A single hour of downtime costs organizations more than $300,000 in lost business, making network and service reliability critical to revenue. The biggest challenge facing IT infrastructure teams is ensuring network resilience, which is the ability to continue operating and delivering services during equipment failures, ransomware attacks, and other emergencies. This guide discusses IT infrastructure management best practices for creating and maintaining more resilient enterprise networks.
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IT infrastructure management best practices

The following IT infrastructure management best practices help improve network resilience while streamlining operations. Click the links on the left for a more detailed look at the technologies and processes involved with each.

Isolated management infrastructure (IMI)

Management interfaces provide the crucial path to monitoring and controlling critical infrastructure, like servers and switches, as well as crown-jewel digital assets like intellectual property (IP). If management interfaces are exposed to the internet or rely on the production network, attackers can easily hijack your critical infrastructure, access valuable resources, and take down the entire network. This is why CISA released a binding directive that instructs organizations to move management interfaces to a separate network, a practice known as isolated management infrastructure (IMI).

The best practice for building an IMI is to use Gen 3 out-of-band (OOB) serial consoles, which unify the management of all connected devices and ensure continuous remote access via alternative network interfaces (such as 4G/5G cellular). OOB management gives IT teams a lifeline to troubleshoot and recover remote infrastructure during equipment failures and outages on the production network. The key is to ensure that OOB serial consoles are fully isolated from production and can run the applications, tools, and services needed to fight through a ransomware attack or outage without taking critical infrastructure offline for extended periods. This essentially allows you to instantly create a virtual War Room for coordinated recovery efforts to get you back online in a matter of hours instead of days or weeks. An IMI using out-of-band serial consoles also provides a safe environment to recover from ransomware attacks. The pervasive nature of ransomware and its tendency to re-infect cleaned systems mean it can take companies between 1 and 6 months to fully recover from an attack, with costs and revenue losses mounting with every day of downtime. The best practice is to use OOB serial consoles to create an isolated recovery environment (IRE) where teams can restore and rebuild without risking reinfection.
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Network and infrastructure automation

As enterprise network architectures grow more complex to support technologies like microservices applications, edge computing, and artificial intelligence, teams find it increasingly difficult to manually monitor and manage all the moving parts. Complexity increases the risk of configuration mistakes, which cause up to 35% of cybersecurity incidents. Network and infrastructure automation handles many tedious, repetitive tasks prone to human error, improving resilience and giving admins more time to focus on revenue-generating projects.

Additionally, automated device provisioning tools like zero-touch provisioning (ZTP) and configuration management tools like RedHat Ansible make it easier for teams to recover critical infrastructure after a failure or attack. Network and infrastructure automation help organizations reduce the duration of outages and allow small IT infrastructure teams to manage large enterprise networks effectively, improving resilience and reducing costs.

Vendor-neutral platforms

Most enterprise networks bring together devices and solutions from many providers, and they often don’t interoperate easily. This box-based approach creates vendor lock-in and technical debt by preventing admins from using the tools or scripting languages they’re familiar with, and it makes a fragmented, complex architecture of management solutions that are difficult to operate efficiently. Organizations also end up compromising on features, ending up with a lot of stuff they don’t need and too little of what they do need.

A vendor-neutral IT infrastructure management platform allows teams to unify all their workflows and solutions. It integrates your administrators’ favorite tools to reduce technical debt and provides a centralized place to deploy, orchestrate, and monitor the entire network. It also extends technologies like OOB, automation, and AIOps to otherwise unsupported legacy and mixed-vendor solutions. Such a platform is revolutionary in the same way smartphones were – instead of needing a separate calculator, watch, pager, phone, etc., everything was combined in a single device. A vendor-neutral management platform allows you to run all the apps, services, and tools you need without buying a bunch of extra hardware. It’s a crucial IT infrastructure management best practice for resilience because it consolidates and unifies network architectures to reduce complexity and prevent human error.

AIOps

AIOps applies artificial intelligence technologies to IT operations to maximize resilience and efficiency. Some AIOps use cases include:

• Security detection: AIOps security monitoring solutions are better at catching novel attacks (those using methods never encountered or documented before) than traditional, signature-based detection methods that rely on a database of known attack vectors.
• Data analysis: AIOps can analyze all the gigabytes of logs generated by network infrastructure and provide health visualizations and recommendations for preventing potential issues or optimizing performance.
• Root-cause analysis (RCA): Ingesting infrastructure logs allows AIOps to identify problems on the network, perform root-cause analysis to determine the source of the issues, and create & prioritize service incidents to accelerate remediation.

AIOps is often thought of as “intelligent automation” because, while most automation follows a predetermined script or playbook of actions, AIOps can make decisions on-the-fly in response to analyzed data. AIOps and automation work together to reduce management complexity and improve network resilience.

IT infrastructure management best practices for maximum resilience

Network resilience is one of the top IT infrastructure management challenges facing modern enterprises. These IT infrastructure management best practices ensure resilience by isolating management infrastructure from attackers, reducing the risk of human error during configurations and other tedious workflows, breaking vendor lock-in to decrease network complexity, and applying artificial intelligence to the defense and maintenance of critical infrastructure.

Need help getting started with these practices and technologies? ZPE Systems can help simplify IT infrastructure management with the vendor-neutral Nodegrid platform. Nodegrid’s OOB serial consoles and integrated branch routers allow you to build an isolated management infrastructure that supports your choice of third-party solutions for automation, AIOps, and more.

Want to learn how to make IT infrastructure management easier with Nodegrid?

To learn more about implementing IT infrastructure management best practices for resilience with Nodegrid, download our Network Automation Blueprint. 

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The DevOps methodology combines the software development and IT operations teams into a highly collaborative unit. In a DevOps environment, team members work simultaneously on the same code base, using automation and source control to accelerate releases. The transformation from a traditional, siloed organizational structure to a streamlined, fast-paced DevOps company is rewarding yet challenging. That’s why it’s important to have the right strategy, and in this guide to collaboration in DevOps, you’ll discover tips and best practices for a smooth transition.

Collaboration in DevOps: Strategies and best practices

A successful DevOps implementation results in a tightly interwoven team of software and infrastructure specialists working together to release high-quality applications as quickly as possible. This transition tends to be easier for developers, who are already used to working with software code, source control tools, and automation. Infrastructure teams, on the other hand, sometimes struggle to work at the velocity needed to support DevOps software projects and lack experience with automation technologies, causing a lot of frustration and delaying DevOps initiatives. The following strategies and best practices will help bring Dev and Ops together while minimizing friction.

Turn infrastructure and network configurations into software code

Infrastructure and network teams can’t keep up with the velocity of DevOps software development if they’re manually configuring, deploying, and troubleshooting resources using the GUI (graphical user interface) or CLI (command line interface). The best practice in a DevOps environment is to use software abstraction to turn all configurations and networking logic into code.

Software abstraction helps accelerate resource provisioning, reducing delays and friction between Dev and Ops. It can also be used to bring networking teams into the DevOps fold with automated, software-defined networks, creating what’s known as a NetDevOps environment.

Use common, centralized tools for software source control

Collaboration in DevOps means a whole team of developers or sysadmins may work on the same code base simultaneously. This is highly efficient — but risky. Development teams have used software source control tools like GitHub for years to track and manage code changes and prevent overwriting each other’s work. In a DevOps organization using IaC and SDN, the best practice is to incorporate infrastructure and network code into the same source control system used for software code.

Managing infrastructure configurations using a tool like GitHub ensures that sysadmins can’t make unauthorized changes to critical resources. For example, administrators initiate many ransomware attacks and other major outages by directly changing infrastructure configurations without testing or approval. This happened in a high-profile MGM cyberattack when an IT staff member fell victim to social engineering and granted elevated Okta privileges to an attacker without having to get approval from a second pair of eyes.

Using DevOps source control, all infrastructure changes must be reviewed and approved by a second party in the IT department to ensure they don’t introduce vulnerabilities or malicious code into production. Sysadmins can work quickly and creatively, knowing there’s a safety net to catch mistakes, reducing Ops delays, and fostering a more collaborative environment.

Consolidate and integrate DevOps tools with a vendor-neutral platform

An enterprise DevOps deployment usually involves dozens – if not hundreds – of different tools to automate and streamline the many workflows involved in a software development project. Having so many individual DevOps tools deployed around the enterprise increases the management complexity, which can have the following consequences.

• Human error – The harder it is to stay on top of patch releases, security bulletins, and monitoring logs, the more likely it is that an issue will slip between the cracks until it causes an outage or breach.
• Security complexity – Every additional DevOps tool added to the architecture makes integrating and implementing a consistent security model more complex and challenging, increasing the risk of coverage gaps.
• Spiraling costs – With many different solutions handling individual workflows around the enterprise, the likelihood of buying redundant services or paying for unneeded features increases, which can impact ROI.
• Reduced efficiency – DevOps aims to increase operational efficiency, but having to work across so many disparate tools can slow teams down, especially when those tools don’t interoperate.

The best practice is consolidating your DevOps tools with a centralized, vendor-neutral platform. For example, the Nodegrid Services Delivery Platform from ZPE Systems can host and integrate 3rd-party DevOps tools, unifying them under a single management umbrella. Nodegrid gives IT teams single-pane-of-glass control over the entire DevOps architecture, including the underlying network infrastructure, which reduces management complexity, increases efficiency, and improves ROI.

Maximize DevOps success

DevOps collaboration can improve operational efficiency and allow companies to release software at the velocity required to stay competitive in the market. Using software abstraction, centralized source code control, and vendor-neutral management platforms reduces friction on your DevOps journey. The best practice is to unify your DevOps environment with a vendor-neutral platform like Nodegrid to maximize control, cost-effectiveness, and productivity.

Want to Simplify collaboration in DevOps with the Nodegrid platform?

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Terminal servers are network management devices providing remote access to and control over remote infrastructure. They typically connect to infrastructure devices via serial ports (hence their alternate names, serial consoles, console servers, serial console routers, or serial switches). IT teams use terminal servers to consolidate remote device management and create an out-of-band (OOB) control plane for remote network infrastructure. Terminal servers offer several benefits over other remote management solutions, such as better performance, resilience, and security. This guide answers all your questions about terminal servers, discussing their uses and benefits before describing what to look for in the best terminal server solution.

What is a terminal server?

A terminal server is a networking device used to manage other equipment. It directly connects to servers, switches, routers, and other equipment using management ports, which are typically (but not always) serial ports. Network administrators remotely access the terminal server and use it to manage all connected devices in the data center rack or branch where it’s installed.

What are the uses for terminal servers?

Network teams use terminal servers for two primary functions: remote infrastructure management consolidation and out-of-band management.

1. Terminal servers unify management for all connected devices, so administrators don’t need to log in to each separate solution individually. Terminal servers save significant time and effort, which reduces the risk of fatigue and human error that could take down the network.
2. Terminal servers provide remote out-of-band (OOB) management, creating a separate, isolated network dedicated to infrastructure management and troubleshooting. OOB allows administrators to troubleshoot and recover remote infrastructure during equipment failures, network outages, and ransomware attacks.

Learn more about using OOB terminal servers to recover from ransomware attacks by reading How to Build an Isolated Recovery Environment (IRE).

What are the benefits of terminal servers?

There are other ways to gain remote OOB management access to remote infrastructure, such as using Intel NUC jump boxes. Despite this, terminal servers are the better option for OOB management because they offer benefits including:

The benefits of terminal servers

Examples of terminal servers

Examples of popular terminal server solutions include the Opengear CM8100, the Avocent ACS8000, and the Nodegrid Serial Console Plus. The Opengear and Avocent solutions are second-generation, or Gen 2, terminal servers, which means they provide some automation support but suffer from vendor lock-in. The Nodegrid solution is the only Gen 3 terminal server, offering unlimited integration support for 3rd-party automation, security, SD-WAN, and more.

What to look for in the best terminal server

Terminal servers have evolved, so there is a wide range of options with varying capabilities and features. Some key characteristics of the best terminal server include:

• 5G/4G LTE and Wi-Fi options for out-of-band access and network failover
• Support for legacy devices without costly adapters or complicated configuration tweaks
• Advanced authentication support, including two-factor authentication (2FA) and SAML 2.0
• Robust onboard hardware security features like a self-encrypted SSD and UEFI Secure Boot
• An open, Linux-based OS that supports Guest OS and Docker containers for third-party software
• Support for zero-touch provisioning (ZTP), custom scripts, and third-party automation tools
• A vendor-neutral, centralized management and orchestration platform for all connected solutions

These characteristics give organizations greater resilience, enabling them to continue operating and providing services in a degraded fashion while recovering from outages and ransomware. In addition, vendor-neutral support for legacy devices and third-party automation enables companies to scale their operations efficiently without costly upgrades.

Why choose Nodegrid terminal servers?

Only one terminal server provides all the features listed above on a completely vendor-neutral platform – the Nodegrid solution from ZPE Systems.

The Nodegrid S Series terminal server uses auto-sensing ports to discover legacy and mixed-vendor infrastructure solutions and bring them under one unified management umbrella.

The Nodegrid Serial Console Plus (NSCP) is the first terminal server to offer 96 management ports on a 1U rack-mounted device (Patent No. 9,905,980).

ZPE also offers integrated branch/edge services routers with terminal server functionality, so you can consolidate your infrastructure while extending your capabilities.

All Nodegrid devices offer a variety of OOB and failover options to ensure maximum speed and reliability. They’re protected by comprehensive onboard security features like TPM 2.0, self-encrypted disk (SED), BIOS protection, Signed OS, and geofencing to keep malicious actors off the management network. They also run the open, Linux-based Nodegrid OS, supporting Guest OS and Docker containers so you can host third-party applications for automation, security, AIOps, and more. Nodegrid extends automation, security, and control to all the legacy and mixed-vendor devices on your network and unifies them with a centralized, vendor-neutral management platform for ultimate scalability, resilience, and efficiency.

Want to learn more about Nodegrid terminal servers?

ZPE Systems offers terminal server solutions for data center, branch, and edge deployments. Schedule a free demo to see Nodegrid terminal servers in action.

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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.

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.

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

• Automation – Tools like zero-touch provisioning (ZTP) that facilitate speedy recovery while minimizing human error

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.

• Read about the high-profile ransomware attacks affecting MOVEit customers and MGM

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.

 

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.

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DevOps is all about streamlining software development and delivery through automation and collaboration. Many workflows are involved in a DevOps software development lifecycle, but they can be broadly broken down into the following categories: development, resource provisioning and management, integration, testing, deployment, and monitoring. The best DevOps tools streamline and automate these key aspects of the DevOps lifecycle. This blog discusses what role these tools play and highlights the most popular offerings in each category.

The best DevOps tools

DevOps version control

In a DevOps environment, a whole team of developers may work on the same code base simultaneously for maximum efficiency. DevOps version control tools like GitHub allow you to track and manage all the changes made to a code base, providing visibility into who’s making what changes at what time. Version control prevents devs from overwriting each other’s work or making unauthorized changes. For example, a developer may come up with a way to improve the performance of a feature by changing the existing code, but doing so inadvertently creates a vulnerability in the software or interferes with other application functions. DevOps version control prevents unauthorized code changes from integrating with the rest of source code and tracks who’s responsible for making the request, improving the stability and security of the software.

•  Best DevOps version control tool: Github

Infrastructure as Code (IaC)

Infrastructure as Code (IaC) streamlines the Operations side of a DevOps environment by abstracting server, VM, and container configurations as software code. IaC build tools like HashiCorp Terraform allow Ops teams to write infrastructure configurations as declarative or imperative code, which is used to provision resources automatically. With IaC, teams can deploy infrastructure at the velocity required by DevOps development cycles.

An example Terraform configuration for IaC.

•  Best Infrastructure as Code (IaC) tool: HashiCorp Terraform

Configuration management

Configuration management involves monitoring infrastructure and network devices to make sure no unauthorized changes are made while systems are in production. Unmonitored changes could introduce security vulnerabilities that the organization is unaware of, especially in a fast-paced DevOps environment. In addition, as systems are patched and updated over time, configuration drift becomes a concern, leading to additional quality and security issues. DevOps configuration management tools like RedHat Ansible automatically monitor configurations and roll back unauthorized modifications. Some IaC build tools, like Terraform, also include configuration management.

•  Best configuration management tool: RedHat Ansible

Continuous Integration/Continuous Delivery (CI/CD)

Continuous Integration/Continuous Delivery (CI/CD) is a software development methodology that goes hand-in-hand with DevOps. In CI/CD, software code is continuously updated and integrated with the main code base, allowing a continuous delivery of new features and improvements. CI/CD tools like Jenkins automate every step of the CI/CD process, including software building, testing, integrating, and deployment. This allows DevOps organizations to continuously innovate and optimize their products to stay competitive in the market.

•  Best CI/CD tool: Jenkins

Software testing

Not all DevOps teams utilize CI/CD, and even those that do may have additional software testing needs that aren’t addressed by their CI/CD platform. In DevOps, app development is broken up into short sprints so manageable chunks of code can be tested and integrated as quickly as possible. Manual testing is slow and tedious, introducing delays that prevent teams from achieving the rapid delivery schedules required by DevOps organizations. DevOps software testing tools like Selenium automatically validate software to streamline the process and allow testing to occur early and often in the development cycle. That means high-quality apps and features get out to customers sooner, improving the ROI of software projects.

•  Best software testing tool: Selenium

Container management

In DevOps, containers are lightweight, virtualized resources used in the development of microservice applications. Microservice applications are extremely agile, breaking up software into individual services that can be developed, deployed, managed, and destroyed without affecting other parts of the app. Docker is the de facto standard for basic container creation and management. Kubernetes takes things a step further by automating the orchestration of large-scale container deployments to enable an extremely efficient and streamlined infrastructure.

•  Best container management tools: Docker and Kubernetes

Monitoring & incident management

Continuous improvement is a core tenet of the DevOps methodology. Software and infrastructure must be monitored so potential issues can be resolved before they affect software performance or availability. Additionally, monitoring data should be analyzed for opportunities to improve the quality, speed, and usability of applications and systems. DevOps monitoring and incident response tools like Cisco’s AppDynamics provide full-stack visibility, automatic alerts, automated incident response and remediation, and in-depth analysis so DevOps teams can make data-driven decisions to improve their products.

•  Best monitoring & incident management tool: Cisco AppDynamics

Deploy the best DevOps tools with Nodegrid

DevOps is all about agility, speed, and efficiency. The best DevOps tools use automation to streamline key workflows so teams can deliver high-quality software faster. With so many individual tools to manage, there’s a real risk of DevOps tech sprawl driving costs up and inhibiting efficiency. One of the best ways to reduce tech sprawl (without giving up all the tools you love) is by using vendor-neutral platforms to consolidate your solutions. For example, the Nodegrid Services Delivery Platform from ZPE Systems can host and integrate 3rd-party DevOps tools, reducing the need to deploy additional virtual or hardware resources for each solution. Nodegrid utilizes integrated services routers, such as the Gate SR or Net SR, to provide branch/edge gateway routing, in-band networking, out-of-band (OOB) management, cellular failover, and more. With a Nodegrid SR, you can combine all your network functions and DevOps tools into a single integrated solution, consolidating your tech stack and streamlining operations.

A major benefit of using Nodegrid is that the Linux-based Nodegrid OS is Synopsys secure, meaning every line of source code is checked during our SDLC. This significantly reduces CVEs and other vulnerabilities that are likely present in other vendors’ software.

Learn more about efficient DevOps management with vendor-neutral solutions

With the vendor-neutral Nodegrid Services Delivery Platform, you can deploy the best DevOps tools while reducing tech sprawl. Watch a free Nodegrid demo to learn more.

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Organizations prioritizing digital transformation by adopting IoT (Internet of Things) technologies generate and process an unprecedented amount of data. Traditionally, the systems used to process that data live in a centralized data center or the cloud. However, IoT devices are often deployed around the edges of the enterprise in remote sites like retail stores, manufacturing plants, and oil rigs. Transferring so much data back and forth creates a lot of latency and uses valuable bandwidth. Edge computing solves this problem by moving processing units closer to the sources that generate the data.

IBM estimates there are over 15 billion edge devices already in use. While edge computing has rapidly become a vital component of digital transformation, many organizations focus on individual use cases and lack a cohesive edge computing strategy. According to a recent Gartner report, the result is what’s known as “edge sprawl”: many individual edge computing solutions deployed all over the enterprise without any centralized control or visibility. Organizations with disjointed edge computing deployments are less efficient and more likely to hit roadblocks that stifle digital transformation.

The report provides guidance on building an edge computing strategy to combat sprawl, and the foundation of that strategy is edge management and orchestration (EMO). Below, this post summarizes the key findings from the Gartner report and discusses some of the biggest edge computing challenges before explaining how to solve them with a centralized EMO platform.

Key findings from the Gartner report

Many organizations already use edge computing technology for specific projects and use cases – they have an individual problem to solve, so they deploy an individual solution. Since the stakeholders in these projects usually aren’t architects, they aren’t building their own edge computing machines or writing software for them. Typically, these customers buy pre-assembled solutions or as-a-service offerings that meet their specific needs.

However, a piecemeal approach to edge computing projects leaves organizations with disjointed technologies and processes, contributing to edge sprawl and shadow IT. Teams can’t efficiently manage or secure all the edge computing projects occurring in the enterprise without centralized control and visibility. Gartner urges I&O (infrastructure & operations) leaders to take a more proactive approach by developing a comprehensive edge computing strategy encompassing all use cases and addressing the most common challenges.

Edge computing challenges

Gartner identifies six major edge computing challenges to focus on when developing an edge computing strategy:

Let’s discuss these challenges and their solutions in greater depth.

• Enabling extensibility – Many organizations deploy purpose-built edge computing solutions for their specific use case and can’t adapt when workloads change or grow.  The goal is to attempt to predict future workloads based on planned initiatives and create an edge computing strategy that leaves room for that growth. However, no one can really predict the future, so the strategy should account for unknowns by utilizing common, vendor-neutral technologies that allow for expansion and integration.

• Extracting value from edge data – The generation of so much IoT and sensor data gives organizations the opportunity to extract additional value in the form of business insights, predictive analysis, and machine learning training. Quickly extracting that value is challenging when most data analysis and AI applications still live in the cloud. To effectively harness edge data, organizations should look for ways to deploy artificial intelligence training and data analytics solutions alongside edge computing units.

• Governing edge data – Edge computing deployments often have more significant data storage constraints than central data centers, so quickly distinguishing between valuable data and destroyable junk is critical to edge ROIs. With so much data being generated, it’s often challenging to make this determination on the fly, so it’s important to address data governance during the planning process. There are automated data governance solutions that can help, but these must be carefully configured and managed to avoid data loss.

• Supporting edge-native applications – Edge applications aren’t just data center apps lifted and shifted to the edge; they’re designed for edge computing from the bottom up. Like cloud-native software, edge apps often use containers, but clustering and cluster management are different beasts outside the cloud data center. The goal is to deploy platforms that support edge-native applications without increasing the technical debt, which means they should use familiar container management technologies (like Docker) and interoperate with existing systems (like OT applications and VMs).

• Securing the edge – Edge deployments are highly distributed in locations that may lack many physical security features in a traditional data center, such as guarded entries and biometric locks, which adds risk and increases the attack surface. Organizations must protect edge computing nodes with a multi-layered defense that includes hardware security (such as TPM), frequent patches, zero-trust policies, strong authentication (e.g., RADIUS and 2FA), and network micro-segmentation.

• Edge management and orchestration – Moving computing out of the climate-controlled data center creates environmental and power challenges that are difficult to mitigate without an on-site technical staff to monitor and respond. When equipment failure, configuration errors, or breaches take down the network, remote teams struggle to meet resilience requirements to keep business operations running 24/7. The sheer number and distribution area of edge computing units make them challenging to manage efficiently, increasing the likelihood of mistakes, issues, or threat indicators slipping between the cracks. Addressing this challenge requires centralized edge management and orchestration (EMO) with environmental monitoring and out-of-band (OOB) connectivity.

  A centralized EMO platform gives administrators a single-pane-of-glass view of all edge deployments and the supporting infrastructure, streamlining management workflows and serving as the control panel for automation, security, data governance, cluster management, and more. The EMO must integrate with the technologies used to automate edge management workflows, such as zero-touch provisioning (ZTP) and configuration management (e.g., Ansible or Chef), to help improve efficiency while reducing the risk of human error. Integrating environmental sensors will help remote technicians monitor heat, humidity, airflow, and other conditions affecting critical edge equipment’s performance and lifespan. Finally, remote teams need OOB access to edge infrastructure and computing nodes, so the EMO should use out-of-band serial console technology that provides a dedicated network path that doesn’t rely on production resources.

Gartner recommends focusing your edge computing strategy on overcoming the most significant risks, challenges, and roadblocks. An edge management and orchestration (EMO) platform is the backbone of a comprehensive edge computing strategy because it serves as the hub for all the processes, workflows, and solutions used to solve those problems.

Edge management and orchestration (EMO) with Nodegrid

Nodegrid is a vendor-neutral edge management and orchestration (EMO) platform from ZPE Systems. Nodegrid uses Gen 3 out-of-band technology that provides 24/7 remote management access to edge deployments while freely interoperating with third-party applications for automation, security, container management, and more. Nodegrid environmental sensors give teams a complete view of temperature, humidity, airflow, and other factors from anywhere in the world and provide robust logging to support data-driven analytics.

The open, Linux-based Nodegrid OS supports direct hosting of containers and edge-native applications, reducing the hardware overhead at each edge deployment. You can also run your ML training, AIOps, data governance, or data analytics applications from the same box to extract more value from your edge data without contributing to sprawl.

In addition to hardware security features like TPM and geofencing, Nodegrid supports strong authentication like 2FA, integrates with leading zero-trust providers like Okta and PING, and can run third-party next-generation firewall (NGFW) software to streamline deployments further.

The Nodegrid platform brings all the components of your edge computing strategy under one management umbrella and rolls it up with additional core networking and infrastructure management features. Nodegrid consolidates edge deployments and streamlines edge management and orchestration, providing a foundation for a Gartner-approved edge computing strategy.

Want to learn more about how Nodegrid can help you overcome your biggest edge computing challenges?

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Various reasons may prompt a move to a new data center, like finding a different provider with lower prices, or the added security of relocating assets from an on-premises location to a colocation facility or private cloud.

Despite the potential benefits, data center migrations are often tough on enterprises, both internally and from the client side of things. Data center managers, systems administrators, and network engineers must cope with the logistical difficulties of planning, executing, and supporting the move. End-users may experience service disruptions and performance issues that make their jobs harder. Migrations also tend to reveal any weaknesses in the actual infrastructure that’s moved, which means systems that once worked perfectly may require extra support during and after the migration.

The best way to limit headaches and business disruptions is to plan every step of a data center migration meticulously. This guide provides a basic data center migration checklist to help with planning and includes additional resources for streamlining your move.

Data center migration checklist

Data center migrations are always complex and unique to each organization, but there are typically two major approaches:

• Lift-and-shift. You physically move infrastructure from one data center to another. In some ways, this is the easiest approach because all components are known, but it can limit your potential benefits if gear remains in racks for easy transport to the new location rather than using the move as an opportunity to improve or upgrade certain parts.

• New build. You replace some or all of your infrastructure with different solutions in a new data center. This approach is more complex because services and dependencies must be migrated to new environments, but it also permits organizations to simultaneously improve operational processes, cut costs, and update existing tech stacks.

The following data center migration checklist will help guide your planning for either approach and ensure you’re asking the right questions to prepare for any potential problems.

1.  Site surveys

The first step is to determine your physical requirements – how much space, power, cooling, cable management, etc., you’ll need in the new data center. Then, conduct site surveys of the new environment to identify existing limitations and available resources. For example, you’ll want to make sure the HVAC system can provide adequate climate control – specific to the new locale – for your incoming hardware. You may need to verify that your power supply can support additional chillers or dehumidifiers, if necessary, to maintain optimal temperature ranges. In addition to physical infrastructure requirements, factors like security and physical accessibility are important considerations for your new location.

2. Infrastructure documentation

At a bare minimum, you need an accurate list of all the physical and virtual infrastructure you’re moving to the new data center. You should also collect any existing documentation on your application and system requirements for storage, compute, networking, and security to ensure you cover all these bases in the migration. If that documentation doesn’t exist, now’s the time to create it. Having as much documentation as possible will streamline many of the following steps in your data center move.

3. Dependencies and ancillary services

Aside from the infrastructure you’re moving, hundreds or thousands of other services will likely be affected by the change. It’s important to map out these dependencies and ancillary services to learn how the migration will affect them and what you can do to smooth the transition. For example, if an application or service relies on a legacy database, you may need to upgrade both the database and its hardware to ensure end-users have uninterrupted access. As an added benefit, creating this map also aids in implementing micro-segmentation for Zero Trust security.

4. Layout and topology

The next step is to plan the physical layout of the new data center infrastructure. Where will network, storage, and power devices sit in the rack and cabinets? How will you handle cable management? Will your planned layout provide enough airflow for cooling? This is also the time to plan the network topology – how traffic will flow to, from, and within the new data center infrastructure.

5. Management access

You must determine how your administrators will deploy and manage the new data center infrastructure. Will you enable remote access? If so, how will you ensure continuous availability during migration or when issues arise? Do you plan to automate your deployment with zero touch provisioning?

• Learn more about enabling 24/7 remote access and end-to-end automation with a Gen 3 out-of-band (OOB) serial console.
• Read the details about how Vapor IO deployed edge data centers in one hour while also providing 24/7 remote access.

6. Network planning

If you didn’t cover this in your infrastructure documentation, you’ll need specific documentation for your data center networking requirements – both WAN (wide area networking) and LAN (local area networking). This is a good time to determine whether you want to exactly replicate your existing network environment or make any network infrastructure upgrades. Then, create a detailed implementation plan covering everything from VLANs to IP address provisioning, DNS migrations, and ordering MPLS circuits.

7. Migration & build planning

Next, plan out each step of the move or build itself – the actions your team will perform immediately before, during, and after the migration. It’s important to include disaster recovery options in case critical services break, or unforeseen changes cause delays. Implementing checkpoints at key stages of the move will help ensure any issues are fixed before they impact subsequent migration steps.

8. Assembling a team

At this stage, you likely have a team responsible for planning the data center migration, but you also need to identify who’s responsible for every aspect of the move itself. It’s critical to do this as early as possible so you have time to set expectations, communicate the plan, and handle any required pre-migration training or support. Additionally, ensure this team includes dedicated support staff who can triage end-user requests if any issues arise during or after the migration.

9. Vendor support

Any experienced sysadmin will tell you that anything that could go wrong with a data center migration probably will, so you should plan for the worst but hope for the best. That means collecting a list of vendor contacts for each hardware and software component you’re migrating so it will be easier to contact support if something goes awry. For especially critical systems, you may even want to alert your vendor POCs prior to the move so they can be on hand (or near their phones) on the day of the move.

10. Lab simulation

This step may not be feasible for every organization, but ideally, you’ll use a lab environment to simulate key stages of the data center migration before you actually move. Running a virtualized simulation can help you identify potential hiccups with connection settings or compatibility issues. It can also highlight gaps in your planning – like forgetting to restore user access and security rules after building new firewalls – so you can address them before they affect production services.

11. Post-migration testing

Finally, you need to create a post-migration testing plan that’s ready to implement as soon as the move is complete. Testing will validate the integrity, performance, and reliability of infrastructure in the new environment, allowing teams to proactively resolve issues instead of waiting for monitoring notifications or end-user complaints.

Streamlining your data center migration

Using this data center migration checklist to create a comprehensive plan will help reduce setbacks on the day of the move. To further streamline the migration process and set yourself up for success in your new environment, consider upgrading to a vendor-neutral data center orchestration platform. Such a platform will provide a unified tool for administrators and engineers to monitor, deploy, and manage modern, multi-vendor, and legacy data center infrastructure. Reducing the number of individual solutions you need to access and manage during migration will decrease complexity and speed up the move, so you can start reaping the benefits of your new environment sooner.

Want to learn more about Data Center migration?

For a complete data center migration checklist, including in-depth guidance and best practices for moving day, click here to download our Complete Guide to Data Center Migrations or contact ZPE Systems today to learn more.
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Today’s IT teams must maintain a growing infrastructure of on-prem and cloud solutions. These range from physical routers, out-of-band devices, and firewalls, to Zero Trust Security solutions, micro-segmentation tools, and network automation integrations. Despite an abundance of physical and virtual solutions meant to help keep digital services online, many organizations face an overwhelming number of tasks just to sustain everyday operations. 

With the rising risk of recession, organizations will be forced to cut back on resources including staff, training, and tools. This will only worsen the existing challenges teams face in their efforts to maintain their distributed infrastructure. 

In this blog, we’ll explore three gaps that will leave IT teams scrambling and show you several practical approaches to cope during recession. 

Gap 1: Lack of staff

IT teams have been historically understaffed, and most people can remember at least one significant tech worker hiring campaign from the past decade. Today’s CIOs may in fact be facing the biggest talent gap since 2008. For example, in the cybersecurity sector alone, the 2021 (ISC)2 Cybersecurity Workforce Study reported that despite adding 700,000 cybersecurity professionals to the workforce in 2021, there’s still a gap of more than 2.7 million workers globally, 377,000 of which are needed in the United States. 

Trained staff are a must for managing an organization’s distributed sites, especially as team silos disappear and workers are required to have a breadth of skills. Business leaders increasingly need people who are proficient in networking and programming, so they can maintain normal operations while progressing their digital transformation initiatives such as hyperautomation. It’s a challenge that often comes down to hiring new talent or increasing the skills of existing employees, and both of these approaches require plenty of time and money. 

This issue will only worsen with the coming recession as companies begin to tighten their belts and slash budgets. Major brands have already shed thousands of workers this year, leaving IT teams to make due with existing staff numbers or even reduced headcounts. In the simplest terms, the coming recession will leave companies much less willing or able to invest in staff. 

Gap 2: Lack of tools to reduce workloads

Today’s infrastructure incorporates solutions from many different vendors, but the problem is these often come with their own unique tools that are meant to serve only a specific function. Managing SD-WAN, SASE, ZTNA, orchestration, and out-of-band solutions means jumping between disparate tools, many of which lack integration with one another. This complexity leaves operational teams stuck in a reactionary break/fix posture trying to climb mountains of never-ending support tickets. 

To address this challenge, many Big Tech companies empower their IT teams through digital transformation initiatives, such as using automation to achieve a proactive approach. But this requires additional investments in upskilling staff and acquiring adequate automation infrastructure/tools. For many organizations, a lack of money and resources makes this difficult during normal economic conditions, and will only become exacerbated with the coming recession. IT teams will continue scrambling with their inflated workloads.

Gap 3: Lack of trust in automation

Automation can greatly reduce the risk of human error (and subsequent outages) by handling simple workloads, such as device provisioning and firmware updates. However, companies that do have the resources to implement automation also recognize its limitations. Automation solutions that aren’t optimized leave IT teams with mundane tasks like managing, scheduling, and restarting bots. But to even reach this level of automation requires training staff who typically don’t have a background in programming or development. 

These teams will be unfamiliar with NetOps/DevOps concepts. In order to develop essential automation practices, these employees will need to learn through trial and error. This is a problem because most organizations lack the proper automation infrastructure and tools that allow their IT teams to recover from mistakes. Operational teams in charge of keeping infrastructure running often fear automation for this exact reason — if they make one error, there’s the potential that it will bring down the network, lead to unhappy customers, and cost them their job. 

 

Digital transformation is a broad term for the act of changing and improving your business processes through the implementation of new technologies. The cloud plays a major role in digital transformation because it provides a flexible, scalable, and accessible environment that’s ideal for a wide range of business applications. However, there are still many processes that are better suited for a traditional, on-prem data center or colocation infrastructure due to cost, security, or performance concerns.

Combining public cloud platforms with private infrastructure is known as hybrid cloud infrastructure, and it allows organizations to map their business processes and applications to the environments best suited to run them. In this post, we’ll discuss the role of hybrid cloud in digital transformation and provide tips for managing and orchestrating a hybrid infrastructure.

The importance of hybrid cloud in digital transformation

While the public cloud offers many advantages, there are a variety of reasons why an organization would want or need to keep some services private.

For example, a company doing business in an industry that’s subject to strict data privacy regulations—like finance, defense, or healthcare—may want to keep sensitive data in an on-premises data center so they can maintain complete control over the security and access control measures. At the same time, they might have other processes and applications that aren’t as high-risk and could benefit from the flexibility of cloud infrastructure.

Sometimes, an organization will migrate a workload to the cloud, only to bring it back in-house later. For instance, cloud services can reduce costs for certain applications but can increase costs for others. Most public cloud providers charge extra for data egress—transferring data of their systems and to another cloud or on-premises. That means applications that require a lot of data egress can be much more expensive to run in the cloud. That cost increase may be worthwhile in the long run to achieve optimal scalability and flexibility, but with a recession looming, many organizations are sacrificing those big picture goals to cut costs for short-term survival.

One of the biggest use cases for hybrid cloud in digital transformation is a gradual cloud migration. Digital transformation is a journey, and along the way, many organizations end up in a hybrid state because they’ve successfully moved some of their processes to the cloud but have others that still live in the data center. For example, a business may send some of their data analysis workflows to a business intelligence application in the cloud but then have an on-premises DCIM tool analyzing the same data in the data center. They eventually transition from hybrid cloud to a pure cloud or multi-cloud environment once they’ve finished migrating all their workloads to the cloud.

Hybrid cloud is one of the most popular enterprise infrastructure models because it’s flexible and affordable, allowing organizations to make the digital transformation journey at their own pace and in their own way.

Tips for managing hybrid cloud infrastructure

The most effective hybrid cloud deployment provides a single, seamless digital environment for business applications and resources, with centralized workload and infrastructure orchestration that works across all platforms and data centers. Let’s discuss how to achieve this ideal hybrid cloud deployment.

Vendor-agnostic platforms

To create a seamless environment in which workflows move effortlessly between the cloud and the data center to deliver a simple and unified experience to end-users, you need all your public cloud, private cloud, and data center solutions to work together. The best way to ensure this is by only using vendor-agnostic (vendor-neutral) hardware and software from the very beginning, but for most organizations that ship has already sailed. The next best option is to use a vendor-agnostic management platform that’s able to hook into all those closed solutions and control them equally. These solutions allow you to orchestrate workloads across public cloud, private cloud, and legacy environments without needing to replace all the systems and software already in place.

SD-WAN

A hybrid cloud deployment can create some networking challenges because of the need to orchestrate WAN (wide area networking) connections across multiple clouds and data centers, each of which may have a different networking infrastructure in place. Software-defined wide area networking, or SD-WAN, helps to reduce the complexity of hybrid cloud networking by separating the control and management processes from the underlying WAN hardware.

SD-WAN virtualizes network management functions as software or script-based configurations, which enables centralized and automated deployment. With the aid of a vendor-agnostic management platform, SD-WAN benefits hybrid cloud infrastructure by consolidating control behind a single pane of glass. This gives administrators the ability to easily orchestrate, optimize, and secure the entire distributed network.

Automation

Automation plays a key role in digital transformation because it can speed up workflows while reducing the risk of human error. For example, using automation to deploy new infrastructure means administrators can provision many resources in a short amount of time while ensuring consistent configurations.

Automation also improves security, both by reducing the rate of misconfigurations and by ensuring all infrastructure is patched as soon as possible. Unpatched infrastructure leaves you vulnerable to hacks and ransomware, but keeping track of updates for so many vendor solutions in so many different places can be challenging. Automation can help by ensuring patches are pushed out to hybrid cloud infrastructure solutions as soon as they become available. 

Vendor agnostic platforms, SD-WAN, and automation are key tools that help organizations more effectively utilize a hybrid cloud in their digital transformation journey.

The role of ZPE Systems in digital transformation

ZPE Systems offers a range of vendor-agnostic network management solutions to help your organization achieve digital transformation. The Nodegrid platform can dig its hooks into your legacy and mixed-vendor infrastructure to provide a common interface from which to manage and orchestrate your entire network architecture. Plus, Nodegrid can host or integrate with your choice of SD-WAN solutions to help you consolidate your tech stack while delivering optimized performance and security.

Contact ZPE Systems today

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