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How SDN Transforms Data Centers for Peak Performance?

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SDN in the Data Center

In the data center, Software-Defined Networking (SDN) revolutionizes the traditional network architecture by centralizing control and introducing programmability. SDN enables dynamic and agile network configurations, allowing administrators to adapt quickly to changing workloads and application demands. This centralized control facilitates efficient resource utilization, automating the provisioning and management of network resources based on real-time requirements.

SDN’s impact extends to scalability, providing a flexible framework for the addition or removal of devices, supporting the evolving needs of the data center. With network virtualization, SDN simplifies complex configurations, enhancing flexibility and facilitating the deployment of applications.

This transformative technology aligns seamlessly with the requirements of modern, virtualized workloads, offering a centralized view for streamlined network management, improved security measures, and optimized application performance. In essence, SDN in the data center marks a paradigm shift, introducing unprecedented levels of adaptability, efficiency, and control.

The Difference Between SDN and Traditional Networking

Software-Defined Networking (SDN) and traditional networks represent distinct paradigms in network architecture, each influencing data centers in unique ways.

Traditional Networks:

  • Hardware-Centric Control: In traditional networks, control and data planes are tightly integrated within network devices (routers, switches).
  • Static Configuration: Network configurations are manually set on individual devices, making changes time-consuming and requiring device-by-device adjustments.
  • Limited Flexibility: Traditional networks often lack the agility to adapt to changing traffic patterns or dynamic workloads efficiently.

SDN (Software-Defined Networking):

  • Decoupled Control and Data Planes: SDN separates the control plane (logic and decision-making) from the data plane (forwarding of traffic), providing a centralized and programmable control.
  • Dynamic Configuration: With a centralized controller, administrators can dynamically configure and manage the entire network, enabling faster and more flexible adjustments.
  • Virtualization and Automation: SDN allows for network virtualization, enabling the creation of virtual networks and automated provisioning of resources based on application requirements.
  • Enhanced Scalability: SDN architectures can scale more effectively to meet the demands of modern applications and services.

In summary, while traditional networks rely on distributed, hardware-centric models, SDN introduces a more centralized and software-driven approach, offering enhanced agility, scalability, and cost-effectiveness, all of which positively impact the functionality and efficiency of data centers in the modern era.

Key Benefits SDN Provides for Data Centers

Software-Defined Networking (SDN) offers a multitude of advantages for data centers, particularly in addressing the evolving needs of modern IT environments.

  • Dealing with big data

As organizations increasingly delve into large data sets using parallel processing, SDN becomes instrumental in managing throughput and connectivity more effectively. The dynamic control provided by SDN ensures that the network can adapt to the demands of data-intensive tasks, facilitating efficient processing and analysis.

  • Supporting cloud-based traffic

The pervasive rise of cloud computing relies on on-demand capacity and self-service capabilities, both of which align seamlessly with SDN’s dynamic delivery based on demand and resource availability within the data center. This synergy enhances the cloud’s efficiency and responsiveness, contributing to a more agile and scalable infrastructure.

  • Managing traffic to numerous IP addresses and virtual machines

Through dynamic routing tables, SDN enables prioritization based on real-time network feedback. This not only simplifies the control and management of virtual machines but also ensures that network resources are allocated efficiently, optimizing overall performance.

  • Scalability and agility

The ease with which devices can be added to the network minimizes the risk of service interruption. This characteristic aligns well with the requirements of parallel processing and the overall design of virtualized networks, enhancing the scalability and adaptability of the infrastructure.

  • Management of policy and security

By efficiently propagating security policies throughout the network, including firewalling devices and other essential elements, SDN enhances the overall security posture. Centralized control allows for more effective implementation of policies, ensuring a robust and consistent security framework across the data center.

The Future of SDN

The future of Software-Defined Networking (SDN) holds several exciting developments and trends, reflecting the ongoing evolution of networking technologies. Here are some key aspects that may shape the future of SDN:

  • Increased Adoption in Edge Computing: As edge computing continues to gain prominence, SDN is expected to play a pivotal role in optimizing and managing distributed networks. SDN’s ability to provide centralized control and dynamic resource allocation aligns well with the requirements of edge environments.
  • Integration with 5G Networks: The rollout of 5G networks is set to revolutionize connectivity, and SDN is likely to play a crucial role in managing the complexity of these high-speed, low-latency networks. SDN can provide the flexibility and programmability needed to optimize 5G network resources.
  • AI and Machine Learning Integration: The integration of artificial intelligence (AI) and machine learning (ML) into SDN is expected to enhance network automation, predictive analytics, and intelligent decision-making. This integration can lead to more proactive network management, better performance optimization, and improved security.
  • Intent-Based Networking (IBN): Intent-Based Networking, which focuses on translating high-level business policies into network configurations, is likely to become more prevalent. SDN, with its centralized control and programmability, aligns well with the principles of IBN, offering a more intuitive and responsive network management approach.
  • Enhanced Security Measures: SDN’s capabilities in implementing granular security policies and its centralized control make it well-suited for addressing evolving cybersecurity challenges. Future developments may include further advancements in SDN-based security solutions, leveraging its programmability for adaptive threat response.

In summary, the future of SDN is marked by its adaptability to emerging technologies, including edge computing, 5G, AI, and containerization. As networking requirements continue to evolve, SDN is poised to play a central role in shaping the next generation of flexible, intelligent, and efficient network architectures.

What is an Edge Data Center?

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Edge data centers are compact facilities strategically located near user populations. Designed for reduced latency, they deliver cloud computing resources and cached content locally, enhancing user experience. Often connected to larger central data centers, these facilities play a crucial role in decentralized computing, optimizing data flow, and responsiveness.

Key Characteristics of Edge Data Centers

Acknowledging the nascent stage of edge data centers as a trend, professionals recognize flexibility in definitions. Different perspectives from various roles, industries, and priorities contribute to a diversified understanding. However, most edge computers share similar key characteristics, including the following:

Local Presence and Remote Management:

Edge data centers distinguish themselves by their local placement near the areas they serve. This deliberate proximity minimizes latency, ensuring swift responses to local demands.

Simultaneously, these centers are characterized by remote management capabilities, allowing professionals to oversee and administer operations from a central location.

Compact Design:

In terms of physical attributes, edge data centers feature a compact design. While housing the same components as traditional data centers, they are meticulously packed into a much smaller footprint.

This streamlined design is not only spatially efficient but also aligns with the need for agile deployment in diverse environments, ranging from smart cities to industrial settings.

Integration into Larger Networks:

An inherent feature of edge data centers is their role as integral components within a larger network. Rather than operating in isolation, an edge data center is part of a complex network that includes a central enterprise data center.

This interconnectedness ensures seamless collaboration and efficient data flow, acknowledging the role of edge data centers as contributors to a comprehensive data processing ecosystem.

Mission-Critical Functionality:

Edge data centers house mission-critical data, applications, and services for edge-based processing and storage. This mission-critical functionality positions edge data centers at the forefront of scenarios demanding real-time decision-making, such as IoT deployments and autonomous systems.

Use Cases of Edge Computing

Edge computing has found widespread application across various industries, offering solutions to challenges related to latency, bandwidth, and real-time processing. Here are some prominent use cases of edge computing:

  • Smart Cities: Edge data centers are crucial in smart city initiatives, processing data from IoT devices, sensors, and surveillance systems locally. This enables real-time monitoring and management of traffic, waste, energy, and other urban services, contributing to more efficient and sustainable city operations.
  • Industrial IoT (IIoT): In industrial settings, edge computing process data from sensors and machines on the factory floor, facilitating real-time monitoring, predictive maintenance, and optimization of manufacturing processes for increased efficiency and reduced downtime.
  • Retail Optimization: Edge data centers are employed in the retail sector for applications like inventory management, cashierless checkout systems, and personalized customer experiences. Processing data locally enhances in-store operations, providing a seamless and responsive shopping experience for customers.
  • Autonomous Vehicles: Edge computing process data from sensors, cameras, and other sources locally, enabling quick decision-making for navigation, obstacle detection, and overall vehicle safety.
  • Healthcare Applications: In healthcare, edge computing are utilized for real-time processing of data from medical devices, wearable technologies, and patient monitoring systems. This enables timely decision-making, supports remote patient monitoring, and enhances the overall efficiency of healthcare services.

Impact on Existing Centralized Data Center Models

The impact of edge data centers on existing data center models is transformative, introducing new paradigms for processing data, reducing latency, and addressing the needs of emerging applications. While centralized data centers continue to play a vital role, the integration of edge data centers creates a more flexible and responsive computing ecosystem. Organizations must adapt their strategies to embrace the benefits of both centralized and edge computing for optimal performance and efficiency.


In conclusion, edge data centers play a pivotal role in shaping the future of data management by providing localized processing capabilities, reducing latency, and supporting a diverse range of applications across industries. As technology continues to advance, the significance of edge data centers is expected to grow, influencing the way organizations approach computing in the digital era.


Related articles: What Is Edge Computing?

What Is Software-Defined Networking (SDN)?

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SDN, short for Software-Defined Networking, is a networking architecture that separates the control plane from the data plane. It involves decoupling network intelligence and policies from the underlying network infrastructure, providing a centralized management and control framework.

How does Software-Defined Networking (SDN) Work?

SDN operates by employing a centralized controller that manages and configures network devices, such as switches and routers, through open protocols like OpenFlow. This controller acts as the brain of the network, allowing administrators to define network behavior and policies centrally, which are then enforced across the entire network infrastructure.SDN network can be classified into three layers, each of which consists of various components.

  • Application layer: The application layer contains network applications or functions that organizations use. There can be several applications related to network monitoring, network troubleshooting, network policies and security.
  • Control layer: The control layer is the mid layer that connects the infrastructure layer and the application layer. It means the centralized SDN controller software and serves as the land of control plane where intelligent logic is connected to the application plane.
  • Infrastructure layer: The infrastructure layer consists of various networking equipment, for instance, network switches, servers or gateways, which form the underlying network to forward network traffic to their destinations.

To communicate between the three layers of SDN network, northbound and southbound application programming interfaces (APIs) are used. Northbound API enables communications between the application layers and the controller, while southbound API allows the controller communicate with the networking equipment.

What are the Different Models of SDN?

Depending on how the controller layer is connected to SDN devices, SDN networks can be divided into four different types which we can classify as follows:

  1. Open SDN

Open SDN has a centralized control plane and uses OpenFlow for the southbound API of the traffic from physical or virtual switches to the SDN controller.

  1. API SDN

API SDN, is different from open SDN. Rather than relying on an open protocol, application programming interfaces control how data moves through the network on each device.

  1. Overlay Model SDN

Overlay model SDN doesn’t address physical netwroks underneath but builds a virtual network on top of the current hardware. It operates on an overlay network and offers tunnels with channels to data centers to solve data center connectivity issues.

  1. Hybrid Model SDN

Hybrid model SDN, also called automation-based SDN, blends SDN features and traditional networking equipment. It uses automation tools such as agents, Python, etc. And components supporting different types of OS.

What are the Advantages of SDN?

Different SDN models have their own merits. Here we will only talk about the general benefits that SDN has for the network.

  1. Centralized Management

Centralization is one of the main advantages granted by SDN. SDN networks enable centralized management over the network using a central management tool, from which data center managers can benefit. It breaks out the barrier created by traditional systems and provides more agility for both virtual and physical network provisioning, all from a central location.

  1. Security

Despite the fact that the trend of virtualization has made it more difficult to secure networks against external threats, SDN brings massive advantages. SDN controller provides a centralized location for network engineers to control the entire security of the network. Through the SDN controller, security policies and information are ensured to be implemented within the network. And SDN is equipped with a single management system, which helps to enhance security.

  1. Cost-Savings

SDN network lands users with low operational costs and low capital expenditure costs. For one thing, the traditional way to ensure network availability was by redundancy of additional equipment, which of course adds costs. Compared to the traditional way, a software-defined network is much more efficient without the need to acquire more network switches. For another, SDN works great with virtualization, which also helps to reduce the cost for adding hardware.

  1. Scalability

Owing to the OpenFlow agent and SDN controller that allow access to the various network components through its centralized management, SDN gives users more scalability. Compared to a traditional network setup, engineers are provided with more choices to change network infrastructure instantly without purchasing and configuring resources manually.

In conclusion, in modern data centers, where agility and efficiency are critical, SDN plays a vital role. By virtualizing network resources, SDN enables administrators to automate network management tasks and streamline operations, resulting in improved efficiency, reduced costs, and faster time to market for new services.

SDN is transforming the way data centers operate, providing tremendous flexibility, scalability, and control over network resources. By embracing SDN, organizations can unleash the full potential of their data centers and stay ahead in an increasingly digital and interconnected world.


Related articles: Open Source vs Open Networking vs SDN: What’s the Difference

What Is FCoE and How Does It Work?

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In the rapidly evolving landscape of networking technologies, one term gaining prominence is FCoE, or Fibre Channel over Ethernet. As businesses seek more efficient and cost-effective solutions, understanding the intricacies of FCoE becomes crucial. This article delves into the world of FCoE, exploring its definition, historical context, and key components to provide a comprehensive understanding of how it works.

What is FCoE (Fibre Channel over Ethernet)?

  • In-Depth Definition

Fibre Channel over Ethernet, or FCoE, is a networking protocol that enables the convergence of traditional Fibre Channel storage networks with Ethernet-based data networks. This convergence is aimed at streamlining infrastructure, reducing costs, and enhancing overall network efficiency.

  • Historical Context

The development of FCoE can be traced back to the need for a more unified and simplified networking environment. Traditionally, Fibre Channel and Ethernet operated as separate entities, each with its own set of protocols and infrastructure. FCoE emerged as a solution to bridge the gap between these two technologies, offering a more integrated and streamlined approach to data storage and transfer.

  • Key Components

At its core, FCoE is a fusion of Fibre Channel and Ethernet technologies. The key components include Converged Network Adapters (CNAs), which allow for the transmission of both Fibre Channel and Ethernet traffic over a single network link. Additionally, FCoE employs a specific protocol stack that facilitates the encapsulation and transport of Fibre Channel frames within Ethernet frames.

How does Fibre Channel over Ethernet Work?

  • Convergence of Fibre Channel and Ethernet

The fundamental principle behind FCoE is the convergence of Fibre Channel and Ethernet onto a shared network infrastructure. This convergence is achieved through the use of CNAs, specialized network interface cards that support both Fibre Channel and Ethernet protocols. By consolidating these technologies, FCoE eliminates the need for separate networks, reducing complexity and improving resource utilization.

  • Protocol Stack Overview

FCoE utilizes a layered protocol stack to encapsulate Fibre Channel frames within Ethernet frames. This stack includes the Fibre Channel over Ethernet Initialization Protocol (FIP), which plays a crucial role in the discovery and initialization of FCoE-capable devices. The encapsulation process allows Fibre Channel traffic to traverse Ethernet networks seamlessly.

  • FCoE vs. Traditional Fibre Channel

Comparing FCoE with traditional Fibre Channel reveals distinctive differences in their approaches to data networking. While traditional Fibre Channel relies on dedicated storage area networks (SANs), FCoE leverages Ethernet networks for both data and storage traffic. This fundamental shift impacts factors such as infrastructure complexity, cost, and overall network design.


” Also Check – IP SAN (IP Storage Area Network) vs. FCoE (Fibre Channel over Ethernet) | FS Community

What are the Advantages of Fibre Channel over Ethernet?

  1. Enhanced Network Efficiency

FCoE optimizes network efficiency by combining storage and data traffic on a single network. This consolidation reduces the overall network complexity and enhances the utilization of available resources, leading to improved performance and reduced bottlenecks.

  1. Cost Savings

One of the primary advantages of FCoE is the potential for cost savings. By converging Fibre Channel and Ethernet, organizations can eliminate the need for separate infrastructure and associated maintenance costs. This not only reduces capital expenses but also streamlines operational processes.

  1. Scalability and Flexibility

FCoE provides organizations with the scalability and flexibility needed in dynamic IT environments. The ability to seamlessly integrate new devices and technologies into the network allows for future expansion without the constraints of traditional networking approaches.

Conclusion

In conclusion, FCoE stands as a transformative technology that bridges the gap between Fibre Channel and Ethernet, offering enhanced efficiency, cost savings, and flexibility in network design. As businesses navigate the complexities of modern networking, understanding FCoE becomes essential for those seeking a streamlined and future-ready infrastructure.


Related Articles: Demystifying IP SAN: A Comprehensive Guide to Internet Protocol Storage Area Networks

What Is Layer 4 Switch and How Does It Work?

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What’s Layer 4 Switch?

A Layer 4 switch, also known as a transport layer switch or content switch, operates on the transport layer (Layer 4) of the OSI (Open Systems Interconnection) model. This layer is responsible for end-to-end communication and data flow control between devices across a network.Here are key characteristics and functionalities of Layer 4 switches:

  • Packet Filtering: Layer 4 switches can make forwarding decisions based on information from the transport layer, including source and destination port numbers. This allows for more sophisticated filtering than traditional Layer 2 (Data Link Layer) or Layer 3 (Network Layer) switches.
  • Load Balancing: One of the significant features of Layer 4 switches is their ability to distribute network traffic across multiple servers or network paths. This load balancing helps optimize resource utilization, enhance performance, and ensure high availability of services.
  • Session Persistence: Layer 4 switches can maintain session persistence, ensuring that requests from the same client are consistently directed to the same server. This is crucial for applications that rely on continuous connections, such as e-commerce or real-time communication services.
  • Connection Tracking: Layer 4 switches can track the state of connections, helping to make intelligent routing decisions. This is particularly beneficial in scenarios where connections are established and maintained between a client and a server.
  • Quality of Service (QoS): Layer 4 switches can prioritize network traffic based on the type of service or application. This ensures that critical applications receive preferential treatment in terms of bandwidth and response time.
  • Security Features: Layer 4 switches often come with security features such as access control lists (ACLs) and the ability to perform deep packet inspection. These features contribute to the overall security of the network by allowing or denying traffic based on specific criteria.
  • High Performance: Layer 4 switches are designed for high-performance networking. They can efficiently handle a large number of simultaneous connections and provide low-latency communication between devices.

Layer 2 vs Layer 3 vs Layer 4 Switch

Layer 2 Switch:

Layer 2 switches operate at the Data Link Layer (Layer 2) and are primarily focused on local network connectivity. They make forwarding decisions based on MAC addresses in Ethernet frames, facilitating basic switching within the same broadcast domain. VLAN support allows for network segmentation.

However, Layer 2 switches lack traditional IP routing capabilities, making them suitable for scenarios where simple switching and VLAN segmentation meet the networking requirements.

Layer 3 Switch:

Operating at the Network Layer (Layer 3), Layer 3 switches combine switching and routing functionalities. They make forwarding decisions based on both MAC and IP addresses, supporting IP routing for communication between different IP subnets. With VLAN support, these switches are versatile in interconnecting multiple IP subnets within an organization.

Layer 3 switches can make decisions based on IP addresses and support dynamic routing protocols like OSPF and RIP, making them suitable for more complex network environments.

Layer 4 Switch:

Layer 4 switches operate at the Transport Layer (Layer 4), building on the capabilities of Layer 3 switches with advanced features. In addition to considering MAC and IP addresses, Layer 4 switches incorporate port numbers at the transport layer. This allows for the optimization of traffic flow, making them valuable for applications with high performance requirements.

Layer 4 switches support features such as load balancing, session persistence, and Quality of Service (QoS). They are often employed to enhance application performance, provide advanced traffic management, and ensure high availability in demanding network scenarios.

Summary:

In summary, Layer 2 switches focus on basic local connectivity and VLAN segmentation. Layer 3 switches, operating at a higher layer, bring IP routing capabilities and are suitable for interconnecting multiple IP subnets. Layer 4 switches, operating at the Transport Layer, further extend capabilities by optimizing traffic flow and offering advanced features like load balancing and enhanced QoS.

The choice between these switches depends on the specific networking requirements, ranging from simple local connectivity to more complex scenarios with advanced routing and application performance needs.


” Also Check – Layer 2, Layer 3 & Layer 4 Switch: What’s the Difference?

Layer 2 vs Layer 3 vs Layer 4 Switch: Key Parameters to Consider When Purchasing

To make an informed decision for your business, it’s essential to consider the key parameters between Layer 2, Layer 3, and Layer 4 switches when purchasing.

  1. Network Scope and Size:

When considering the purchase of switches, the size and scope of your network are critical factors. Layer 2 switches are well-suited for local network connectivity and smaller networks with straightforward topologies.

In contrast, Layer 3 switches come into play for larger networks with multiple subnets, offering essential routing capabilities between different LAN segments.

Layer 4 switches, with advanced traffic optimization features, are particularly beneficial in more intricate network environments where optimizing traffic flow is a priority.

  1. Functionality and Use Cases:

The functionality of the switch plays a pivotal role in meeting specific network needs. Layer 2 switches provide basic switching and VLAN support, making them suitable for scenarios requiring simple local connectivity and network segmentation.

Layer 3 switches, with combined switching and routing capabilities, excel in interconnecting multiple IP subnets and routing between VLANs.

Layer 4 switches take functionality a step further, offering advanced features such as load balancing, session persistence, and Quality of Service (QoS), making them indispensable for optimizing traffic flow and supporting complex use cases.

  1. Routing Capabilities:

Understanding the routing capabilities of each switch is crucial. Layer 2 switches lack traditional IP routing capabilities, focusing primarily on MAC address-based forwarding.

Layer 3 switches, on the other hand, support basic IP routing, allowing communication between different IP subnets.

Layer 4 switches, while typically not performing traditional IP routing, specialize in optimizing traffic flow at the transport layer, enhancing the efficiency of data transmission.

  1. Scalability and Cost:

The scalability of the switch is a key consideration, particularly as your network grows. Layer 2 switches may have limitations in larger networks, while Layer 3 switches scale well for interconnecting multiple subnets.

Layer 4 switch scalability depends on specific features and capabilities. Cost is another crucial factor, with Layer 2 switches generally being more cost-effective compared to Layer 3 and Layer 4 switches. The decision here involves balancing your budget constraints with the features required for optimal network performance.

  1. Security Features:

Security is paramount in any network. Layer 2 switches provide basic security features like port security. Layer 3 switches enhance security with the inclusion of access control lists (ACLs) and IP security features.

Layer 4 switches may offer additional security features, including deep packet inspection, providing a more robust defense against potential threats.

In conclusion, when purchasing switches, carefully weighing factors such as network scope, functionality, routing capabilities, scalability, cost, and security features ensures that the selected switch aligns with the specific requirements of your network, both in the present and in anticipation of future growth and complexities.

The Future of Layer 4 Switch

The future development of Layer 4 switches is expected to revolve around addressing the growing complexity of modern networks. Enhanced application performance, better support for cloud environments, advanced security features, and alignment with virtualization and SDN trends are likely to shape the evolution of Layer 4 switches, ensuring they remain pivotal components in optimizing and securing network infrastructures.


In conclusion, the decision between Layer 2, Layer 3, and Layer 4 switches is pivotal for businesses aiming to optimize their network infrastructure. Careful consideration of operational layers, routing capabilities, functionality, and use cases will guide you in selecting the switch that aligns with your specific needs. Whether focusing on basic connectivity, IP routing, or advanced traffic optimization, choosing the right switch is a critical step in ensuring a robust and efficient network for your business.


Related Article: Layer 2 vs Layer 3 Switch: Which One Do You Need? | FS Community

The Chip Shortage: Current Challenges, Predictions, and Potential Solutions

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The COVID-19 pandemic caused several companies to shut down, and the implications were reduced production and altered supply chains. In the tech world, where silicon microchips are the heart of everything electronic, raw material shortage became a barrier to new product creation and development.

During the lockdown periods, some essential workers were required to stay home, which meant chip manufacturing was unavailable for several months. By the time lockdown was lifted and the world embraced the new normal, the rising demand for consumer and business electronics was enough to ripple up the supply chain.

Below, we’ve discussed the challenges associated with the current chip shortage, what to expect moving forward, and the possible interventions necessary to overcome the supply chain constraints.

Challenges Caused by the Current Chip Shortage

As technology and rapid innovation sweeps across industries, semiconductor chips have become an essential part of manufacturing – from devices like switches, wireless routers, computers, and automobiles to basic home appliances.

To understand and quantify the impact this chip shortage has caused spanning the industry, we’ll need to look at some of the most affected sectors. Here’s a quick breakdown of how things have unfolded over the last eighteen months.

Automobile Industry

in North America and Europe had slowed or stopped production due to a lack of computer chips. Major automakers like Tesla, Ford, BMW, and General Motors have all been affected. The major implication is that the global automobile industry will manufacture 4 million fewer cars by the end of 2021 than earlier planned, and it will forfeit an average of $110 billion in revenue.

Consumer Electronics

Consumer electronics such as desktop PCs and smartphones rose in demand throughout the pandemic, thanks to the shift to virtual learning among students and the rise in remote working. At the start of the pandemic, several automakers slashed their vehicle production forecasts before abandoning open semiconductor chip orders. And while the consumer electronics industry stepped in and scooped most of those microchips, the supply couldn’t catch up with the demand.

Data Centers

Most chip fabrication companies like Samsung Foundries, Global Foundries, and TSMC prioritized high-margin orders from PC and data center customers during the pandemic. And while this has given data centers a competitive edge, it isn’t to say that data centers haven’t been affected by the global chip shortage.

Some of the components data centers have struggled to source include those needed to put together their data center switching systems. These include BMC chips, capacitors, resistors, circuit boards, etc. Another challenge is the extended lead times due to wafer and substrate shortages, as well as reduced assembly capacity.

LED Lighting

LED backlights common in most display screens are powered by hard-to-find semiconductor chips. The prices of gadgets with LED lighting features are now highly-priced due to the shortage of raw materials and increased market demand. This is expected to continue up to the beginning of 2022.

Renewable Energy- Solar and Turbines

Renewable energy systems, particularly solar and turbines, rely on semiconductors and sensors to operate. The global supply chain constraints have hurt the industry and even forced some energy solutions manufacturers like Enphase Energy to

Semiconductor Trends: What to Expect Moving Forward

In response to the global chip shortage, several component manufacturers have ramped up production to help mitigate the shortages. However, top electronics and semiconductor manufacturers say the crunch will only worsen before it gets better. Most of these industry leaders speculate that the semiconductor shortage could persist into 2023.

Based on the ongoing disruption and supply chain volatility, various analysts in a recent CNBC article and Bloomberg interview echoed their views, and many are convinced that the coming year will be challenging. Here are some of the key takeaways:

Pat Gelsinger, CEO of Intel Corp., noted in April 2021 that the chip shortage would recover after a couple of years.

DigiTimes Report found that Intel and AMD server ICs and data centers have seen their lead times extend to 45 to 66 weeks.

The world’s third-largest EMS and OEM provider, Flex Ltd., expects the global semiconductor shortage to proceed into 2023.

In May 2021, Global Foundries, the fourth-largest contract semiconductor manufacturer, signed a $1.6 billion, 3-year silicon supply deal with AMD, and in late June, it launched its new $4 billion, 300mm-wafer facility in Singapore. Yet, the company says its production capacity will only increase component production earliest in 2023.

TMSC, one of the leading pure-play foundries in the industry, says it won’t meaningfully increase the component output until 2023. However, it’s optimistic that the company will ramp up the fabrication of automotive micro-controllers by 60% by the end of 2021.

From the industry insights above, it’s evident that despite the many efforts that major players put into resolving the global chip shortage, the bottlenecks will probably persist throughout 2022.

Additionally, some industry observers believe that the move by big tech companies such as Amazon, Microsoft, and Google to design their own chips for cloud and data center business could worsen the chip shortage crisis and other problems facing the semiconductor industry.

article, the authors hint that the entry of Microsoft, Amazon, and Google into the chip design market will be a turning point in the industry. These tech giants have the resources to design superior and cost-effective chips of their own, something most chip designers like Intel have in limited proportions.

Since these tech giants will become independent, each will be looking to create component stockpiles to endure long waits and meet production demands between inventory refreshes. Again, this will further worsen the existing chip shortage.

Possible Solutions

To stay ahead of the game, major industry players such as chip designers and manufacturers and the many affected industries have taken several steps to mitigate the impacts of the chip shortage.

For many chip makers, expanding their production capacity has been an obvious response. Other suppliers in certain regions decided to stockpile and limit exports to better respond to market volatility and political pressures.

Similarly, improving the yields or increasing the number of chips manufactured from a silicon wafer is an area that many manufacturers have invested in to boost chip supply by some given margin.

Here are the other possible solutions that companies have had to adopt:

Embracing flexibility to accommodate older chip technologies that may not be “state of the art” but are still better than nothing.

Leveraging software solutions such as smart compression and compilation to build efficient AI models to help unlock hardware capabilities.

LED Lighting

The latest global chip shortage has led to severe shocks in the semiconductor supply chain, affecting several industries from automobile, consumer electronics, data centers, LED, and renewables.

Industry thought leaders believe that shortages will persist into 2023 despite the current build-up in mitigation measures. And while full recovery will not be witnessed any time soon, some chip makers are optimistic that they will ramp up fabrication to contain the demand among their automotive customers.

That said, staying ahead of the game is an all-time struggle considering this is an issue affecting every industry player, regardless of size or market position. Expanding production capacity, accommodating older chip technologies, and leveraging software solutions to unlock hardware capabilities are some of the promising solutions.

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Article Source: The Chip Shortage: Current Challenges, Predictions, and Potential Solutions

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Impact of Chip Shortage on Datacenter Industry

Impact of Chip Shortage on Datacenter Industry

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As the global chip shortage let rip, many chip manufacturers have to slow or even halt semiconductor production. Makers of all kinds of electronics such as switches, PCs, servers are all scrambling to get enough chips in the pipeline to match the surging demand for their products. Every manufacturer, supplier and solution provider in datacenter industry is feeling the impact of the ongoing chip scarcity. However, relief is nowhere in sight yet.

What’s Happening?

Due to the rise of AI and cloud computing, datacenter chips have been a highly charged topic in recent times. As networking switches and modern servers, indispensable equipment in datacenter applications, use more advanced components than an average consumer’s PC, naturally when it comes to chip manufacturers and suppliers, data centers are given the top priority. However, with the demand for data center machines far outstripping supply, chip shortages may continue to be pervasive across the next few years. Coupled with economic uncertainties caused by the pandemic, it further puts stress on datacenter management.

According to a report from the Dell’Oro Group, robust datacenter switch sales over the past year could foretell a looming shortage. As the mismatch in supply and demand keeps growing, enterprises looking to buy datacenter switches face extended lead times and elevated costs over the course of the next year.

“So supply is decreasing and demand is increasing,” said Sameh Boujelbene, leader of the analyst firm’s campus and data-center research team. “There’s a belief that things will get worse in the second half of the year, but no consensus on when it’ll start getting better.”

Back in March, Broadcom said that more than 90% of its total chip output for 2021 had already been ordered by customers, who are pressuring it for chips to meet booming demand for servers used in cloud data centers and consumer electronics such as 5G phones.

“We intend to meet such demand, and in doing so, we will maintain our disciplined process of carefully reviewing our backlog, identifying real end-user demand, and delivering products accordingly,” CEO Hock Tan said on a conference call with investors and analysts.

Major Implications

Extended Lead Times

Arista Networks, one of the largest data center networking switch vendors and a supplier of switches to cloud providers, foretells that switch-silicon lead times will be extended to as long as 52 weeks.

“The supply chain has never been so constrained in Arista history,” the company’s CEO, Jayshree Ullal, said on an earnings call. “To put this in perspective, we now have to plan for many components with 52-week lead time. COVID has resulted in substrate and wafer shortages and reduced assembly capacity. Our contract manufacturers have experienced significant volatility due to country specific COVID orders. Naturally, we’re working more closely with our strategic suppliers to improve planning and delivery.”

Hock Tan, CEO of Broadcom, also acknowledged on an earnings call that the company had “started extending lead times.” He said, “part of the problem was that customers were now ordering more chips and demanding them faster than usual, hoping to buffer against the supply chain issues.”

Elevated Cost

Vertiv, one of the biggest sellers of datacenter power and cooling equipment, mentioned it had to delay previously planned “footprint optimization programs” due to strained supply. The company’s CEO, Robert Johnson, said on an earnings call, “We have decided to delay some of those programs.”

Supply chain constraints combined with inflation would cause “some incremental unexpected costs over the short term,” he said, “To share the cost with our customers where possible may be part of the solution.”

“Prices are definitely going to be higher for a lot of devices that require a semiconductor,” says David Yoffie, a Harvard Business School professor who spent almost three decades serving on the board of Intel.

Conclusion

There is no telling that how the situation will continue playing out and, most importantly, when supply and demand might get back to normal. Opinions vary on when the shortage will end. The CEO of chipmaker STMicro estimated that the shortage will end by early 2023. Intel CEO Patrick Gelsinger said it could last two more years.

As a high-tech network solutions and services provider, FS has been actively working with our customers to help them plan for, adapt to, and overcome the supply chain challenges, hoping that we can both ride out this chip shortage crisis. At least, we cannot lose hope, as advised by Bill Wyckoff, vice president at technology equipment provider SHI International, “This is not an ‘all is lost’ situation. There are ways and means to keep your equipment procurement and refresh plans on track if you work with the right partners.”

Article Source: Impact of Chip Shortage on Datacenter Industry

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Data Center Infrastructure Basics and Management Solutions

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Datacenter infrastructure refers to all the physical components in a data center environment. These physical components play a vital role in the day-to-day operations of a data center. Hence, data center management challenges are an urgent issue that IT departments need to pay attention to. On the one hand, it is to improve the energy efficiency of the data center; on the other hand, it is to know about the operating performance of the data center in real-time ensuring its good working condition and maintaining enterprise development.

Data Center Infrastructure Basics

The standard for data center infrastructure is divided into four tiers, each of which consists of different facilities. They mainly include cabling systems, power facilities, cooling facilities, network infrastructure, storage infrastructure, and computing resources.

There are roughly two types of infrastructure inside a data center: the core components and IT infrastructure. Network infrastructure, storage infrastructure, and computing resources belong to the former, while cooling equipment, power, redundancy, etc. belong to the latter.

Core Components

Network, storage, and computing systems are vital infrastructures for data centers to achieve sharing access to applications and data, providing data centers with shared access to applications and data. Also, they are the core components of data centers.

Network Infrastructure

Datacenter network infrastructure is a combination of network resources, consisting of switches, routers, load balancing, analytics, etc., to facilitate the storage and processing of applications and data. Modern data center networking architectures, through using full-stack networking and security virtualization platforms that support a rich set of data services, can achieve connecting everything from VMs, containers, and bare-metal applications, while enabling centralized management and fine-grained security controls.

Storage Infrastructure

Datacenter storage is a general term for the tools, technologies and processes for designing, implementing, managing and monitoring storage infrastructure and resources in data centers, mainly referring to the equipment and software technologies that implement data and application storage in data center facilities. These include hard drives, tape drives and other forms of internal and external storage and backup management software utilities external storage facilities/solutions.

Computing Resources

A data center meter is a memory and processing power to run applications, usually provided by high-end servers. In the edge computing model, the processing and memory used to run applications on servers may be virtualized, physical, distributed among containers or distributed among remote nodes.

IT Infrastructure

As data centers become critical to enterprise IT operations, it is equally important to keep them running efficiently. When designing data center infrastructure, it is necessary to evaluate its physical environment, including cabling system, power system, cooling system to ensure the security of the physical environment of the data center.

Cabling Systems

The integrated cabling is an important part of data center cable management, supporting the connection, intercommunication and operation of the entire data center network. The system is usually composed of copper cables, optical cables, connectors and wiring equipment. The application of the data center integrated wiring system has the characteristics of high density, high performance, high reliability, fast installation, modularization, future-oriented, and easy application.

Power Systems

Datacenter digital infrastructure requires electricity to operate. Even an interruption of a fraction of a second will result in a significant impact. Hence, power infrastructure is one of the most critical components of a data center. The data center power chain starts at the substation and ends up through building transformers, switches, uninterruptible power supplies, power distribution units, and remote power panels to racks and servers.

Cooling Systems

Data center servers generate a lot of heat while running. Based on this characteristic, cooling is critical to data center operations, aiming to keep systems online. The amount of power each rack can keep cool by itself places a limit on the amount of power a data center can consume. Generally, each rack can allow the data center to operate at an average 5-10 kW cooling density, but some may be higher.

data center

Data Center Infrastructure Management Solutions

Due to the complexity of IT equipment in a data center, the availability, reliability, and maintenance of its components require more attention. Efficient data center operations can be achieved through balanced investments in facilities and accommodating equipment.

Energy Usage Monitoring Equipment

Traditional data centers lack the energy usage monitoring instruments and sensors required to comply with ASHRAE standards and collect measurement data for use in calculating data center PUE. It results in a poor monitoring environment for the power system of the data center. One measure is to install energy monitoring components and systems on power systems to measure data center energy efficiency. Enterprise teams can implement effective strategies by the measure to balance overall energy usage efficiency and effectively monitor the energy usage of all other nodes.

Cooling Facilities Optimization

Independent computer room air conditioning units used in traditional data centers often have separate controls and set points, resulting in excessive operation due to temperature and humidity adjustments. It’s a good way for helping servers to achieve cooling by creating hot-aisle/cold-aisle layouts to maximize the flow of cold air to the equipment intakes and the hot exhaust air from the equipment racks. The creation of hot or cold aisles can eliminate the mixing of hot and cold air by adding partitions or ceilings.

CRAC Efficiency Improvement

Packaged DX air conditioners likely compose the most common type of cooling equipment for smaller data centers. These units are often described as CRAC units. There are, however, there are several ways to improve the energy efficiency of the cooling system employing DX units. Indoor CRAC units are available with a few different heat rejection options.

  • – As with rooftop units, adding evaporative spray can improve the efficiency of air-cooled CRAC units.
  • – A pre-cooling water coil can be added to the CRAC unit upstream of the evaporator coil. When ambient conditions allow the condenser water to be cooled to the extent that it provides direct cooling benefits to the air entering the CRAC unit, the condenser water is diverted to the pre-cooling coil. This will reduce or sometimes eliminate the need for compressor-based cooling for the CRAC unit.

DCIM

Data center infrastructure management is the combination of IT and operations to manage and optimize the performance of data center infrastructure within an organization. DCIM tools help data center operators monitor, measure, and manage the utilization and energy consumption of data center-related equipment and facility infrastructure components, effectively improving the relationship between data center buildings and their systems.

DCIM enables bridging of information across organizational domains such as data center operations, facilities, and IT to maximize data center utilization. Data center operators create flexible and efficient operations by visualizing real-time temperature and humidity status, equipment status, power consumption, and air conditioning workloads in server rooms.

Preventive Maintenance

In addition to the above management and operation solutions for infrastructure, unplanned maintenance is also an aspect to consider. Unplanned maintenance typically costs 3-9 times more than planned maintenance, primarily due to overtime labor costs, collateral damage, emergency parts, and service calls. IT teams can create a recurring schedule to perform preventive maintenance on the data center. Regularly checking the infrastructure status and repairing and upgrading the required components promptly can keep the internal infrastructure running efficiently, as well as extend the lifespan and overall efficiency of the data center infrastructure.

Article Source: Data Center Infrastructure Basics and Management Solutions

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Understanding Data Center Redundancy

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Maximizing the uptime should be the top priority for every data center, be they small or hyperscale. To keep your data center constantly running, a plan for redundancy systems is a must.

What Is Data Center Redundancy?

Data center redundancy refers to a system design where critical components such as UPS units, cooling systems and backup generators are duplicated so that data center operations can continue even if a component fails. For example, a redundant UPS system starts working when a power outage happens. In the event of downtime due to hazardous weather, power outages, or component failures, data center backup components play their role to keep the whole system running.

Why Is Data Center Redundancy Important?

It is imperative for businesses to increase uptime and recover more quickly from downtime, whether unexpected or planned. Downtime hurts business. It can have serious and direct impact on brand images, business operations, and customer experience, resulting in devastating financial losses, missed business opportunities and a tarnished reputation. Even for small businesses, unscheduled downtime can still cost hundreds of dollars per minute.

Redundancy configuration in data centers helps cut the risk of downtime, thus reducing losses caused by undesired impacts. A well-planned redundancy design means shorter potential downtime in the long run. Moreover, redundant components also ensure that data is safe and secure as data center operations keep working and never fail.

Redundancy is also a crucial factor in gauging data center reliability, performance and availability. The Uptime Institute offers a tier classification system that certifies data centers according to four distinct tiers—Tier 1, Tier 2, Tier 3 and Tier 4. Each tier has strict and specific requirements around data center redundancy level.

Different Levels of Redundancy

There is no one-size-fits-all redundancy design. Lower levels of redundancy mean increased potential downtime in the long run. While more redundancy will result in less downtime but increased costs of maintaining the redundant components. however, if your business model requires as little downtime as possible, this is often justifiable in terms of profit and overall net growth. To choose the right configuration for your business, it is important to recognize the capabilities and risks of different redundancy models, including N, N+1, N+X, 2N, 2N+1, and 3N/2.

N Model

N equals the amount of capacity required to power, backup, or cool a facility at full IT load. It can represent the units that you want to duplicate such as a generator, UPS, or cooling unit. For example, if a data center requires three UPS units to operate at full capacity, N would equal three.

An architecture of N means the facility is designed only to keep a data center running at full capacity. Simply put, N is the same as zero redundancy. If the data center facility is at full load and there is a hardware failure, scheduled maintenance, or an unexpected outage, mission-critical applications would suffer. With an N design, any interruption would leave your business unable to access your data until the issue is resolved.

N+1 or N+X Model

An N+1 redundancy model provides a minimal level of resiliency by adding a single component—a UPS, HVAC system or generator—to the N architecture to support a failure and maintain a full workload. When one system is offline, the extra component takes over the load. Going back to the previous example, if N equals three UPS units, N+1 provides four. Likewise, an N+2 redundancy design provides two extra components. In our example, N+1 provides five UPS units instead of four. So N+X provides N+X extra components to reduce risks in the event of multiple simultaneous failures.

2N Model

2N redundancy creates a mirror image of the original UPS, cooling system or generators to provide full fault tolerance. It means if three UPS units are necessary to support full capacity, this redundancy model would include an additional set of three UPS units, for a total of six systems. This design also utilizes two independent distribution systems.

With a 2N model, data center operators can take down an entire set of components for maintenance without affecting normal operations. Moreover, in the event of unscheduled multiple component failures, the additional set takes over to maintain full capacity. The resiliency of this model greatly cuts the risks of downtime.

2N+1 Model

If 2N means full fault tolerance, 2N+1 delivers the fully fault-tolerant 2N model plus an extra component for extra protection. Not only can this model withstand multiple component failures, even in a worst-case scenario when the entire primary system is offline, it can still sustain N+1 redundancy. For its high level of reliability, this redundancy model is generally used by businesses that cannot tolerate even minor service disruptions.

N+1 2N+1 redundancy

3N/2 Model

The three-to-make-two or 3N/2 redundant model refers to a redundancy methodology where additional capacity is based on the load of the system. If we consider a 3N/2 scenario, three power delivery systems will power two servers, which means each power delivery system utilizes 67% of the available capacity. Likewise, in a 4N/3, there will be four power delivery systems powering three workloads (three servers). The 3N/2 could be upgraded to 4N/3, but only in theory. This is because such an elaborate model has so many components that it would be very difficult to manage and balance loads to maintain redundancy.

3N/2 redundancy

What’s the Right One for You?

Choosing a redundant model that meets your business needs can be challenging. Finding the right balance between reliability and cost is the key. For businesses that require as little downtime as possible, higher levels of redundancy are justifiable in terms of profit and overall net growth. For those that do not, lower levels of redundancy are acceptable. They are cheaper and more energy-efficient than the other more sophisticated redundancy designs.

In a word, there’s no right or wrong redundancy model because it depends on a range of factors like your business goals, budget, and IT environment. Consult your data center provider or discuss with your IT team to figure out the best option for you.

Article Source: Understanding Data Center Redundancy

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5 Factors to Consider for Data Center Environmental Monitoring

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What Are Data Center Environmental Standards

Data center environmental monitoring is vital for device operations. The data center architecture is divided into four layers where the equipment placed inside also affects the design of data center environmental standards.

  • Tier I defines data center standards for facilities with minimal redundancy.
  • Tier II provides redundant critical power and cooling components.
  • Tier III adds redundant transmission paths for power and cooling to redundant critical components.
  • Tier IV infrastructure is built on Tier Ⅲ and adds the concept of fault tolerance to infrastructure topology.

Enterprises must comply with fairly stringent environmental standards to ensure these facilities remain functional.

Evolution of Data Center Environmental Standards

As early as the 1970s and 1980s, data center environmental monitoring revolved around power facilities. For example, whether the environment where the power supply was located has proper isolation, whether the main power supply affected the operation of the overall equipment, but the cooling problem was rarely monitored. Some enterprises have explored cooling technologies to facilitate cooling in data centers, such as liquid cooling. Typically, enterprises used loud fans to control airflow. In some countries, the cost of electricity was high, so there was a greater emphasis on being able to supply enough electricity for a given system configuration.

In the 1990s, the power density of the rack became a considered issue of enterprise data center environmental standards. In the past, a simple power factor calculation could yield the required cooling value for a data center, but accurate cooling values could not be provided by the increasing rack densities. At this point, enterprises had to re-plan the airflow patterns of data center racks and equipment. This required IT managers to know more statistics when designing a data center, such as pressure drop, air velocity, and flow resistance.

By the early 20th century, power densities were still increasing, and thermal modeling was seen as a potential answer to optimizing the cooling of data center environments. The lack of necessary data implied that temperature data typically was collected after data center construction and then IT managers needed to make adjustments based on that information. Enterprises should choose the correct thermal model of equipment when building a data center to enhance data center environmental monitoring. Here are several environmental control methods when building a data center.

5 Factors in Data Center Environmental Controls

For ensuring the reliable operation of IT equipment within a rack, the primary concerns for monitoring and controlling data center environmental conditions are temperature, humidity, static electricity, physical and human safety. Moreover, data center environmental impact resulted from these factors not only on the ecological environment but also on data center security, energy efficiency, and the enterprise social image.

Temperature Control

Thermal control is always a challenging issue for data centers, as servers emit heat when they are running. If they are paralyzed by overheating, it will cripple data center operations. Temperature control can check if equipment is operating within the recommended temperature range. A temperature sensor is an effective method to solve temperature control. Placing them in strategic locations and reading the overall temperature allows IT managers to conduct temperature control promptly.

Humidity Control

Humidity control is closely related to temperature levels. High humidity can corrode hardware. Low humidity levels can cause electrostatic arcing problems. For this reason, cooling and ventilation systems need to detect and control the relative humidity in the room air. ASHRAE recommends operation within a dew point range of 41.9 to 59 degrees Fahrenheit with a maximum relative humidity of 60%. Datacenter designers need to invest in systems that can detect humidity and water near equipment to better monitor cooling fans and measure the presence of airflow during routine management. Of course, it is also possible to use a set of computer room air conditioner(CRAC) units on larger facilities to create consistent airflow that flows throughout the room. These CRAC systems typically work by drawing in and cooling heat, then expelling it as cool air through vents and air intakes leading to the server.

Electricity Monitoring

Static electricity is also one of the threats in the data center environment, it is an invisible nuisance. Some newer IT components can be damaged or completely fried by less than 25 volts of discharge. If this problem isn’t addressed, it might result in frequent disconnections, system crashes, and even data corruption. Unexpected bursts of energy in the form of electrostatic discharges may be the greatest threat to the performance of the average data center. To prevent such incidents, businesses must install energy monitors that are strategically located to detect the buildup of static electricity.

Fire Suppression

A comprehensive fire suppression system is a must-have feature in data center environmental standards. If an entire data center is to be protected from disaster, data center designers need to take security measures from fire and fire suppression systems to physical and virtual systems. Fire suppression systems are subject to regular testing and active monitoring of the data center to ensure that they will indeed do their job in the clutch.

Security Systems

Data security of data center environmental standards is also very important. IT departments must institute a limit that keeps intruders away from buildings as well as server rooms and the racks they are in. Setting up a complete range of physical security is a desirable method—from IP surveillance systems to advanced sensors. If unauthorized personnel is detected entering a building or server rack, it will alert data center managers.

Summary

The purpose of data center environmental monitoring is to provide a better operating environment for facilities and avoid some unplanned cases that affect the business of enterprises. For the above data center environmental controls, it is beneficial for enterprises to maintain data center security when designing data centers, which is conducive to data center management. Also, it properly controls the data center environmental impact on ecology and energy efficiency.

Article Source: 5 Factors to Consider for Data Center Environmental Monitoring

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