Edge Computing, which highlights the drivers of edge computing and offers guidance for organizations considering edge strategies.

What is an Edge Computing Platform (ECP)?

Edge computing moves data processing close to where it’s generated. For bank branches, manufacturing plants, hospitals, and others, edge computing delivers benefits like reduced latency, faster response times, and lower bandwidth costs. An Edge Computing Platform (ECP) provides the foundation of infrastructure, management, and cloud integration that enable edge computing. The goal of having an ECP is to allow many edge locations to be efficiently operated and scaled with minimal, if any, human touch or physical infrastructure changes.

Before we describe ECPs in detail, it’s important to first understand why edge computing is becoming increasingly critical to IT and what challenges arise as a result.

What’s Driving Edge Computing, and What Are the Challenges?

Here are the five drivers of edge computing described in Gartner’s report, along with the challenges that arise from each:

1. Edge Diversity

Every industry has its unique edge computing requirements. For example, manufacturing often needs low-latency processing to ensure real-time control over production, while retail might focus on real-time data insights to deliver hyper-personalized customer experiences.

Challenge: Edge computing solutions are usually deployed to address an immediate need, without taking into account the potential for future changes. This makes it difficult to adapt to diverse and evolving use cases.

2. Ongoing Digital Transformation

Gartner predicts that by 2029, 30% of enterprises will rely on edge computing. Digital transformation is catalyzing its adoption, while use cases will continue to evolve based on emerging technologies and business strategies.

Challenge: This rapid transformation means environments will continue to become more complex as edge computing evolves. This complexity makes it difficult to integrate, manage, and secure the various solutions required for edge computing.

3. Data Growth

The amount of data generated at the edge is increasing exponentially due to digitalization. Initially, this data was often underutilized (referred to as the “dark edge”), but businesses are now shifting towards a more connected and intelligent edge, where data is processed and acted upon in real time.

Challenge: Enormous volumes of data make it difficult to efficiently manage data flows and support real-time processing without overwhelming the network or infrastructure.

4. Business-Led Requirements

Automation, predictive maintenance, and hyper-personalized experiences are key business drivers pushing the adoption of edge solutions across industries.

Challenge: Meeting business requirements poses challenges in terms of ensuring scalability, interoperability, and adaptability.

5. Technology Focus

Emerging technologies such as AI/ML are increasingly deployed at the edge for low-latency processing, which is particularly useful in manufacturing, defense, and other sectors that require real-time analytics and autonomous systems.

Challenge: AI and ML make it difficult for organizations to determine how to strike a balance between computing power and infrastructure costs, without sacrificing security.

What Features Do Edge Computing Platforms Need to Have?

To address these challenges, here’s a brief look at three core features that ECPs need to have according to Gartner’s Market Guide:

  1. Edge Software Infrastructure: Support for edge-native workloads and infrastructure, including containers and VMs. The platform must be secure by design.
  2. Edge Management and Orchestration: Centralized management for the full software stack, including orchestration for app onboarding, fleet deployments, data storage, and regular updates/rollbacks.
  3. Cloud Integration and Networking: Seamless connection between edge and cloud to ensure smooth data flow and scalability, with support for upstream and downstream networking.

A simple diagram showing the computing and networking capabilities that can be delivered via Edge Management and Orchestration.

Image: A simple diagram showing the computing and networking capabilities that can be delivered via Edge Management and Orchestration.

  1.  

How ZPE Systems’ Nodegrid Platform Addresses Edge Computing Challenges

ZPE Systems’ Nodegrid is a Secure Service Delivery Platform that meets these needs. Nodegrid covers all three feature categories outlined in Gartner’s report, allowing organizations to host and manage edge computing via one platform. Not only is Nodegrid the industry’s most secure management infrastructure, but it also features a vendor-neutral OS, hypervisor, and multi-core Intel CPU to support necessary containers, VMs, and workloads at the edge. Nodegrid follows isolated management best practices that enable end-to-end orchestration and safe updates/rollbacks of global device fleets. Nodegrid integrates with all major cloud providers, and also features a variety of uplink types, including 5G, Starlink, and fiber, to address use cases ranging from setting up out-of-band access, to architecting Passive Optical Networking.

Here’s how Nodegrid addresses the five edge computing challenges:

1. Edge Diversity: Adapting to Industry-Specific Needs

Nodegrid is built to handle diverse requirements, with a flexible architecture that supports containerized applications and virtual machines. This architecture enables organizations to tailor the platform to their edge computing needs, whether for handling automated workflows in a factory or data-driven customer experiences in retail.

2. Ongoing Digital Transformation: Supporting Continuous Growth

Nodegrid supports ongoing digital transformation by providing zero-touch orchestration and management, allowing for remote deployment and centralized control of edge devices. This enables teams to perform initial setup of all infrastructure and services required for their edge computing use cases. Nodegrid’s remote access and automation provide a secure platform for keeping infrastructure up-to-date and optimized without the need for on-site staff. This helps organizations move much of their focus away from operations (“keeping the lights on”), and instead gives them the agility to scale their edge infrastructure to meet their business goals.

3. Data Growth: Enabling Real-Time Data Processing

Nodegrid addresses the challenge of exponential data growth by providing local processing capabilities, enabling edge devices to analyze and act on data without relying on the cloud. This not only reduces latency but also enhances decision-making in time-sensitive environments. For instance, Nodegrid can handle the high volumes of data generated by sensors and machines in a manufacturing plant, providing instant feedback for closed-loop automation and improving operational efficiency.

4. Business-Led Requirements: Tailored Solutions for Industry Demands

Nodegrid’s hardware and software are designed to be adaptable, allowing businesses to scale across different industries and use cases. In manufacturing, Nodegrid supports automated workflows and predictive maintenance, ensuring equipment operates efficiently. In retail, it powers hyperpersonalization, enabling businesses to offer tailored customer experiences through edge-driven insights. The vendor-neutral Nodegrid OS integrates with existing and new infrastructure, and the Net SR is a modular appliance that allows for hot-swapping of serial, Ethernet, computing, storage, and other capabilities. Organizations using Nodegrid can adapt to evolving use cases without having to do any heavy lifting of their infrastructure.

5. Technology Focus: Supporting Advanced AI/ML Applications

Emerging technologies such as AI/ML require robust edge platforms that can handle complex workloads with low-latency processing. Nodegrid excels in environments where real-time analytics and autonomous systems are crucial, offering high-performance infrastructure designed to support these advanced use cases. Whether processing data for AI-driven decision-making in defense or enabling real-time analytics in industrial environments, Nodegrid provides the computing power and scalability needed for AI/ML models to operate efficiently at the edge.

Read Gartner’s Market Guide for Edge Computing Platforms

As businesses continue to deploy edge computing solutions to manage increasing data, reduce latency, and drive innovation, selecting the right platform becomes critical. The 2024 Gartner Market Guide for Edge Computing Platforms provides valuable insights into the trends and challenges of edge deployments, emphasizing the need for scalability, zero-touch management, and support for evolving workloads.

Click below to download the report.

Get a Demo of Nodegrid’s Secure Service Delivery

Our engineers are ready to walk you through the software infrastructure, edge management and orchestration, and cloud integration capabilities of Nodegrid. Use the form to set up a call and get a hands-on demo of this Secure Service Delivery Platform.

Top 5 Data Center Mistakes and How To Avoid Them

Top 5 Data Center Mistakes and How To Avoid Them

Data center deployments require careful planning and execution. The sheer complexity makes it easy to stumble into common pitfalls that can compromise uptime, security, and scalability. After talking with hundreds of customers, we’ve compiled the top five data center mistakes organizations often make during deployments, with tips on how to avoid them.

1. Overlooking Isolated Management Infrastructure

In the data center, the focus is bringing production infrastructure online, including power, cabling, racks, servers, and network gear. But many project managers and architects say they wished they’d given more attention to setting up proper management infrastructure. This oversight usually leads to business challenges down the line, especially when management access relies on the production infrastructure. When a device fails or goes offline, there’s no choice but to go on-site to manually troubleshoot and recover. Many professionals admit to making this data center mistake and wish that they had considered this early in the planning process. Incorporating something called Isolated Management Infrastructure from the start can avoid this challenge, since it provides a dedicated management plane through which teams can access production gear without relying on the production network. 

Tip: Make management infrastructure a priority in your initial planning stages. This proactive approach can prevent complications later.

IMI

2. Neglecting Automation for Configuration and Scaling

Many data center implementors focus heavily on the “rack and stack” initial setup, but fail to automate processes for configuration and scaling operations. This data center mistake often leads to days’ or weeks’ worth of manual, repetitive work, while also exposing the organization to human error. A lot of people we talked to wish they’d invested just a few weeks into automating essential tasks such as switch setup, VLAN configurations, and IP address assignments, which would have saved them lots of time later on and likely helped to prevent errors. Additionally, if rearchitecting is needed, automated systems allow for quick reimplementation, minimizing the time and complexity involved. 

Tip: Dedicate time to automating routine processes. This investment will pay off in enhanced operational efficiency and reduced human error.

3. Inadequate Out-of-Band Management

When people think of out-of-band (OOB) management, a common misconception is that it is solely about Ethernet switches. However, it’s crucial not to overlook the importance of having management access to your entire device stack. Low-level access can be essential for system recovery and management. The recent CrowdStrike outage is a perfect example – when the failed devices needed to be reimaged, typical out-of-band management solutions were inadequate at providing this type of low-level access. Generation three out-of-band serial consoles, like the Nodegrid Net SR, give Ethernet, serial, and USB access, allowing teams to remote-in at the BIOS level to revive failed devices. Using this kind of comprehensive out-of-band – on a fully isolated management plane – helps teams remotely recover and confidently automate processes.

Tip: Ensure that your OOB strategy includes robust serial console access to enhance system reliability and recovery capabilities.

IMI with Nodegrid2

4. Ignoring Security Best Practices

Zero trust security is no longer just advisable, it’s essential. The typical approach is to establish direct connectivity to devices to configure, troubleshoot, upgrade, etc. But this comes with unnecessary risks, often exposing management ports to the Internet and leaving you at risk of attack. Without a fully isolated management plane and zero trust security controls, how would you recover if you were ransomware’d? This is why it’s essential to implement security controls like role-based access and multi-factor authentication, and ensure complete separation of management and production networks. 

Tip: Prioritize security by adopting a zero-trust approach and implementing rigorous access controls to safeguard your data center.

5. Cutting Corners on Out-of-Band Management

In the race for implementing AI, it’s crucial to invest in AI data center infrastructure. But organizations often cut corners on their ability to manage the underlying infrastructure that powers AI. Management access should not stop at ethernet switches; it should extend to encompass serial console access, PDUs, jump boxes, 5G connectivity, routing, WAN links, and a centralized cloud hub with secure tunnels to colocation sites. Using a comprehensive and centralized platform like Nodegrid consolidates many management devices into one while giving remote control to optimize AI’s underlying infrastructure. Aside from enhancing efficiency, this approach minimizes waste and energy consumption, which addresses environmental, social, and governance (ESG) concerns. 

Tip: Avoid the partial out-of-band management deployment. A complete system not only supports resilience and security but also contributes to sustainability goals.

 

Addressing these common data center mistakes can significantly enhance operational efficiency, security, and scalability. By prioritizing management infrastructure, automating processes, ensuring adequate out-of-band access, implementing robust security measures, and investing wisely in management systems, organizations can build resilient data centers equipped to meet the demands of today and the future.

See ZPE Cloud in action with this video demo

Senior Sales Engineer Marcel van Zwienen gives you a hands-on demo of ZPE Cloud in this video. Watch Marcel take you from signing in to gaining remote access for troubleshooting, to showing how to apply configuration changes automatically across device fleets. Watch now at the link below.

Use Our Blueprint to Avoid Data Center Mistakes

Our blueprint shows how to deploy an isolated management infrastructure, which gives you secure remote access to recover from outages and automate operations. Download now for the complete guide.

Perle Console Server Replacement Options

NCSP Back side

Perle offers two console server solutions for out-of-band (OOB) management of data center infrastructure: the IOLAN SCG and the IOLAN SCR. The SCG is available in both fixed and modular form factors, while the SCR comes in four models with different combinations of 56 managed ports, allowing companies to choose the OOB management hardware that best suits their environment. Unfortunately, IOLAN solutions suffer from hardware and software limitations that can curb scalability and limit agility. This guide discusses Perle console server replacement options that enable streamlined growth through automation capabilities and vendor freedom.

 

Key takeaways

  • Perle IOLAN SCG appliances offer out-of-band console server management for up to 48 devices in a fixed or modular form factor. Perle IOLAN SCR console servers come with four different managed port configurations for added flexibility.
  • Perle console servers offer some automation capabilities, like auto-discovery and zero-touch provisioning, as well as comprehensive firewall functionality. However, their underpowered hardware and closed management software prevent Guest OS hosting or third-party infrastructure automation and orchestration.
  • The Nodegrid platform from ZPE Systems overcomes these limitations with robust CPU, RAM, and storage, as well as vendor-neutral software. It enables data center scalability by providing high-density serial port configurations and supporting 3rd-party automation.
  • Nodegrid can also run networking, security, edge computing, AIOps, and more, consolidating the data center tech stack and improving operational efficiency.

 

Perle IOLAN console server overview

Perle IOLAN SCG console servers provide out-of-band management for up to 48 infrastructure devices. Fixed-form-factor models use copper Ethernet for networking and OOB, while the modular version has options for Wi-Fi, cellular, and dial-up. The modular series also has three expansion bays that support any combination of 16-port RS-232 or USB serial modules.

Perle IOLAN SCR console servers come in four different models with up to 56 managed serial, USB, and Ethernet ports, as well as optional cellular integration.

Click here to compare Perle console server tech specs.

Perle console servers have automatic LLDP (Link Layer Discovery Protocol) discovery and can extend zero-touch provisioning (ZTP) to end-devices. They come with an embedded firewall, OpenVPN and IPSec VPN, and AES encryption. The PerleVIEW cloud-based management software provides centralized monitoring and control of all connected data center infrastructure.

 

Why consider Perle console server alternatives

IOLAN console servers have an underpowered 500 MHz core 32-bit ARM processor, 4GB of flash storage, and 1GB RAM. This hardware may be sufficient for basic infrastructure management workflows and ZTP, but it prevents Guest OS hosting and more advanced automation. The Perle platform also doesn’t integrate with any third-party automation or orchestration solutions.

An inability to fully automate infrastructure management workflows – or to orchestrate those tasks that can be automated – ultimately limits operational efficiency and data center scalability. Consequently, IT teams can’t effectively support the needs of the growing business, adapt to strategy changes, or focus on revenue-driving innovations like artificial intelligence and machine learning (AI/ML).

What’s needed is an open platform that can manage any device, automate any workflow, and work with third-party software to provide a fully integrated infrastructure orchestration experience.

 

Perle console server replacement options from ZPE Systems

Nodegrid is a family of vendor-neutral console server solutions from ZPE Systems. It comes in four models:

  1. The Nodegrid Serial Console Plus (NSCP) is a robust platform offering up to 96 managed serial ports in a 1U rack-mounted form factor for hyperscale data centers and cloud service providers.
  2. The Nodegrid Serial Console S Series provides up to 48 auto-sensing ports to unify management of legacy, modern, and multi-vendor data center environments.
  3. The Nodegrid Net Services Router (NSR) is a modular solution that can be customized with a range of serial, networking, storage, and compute cards to adapt to any use case.
  4. The Nodegrid Serial Console Plus Core Edition (NSCP-CE) is ideal for break-fix deployments while providing more robust security capabilities than comparable solutions.

Nodegrid devices come with Intel x86-32 bit processors, robust (and upgradable) internal storage and RAM options, and a Linux-based Nodegrid OS. The NSCP, S Series, and NSR support Guest OS and Docker containers for third-party applications. That means they can directly host infrastructure automation and orchestration (like Ansible, Puppet, and Chef), security (like Palo Alto’s next-generation firewalls), and much more. Plus, it can extend this automation to legacy and mixed-vendor devices that otherwise wouldn’t support it.

All Nodegrid models can use a wide range of USB environmental monitoring sensors to help remote teams maintain optimal conditions in the data center. Nodegrid hardware protects the control plane with advanced security features like BIOS protection, UEFI Secure Boot, self-encrypted disk (SED), Trusted Platform Module (TPM) 2.0, and a multi-site VPN using IPSec, WireGuard, and OpenSSL protocols. The Nodegrid OS and the ZPE Cloud management software are also Synopsys-validated as achieving industry-leading security.

 

 

Which Nodegrid serial console is right for you?

Use Cases
Serial
Network
CPU
Guest OS
Docker Apps
Storage
RAM
Wi-Fi
Cellular
Power
Data Sheet
Nodegrid NSCP
Hyperscale data centers and cloud service providers
16 / 32 / 48 / 96
2 SFP+ & 2 ETH
Intel x86_64 quad core
1
1-2
32GB SSD
4GB DDR4
Optional
Optional
Single or Dual AC

Dual DC

Nodegrid NSC S Series
Mixed legacy, modern, and multi-vendor environments
16 / 32 / 48
2 SFP+ or 2 ETH
Intel x86_64 dual core
1
1-2
32GB SSD
4GB DDR3
Optional
Optional
Single or Dual AC

Dual DC

Nodegrid NSR
Modular and adaptable to any use case
16 / 32 / 48 / 64 / 80
2 SFP+ & 2 ETH
Intel x86_64 quad core or 8-core
1-6
1-4
32GB – 128GB
8GB DDR4
Optional
Optional
Single or Dual AC

Dual DC

Nodegrid NSCP-CE
Break-fix solution for data centers, colocations, and branches
16 / 32 / 48
2 SFP & 2 ETH
Intel x86_64 dual core
0
0
16GB SSD
4GB DDR4
Optional
Optional
Dual AC

Dual DC

Future-proof your data center with Nodegrid

Perle console servers deliver unified, out-of-band management of remote data center infrastructure with some basic automation capabilities, but their closed architecture and underpowered hardware limit extensibility and scalability. Nodegrid improves upon outdated console server solutions with a vendor-neutral platform that supports unlimited innovation and growth with less management complexity.

To learn more about Perle console server replacement options, schedule a demo of the vendor-neutral Nodegrid platform.

 

Perle IOLAN console server tech specs

Use Cases
Serial
Network
CPU
Guest OS
Docker Apps
Storage
RAM
Wi-Fi
Cellular
Power
IOLAN SCG (Fixed)
Data centers
16 / 32 / 48
1 ETH
ARM 32-bit 500MHz single core
0
0
4GB Flash
1GB
No
No
Single AC
IOLAN SCG (Modular)
Multiple
Up to 50
2 SFP or 2 ETH
ARM 32-bit 500MHz single core
0
0
4GB Flash
1GB
Optional
Optional
Dual AC

Dual AC

IOLAN SCG (Modular)
Large data centers
24 / 32 / 40 / 56
2 SFP (SCR256)

2 SFP & 2 ETH (SCR226, 242, 258)

ARM 32-bit 500MHz single core
0
0
4GB Flash
1GB
Optional
Optional
Dual AC

Ready to replace your outdated Perle console server?

 

We know that replacing outdated, EOL devices takes a lot of effort. That’s why ZPE now offers a complete package of budget-friendly products and engineering services to help streamline the process.

Click here to see how we make it easy to upgrade to next-gen out-of-band management.