In traditional computing architectures, Central Processing Units (CPUs) and Graphics Processing Units (GPUs) play an important role, but with the increasing volume of data and the emergence of diversified data processing needs, these traditional units are gradually showing some bottlenecks and limitations. The introduction of DPUs makes up for these shortcomings and provides a more efficient, flexible, and customisable data processing solution. In this article, we will explore the differences and connections between DPUs, CPUs and GPUs.
What is a CPU?
The central processing unit (CPU) is the core of a computer system, responsible for executing instructions in the program and controlling the operation of other hardware. CPU adopts a single, more complex core structure. CPU is like the ‘brain’ of the computer. It handles all the basic tasks of computer work, such as running programmes, managing files and performing basic calculations.
Think of it as a human brain, making sure that all your faculties and behaviours are in order. Different types of CPUs may have different instruction set architectures (e.g. x86, ARM, etc.) for different application scenarios, such as personal computers, servers, embedded systems, and so on.
What does a CPU actually do?
At its core, a CPU takes instructions from a programme or application and performs calculations. There are three key stages in this process: fetch, decode and execute. In the fetch phase, the CPU reads instructions from memory. In the decode phase, the instruction is decoded to determine the operation to be performed. The execution phase performs the actual computation or operation according to the decoding result. The write back stage writes the result of the execution back to memory or registers.
What is a GPU?
Originally designed to handle graphics and image-related computations, Graphics Processing Units (GPUs) have been gradually expanding their applications as fields such as scientific computing and deep learning have evolved.
Unlike the serial processing of traditional CPUs, GPUs have thousands of highly parallel cores that are able to break down complex computational tasks into countless smaller tasks that are processed simultaneously. This highly parallel architecture allows GPUs to excel in scenarios that require large amounts of computation for tasks such as graphics rendering, machine learning (ML), video editing, gaming applications, and computer vision.
GPU Application Scenarios
Professional Visualisation
GPUs not only play a role in entertainment, but also excel in professional applications. For example, GPUs provide the computational power to process and render complex graphics in CAD drafting, video editing, product demonstration and interaction, medical imaging, and seismic imaging. These applications often require the processing of large amounts of data and complex image processing tasks, and the parallel processing power of GPUs makes them ideal for these tasks.
Machine Learning
Training complex machine learning models often requires a significant amount of computational power, and GPUs, with their parallel processing architecture, can significantly accelerate this process. For those training models on local hardware, this can take days or even weeks, whereas with cloud-based GPU resources, model training can be completed in a matter of hours.
Simulation
GPUs are used in a wide range of high-end simulations. Simulations in areas such as molecular dynamics, weather forecasting, and astrophysics all use GPUs to perform complex calculations, and GPUs are able to rapidly process and simulate large-scale physical systems. Additionally, in the design of automobiles and large vehicles, applications involving complex simulations such as fluid dynamics also rely on the powerful computing capabilities of GPUs for accurate modelling and simulation, helping engineers to optimise designs and reduce the need for physical testing.
What is a DPU?
The DPU, or Data Processing Unit, is a major key component in the future of computing. It is a hardware unit specifically designed to process data, with a greater focus on efficiently performing specific types of computing tasks. DPUs can share the work of the CPU in four ways: networking, storage, virtualisation and security.
Typically, DPUs are integrated into SmartNICs (Smart NICs) as a third computing unit in addition to CPUs and GPUs, which builds the heterogeneous computing architecture of the data centre.
Application Areas for DPUs
DPUs are an important part of the future of computing, and their applications cover a wide range of areas, from deep learning to edge computing and cryptographic security.
Deep Learning
Deep Learning is one of the important application areas of DPU. DPU, as a hardware unit specially designed for data processing, has excellent parallel computing capabilities and efficient data processing capabilities. DPU achieves fast training and inference of deep learning models through hardware accelerators, which greatly improves the efficiency of deep learning tasks. In fields such as natural language processing and computer vision, DPU achieves faster and more accurate text analysis, image recognition and other tasks by accelerating the training and inference process of models.
Edge Computing
Edge computing is another important application area for DPUs. As specialised data processing units, DPUs can perform complex computing tasks on edge devices to meet the needs of edge computing. In industrial automation, intelligent transportation, healthcare and other fields, DPUs can monitor and analyse real-time data, help users perform predictive maintenance, intelligent scheduling and other tasks, and improve the efficiency and reliability of the system.
Encryption and Security
With the increasing importance of data security and privacy protection, encryption and security have become important issues in the computing field. DPU can achieve efficient encryption and security processing to protect the security of user data. In the field of network security and intrusion detection, DPU can achieve real-time data monitoring and analysis to help users find and respond to network attacks and security threats promptly, to ensure the security and stability of the system.
The rapid growth of global arithmetic demand has driven the development of DPUs.NVIDIA, as a pioneer in the DPU field, has launched the BlueField series of DPUs and predicted that the DPU market will see explosive growth.FS, as one of NVIDIA’s partners, provides NVIDIA’s series of smart NICs, covering the ConnectX®4-ConnectX®7 series, and provides RIVERMAX licenses service.
Difference between CPU, GPU and DPU
Functionally, the main difference between the three lies in application scenarios and processing tasks. CPU is widely used for various computing tasks, while GPU is mainly used for graphics computing, and DPU is mainly used for data transmission data processing in data centres.
In terms of architecture, GPUs have more cores and processors than CPUs, and have higher parallel processing capabilities, while DPUs not only have the ability to transmit data but also can manage infrastructure, which enables them to work better together.
Of course, the DPU is not to replace the CPU and GPU, but the three divisions of labour. Among them, CPU is responsible for the definition of the entire IT ecosystem and processing general-purpose computing tasks, GPU is responsible for data-parallel tasks such as graphic images, deep learning, matrix operations and other accelerated computing tasks, and DPU takes on the accelerated processing of other specialised services such as security, networking, and storage.
Conclusion
DPUs have become an important part of computing, alongside central processing units (CPUs) and graphics processing units (GPUs). By integrating DPUs into devices such as Smart NICs, more efficient data transfer and processing can be achieved while reducing the burden on the CPU and GPU, increasing overall system throughput and responsiveness.
FS NIC products include Intel, Broadcom and NVIDIA brands, with a wide range of categories to choose from, fully stocked for fast delivery. FS always strives to provide competitive pricing, while being able to ensure product quality and service levels. Visit the FS website for more product information.
In the wave of digital transformation, the importance of network connectivity as the blood vessel for data flow cannot be overstated. The continuous development of network technology and hardware devices has changed the landscape of data centres and cloud computing. Traditional NICs have struggled to meet the growing bandwidth demands, security challenges, and the need for intelligent management. As a result, smart NICs have emerged. This article will delve into the features, types, and differences of smart NICs and how to choose the right option for a given use case.
What is Smart NIC?
Smart NIC, is a network interface card with integrated intelligent processing capabilities. Not only does it have the data transmission capabilities of a traditional NIC, but it also has a built-in high-performance processor (e.g., FPGA, ASIC, or smart chip) and a dedicated acceleration engine that is capable of performing complex data processing tasks such as data encryption, network protocol offloading, and traffic management. This design enables smart NICs to significantly improve network performance and security without increasing the CPU burden.
Functions
Packet filtering and load balancing.
Quality of Service (QoS) implementation.
Storage acceleration, including Remote Direct Memory Access (RDMA), iSCSI, and NVMe over Fabrics.
Security features such as firewall processing and Intrusion Detection System (IDS) checks.
Types
There is no fixed way to classify smart NICs, and they can be divided into the following types according to the form adopted for the design of smart NICs:
FPGA-Based Smart NICs:
FPGA (Field Programmable Gate Array) based Smart NICs are highly customisable and programmable. They provide low-latency processing by offloading network tasks, such as packet inspection, encryption, or compression, directly onto the NIC. This flexibility makes FPGA-based intelligent NICs ideal for specific, specialised workloads such as financial trading systems where speed and low latency are critical. They support real-time updates to adapt to changing network requirements without requiring hardware changes. Example: Xilinx Alveo SmartNIC.
ASIC-Based Smart NICs:
ASIC (Application Specific Integrated Circuits) based SmartNICs are designed for specific tasks and provide high performance and efficiency. These smart NICs are typically used for fixed-function tasks such as offloading TCP/IP processing, RDMA (Remote Direct Memory Access), or VXLAN encapsulation/decapsulation. ASIC-based smart NICs offer low power consumption and high throughput, making them ideal for cloud environments and hyperscale data centres. Example: Mellanox (NVIDIA) BlueField-2 Smart NIC.
SoC (System-on-Chip) Based Smart NICs:
These smart NICs integrate multiple processing units (CPUs, GPUs or other accelerators) on a single chip, enabling them to handle complex networking and security functions independently. SoC-based smart NICs are suitable for workloads that require both computing power and networking, such as security functions like firewalls, DDoS protection and encryption. They enable tasks such as deep packet inspection, network virtualisation and telemetry to be handled directly on the NIC. Example: Intel Ethernet 800 Series with Dynamic Device Personalization (DDP).
ARM-Based Intelligent NICs:
ARM-based intelligent NICs integrate ARM processors on the NIC itself to handle compute and network tasks. These processors offload workloads from the host server CPU, reducing CPU overhead and increasing system efficiency. They are widely used in virtualised, containerised and cloud-native environments where network traffic processing can be offloaded to the NIC. example: Marvell ARMADA-based NIC.
FS, as an NVIDIA partner, can provide NVIDIA Ethernet NICs, which are rigorously tested and certified to ensure full compatibility with a wide range of operating systems and hypervisors. In addition, FS offers a complete end-to-end solution supporting InfiniBand and Ethernet networking technologies, providing organisations with the infrastructure needed to support the development deployment implementation and storage requirements of the accelerated computing era.
Application Scenarios
High Performance Computing (HPC): Offload tasks to improve supercomputing performance.
Financial Services: Improve latency for time-sensitive applications such as stock trading.
Telecommunications: Optimising virtual network functions (VNFs) in telecoms networks.
Cloud & Data Centre: In the cloud and data centre space, smart NICs can significantly improve server network performance and security, reduce latency and packet loss, and improve overall quality of service and user experience.
Edge Computing: In edge computing scenarios, smart NICs can support low-latency and high-bandwidth data transmission requirements, while providing strong security protection capabilities to ensure data security and privacy protection for edge devices.
Internet of Things and Smart Cities: In the field of Internet of Things and Smart Cities, smart NICs can connect a variety of smart devices and sensors to achieve rapid data transmission and intelligent processing, providing strong support for city management and services.
Why is a Smart NIC better than a standard NIC?
Smart NICs reduce the burden on host server CPUs for routing, network address translation, telemetry, load balancing, firewalls, and more. It can block DDoS attacks and can be used to manage hard discs/solid-state drives in a similar way to a storage controller. In addition, SmartNICs are great solutions for offloading the data plane. Smart NICs may take on handling tunnelling protocols (e.g. VxLAN) and complex virtual switching. Its ultimate goal is to consume fewer host CPU processor cores while providing a higher-performance solution at a lower cost.
While standard NIC functionality is sufficient to support common network connectivity needs, it falls short when faced with data-intensive applications, virtualised environments, cloud computing and high-performance computing that demand higher performance and functionality.
Of course, there are times when we need to choose between a standard Network NIC and a smart NIC. At this critical juncture, FS offers a range of Intel-based Ethernet adapters to provide our customers with a cost-effective solution. Whether you choose one of our advanced NICs or select a Smart NIC, FS is ready to meet your networking needs and ensure that your network operates in an optimal, secure and efficient manner.
In August, FS introduced its latest portfolio of highly scalable, high-performance original Broadcom® Ethernet adapters. Included are seven Broadcom® NICs supporting a full range of speeds and feeds from 10G to 400G in a standard half-height, half-length form factor, providing enhanced, open, standards-based Ethernet NICs to address connectivity bottlenecks that occur as data centre bandwidth and cluster sizes grow rapidly.
How to choose Smart NICs?
In the ever-evolving world of networking, choosing the right NIC is critical and will have a direct impact on the performance, security and operation of your network and applications. Different use cases and requirements will determine the best choice for you.
Uses
Different workloads benefit from specific smart card features. For example, high-performance computing (HPC), financial trading, AI workloads, or video streaming may require a low-latency, high-throughput NIC with dedicated offload capabilities. Also, if you are managing a virtualised environment, make sure the smart card supports technologies such as SR-IOV (Single Root I/O Virtualization) and OVS (Open vSwitch) offload. These technologies help virtualise the network and reduce CPU overhead.
Speed and Bandwidth
Evaluate your current network speed requirements (10G, 25G, 40G, 100G or even 400G). For data-intensive environments, such as cloud data centres or AI workloads, high-speed smart NICs such as 100G or 400G may be required. Consider choosing higher-speed smart NICs or modular NICs that can be upgraded as your network expands to be future-proof.
Software and Compatibility
Ensure that the smart NIC supports the operating systems in your infrastructure, such as Linux, Windows, or FreeBSD. Choose a smart NIC that integrates with your existing network architecture. For example, if you are using a specific switch vendor, make sure the smart card is compatible with the vendor’s network management tools. In addition, some smart cards come with software development kits (SDKs) or APIs for customisation. If programmability is a priority, make sure the vendor provides good support for custom applications.
Power Consumption
High-performance smart NICs can consume a lot of power. For large-scale deployments, consider the power-to-performance ratio. ASIC-based NICs are typically more energy efficient, while FPGA-based NICs offer flexibility but may consume more power.
Security
If your organisation uses a zero-trust network model, choose a smart card that supports hardware-based security features such as encryption, IPsec offload, and trusted boot mechanisms. Some smart cards also offer real-time telemetry and analytics, enabling you to monitor network traffic, detect anomalies, and quickly respond to potential security threats.
Cost
The cost of smart NICs can vary widely depending on their features and capabilities. ASIC-based cards tend to be more affordable, while FPGA-based cards can be more expensive due to their customizability. Evaluate cost savings in terms of CPU offloading, power efficiency, and performance enhancements. While smart NICs may have higher upfront costs, they can reduce overall infrastructure costs by offloading critical network functions.
Latency and Throughput
Latency is a key factor in applications such as financial trading or HPC. Look for smart NICs that support low-latency packet processing and accelerated I/O to optimise real-time performance. Choosing smart NICs with high throughput capabilities ensures they can handle the expected amount of data without bottlenecks.
Conclusion
As a new chapter in the future of network connectivity, smart NICs are leading the innovation and development of network technology with their excellent performance, strong security capabilities and intelligent management features. In the future, smart NICs will also open up a wider range of application scenarios and market opportunities. In short, the emergence and application of smart NICs will bring more opportunities and challenges to the digital society and intelligent future.
With the deepening of the digital era, Cloud Computing and Edge Computing, as the two hotspots in the current technology field, have changed the traditional mode of data storage and processing in different ways, and together they have shaped a more efficient and intelligent informationized world.
This article will delve into the differences between cloud computing and edge computing to help you gain a deeper understanding of these two concepts.
What is Cloud Computing
Cloud computing is a kind of distributed computing, which refers to the decomposition of huge data calculation and processing procedures into countless small procedures through the network “cloud”, and then processing and analyzing these small procedures through the system composed of multiple servers, and then returning the results to the users.
The core concept of cloud computing is to centralize computing power into large data centres and achieve flexible resource allocation and management through virtualization technology.
Characteristics
Virtualization technology: Cloud computing achieves abstraction of hardware resources through virtualization technology, allowing users to use computing resources more flexibly without caring about the underlying hardware details.
Elasticity and scalability: Users are allowed to rapidly expand or reduce computing resources according to their needs, realizing the elastic use of resources and avoiding the waste of resources.
On-demand services: Users can purchase and use various services provided by cloud computing according to their needs, without investing large amounts of money in advance to build their computing infrastructure.
Easy integration and standardization: Support for multiple standards and protocols facilitates the development of cross-platform applications.
What is Edge Computing
Edge computing emphasises data processing and storage at or near the source of data generation. In an ideal environment, edge computing refers to analysing and processing data near the source of data generation without data flow, reducing network traffic and response time.
Features
Low Latency: Edge computing processes data at the source of data generation, reducing the distance and lowering the latency of data transmission, enabling applications to respond faster to user requests.
Enhanced data security: Data is processed locally, reducing the need for transmission to the cloud, thereby reducing the risk of potential data leakage.
Network and storage efficiency: Edge computing occurs at the edge layer, halfway between the cloud and device layers, with the obvious benefit of being closer to the user, reducing bandwidth and storage demands on the central data centre.
Cloud Computing VS. Edge Computing
Edge computing and cloud computing are closely related in many ways. Edge computing is usually based on cloud computing, where computing and storage resources are deployed at the edge of the network to improve computing efficiency and user experience. Cloud computing is usually based on edge computing, where computing and storage resources are centrally managed to improve computing efficiency and reduce costs. In the future, edge computing and cloud computing will converge with each other and jointly drive the development of the computing field.
Differences Between Cloud Computing and Edge Computing
Data Processing Location
Cloud computing emphasizes the centralized processing of data in a central data centre, which is accessed by users via the Internet so that they can use the services provided by the cloud. In contrast, edge computing pushes data processing to edge devices closer to the data source, such as IoT devices, edge servers, etc., for lower latency and more efficient data processing.
Latency and Response Time
Cloud computing typically involves transmitting data to a remote data centre for processing, so there can be high latency during data transmission and processing. In contrast, edge computing pushes data processing closer to the data source, enabling faster response times in scenarios where real-time requirements are high.
Availability and Stability
Cloud computing delivers services through large data centres with powerful computing and storage capabilities, but in some cases can be affected by network failures or data centre failures. Edge computing, on the other hand, provides services through computing resources distributed on edge devices, which can operate independently in some cases.
Application Scenarios
Cloud computing is more suitable for scenarios that require large-scale computing and storage, such as big data analysis and machine intelligence training. Edge computing is more suitable for scenarios that require high real-time and low latency, such as IoT, autonomous driving, and industrial automation.
FS, a leading solution provider, has launched a next-generation network solution for autonomous driving, based on PicOS® switches and AmpCon™ management platform, which delivers real-time processing to enable self-driving cars to drive in a variety of environments. FS provides a range of customized hardware, easy-to-deploy application and management software, and end-to-end services for the solution. With these, organizations can instantly respond to customer needs, run their networks with maximum efficiency and security, and bring innovation in the field of autonomous driving.
Synergistic Applications
Cloud and edge computing are not mutually exclusive but can work together to take full advantage of their respective strengths. By distributing data processing between edge devices and cloud data centres, a more flexible and efficient computing architecture can be achieved. Here are some use cases:
In a smart factory, sensors and devices collect and analyze production data in real-time through edge computing to improve productivity. Meanwhile, cloud computing can be used for centralized management of global data, long-term analysis and optimization.
In healthcare, edge computing can monitor patient vital signs in real-time and provide rapid emergency treatment. Cloud computing, on the other hand, can be used to store and analyze large-scale medical data to support medical research and precision medicine.
In intelligent transportation systems, edge devices such as traffic cameras and sensors can monitor traffic conditions in real-time and respond quickly. Cloud computing can then analyze historical traffic data to optimize traffic flow and improve urban traffic efficiency.
In smart city and smart home scenarios, edge computing can be used for real-time interaction and data processing, while cloud computing can be used for data storage and analysis.
In virtual reality and augmented reality scenarios, edge computing can be used for real-time rendering and interaction, while cloud computing can be used to store and process large-scale virtual reality data.
Conclusion
To summarize, cloud computing focuses on the “cloud”, while edge computing focuses on the “end”. Specifically, edge computing is the processing of data, the operation of applications, and even the realization of some functional services from the central server to the nodes on the edge of the network.
Cloud computing is an orchestrator, responsible for big data analysis of long-period data, and able to operate in areas such as cyclical maintenance and business decision-making.
However, with the development of the digital era, they are also gradually forming a trend of synergistic applications, giving full play to their respective advantages and providing a more flexible and efficient computing architecture.
Immediately enter the FS website to learn more knowledge content, a large number of products for you to choose from, and technicians are ready to answer your questions.
Whether for governments, businesses, or consumers, we all use various clouds almost daily. Cloud computing is now a key part of modern IT systems. Cloud service models are important for creating and providing cloud services. Four main types of cloud computing include private cloud, public cloud, hybrid cloud, and multi-cloud.
Cloud computing has three main service models. They are Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These are the main cloud computing service models today. This article will delve into these three models, exploring their features, advantages, and suitability for different scenarios.
Cloud Computing Deployment Models
Cloud computing is a new computing model based on the internet. It integrates technologies such as distributed computing, parallel computing, network storage, virtualisation, and load balancing.
It uses many distributed computers instead of local or remote servers. This provides computing resources and services that are scalable, reliable, flexible, and secure. These resources are available when needed.
Cloud Computing Deployment Models describe the configuration methods for cloud computing resources and services, explaining how different environments deploy cloud infrastructure. These models help organisations decide how to deploy and manage their computing resources across various cloud environments. The main cloud computing deployment models include:
Public Cloud
Cloud-based applications are entirely deployed in the cloud, with all components running in the cloud. Two types of cloud-based applications exist. Some developers create them in the cloud, while others migrate existing systems to the cloud. This helps them take advantage of cloud benefits.
Developers can build cloud-based applications using basic infrastructure components. They can also use higher-level services. These services simplify the core infrastructure’s management, design, and scaling.
Hybrid Cloud
Hybrid deployment connects infrastructure and applications between cloud-based resources and existing non-cloud resources. The most common hybrid deployment method adds a cloud layer to an organization’s infrastructure. It connects cloud resources with internal systems.
Private Cloud
Deploying resources locally using virtualisation and resource management tools is often called a “private cloud.” While local deployment cannot offer many cloud computing advantages, this approach sometimes provides dedicated resources. In most cases, this deployment model is similar to traditional IT infrastructure, with application management and virtualisation technologies used to maximise resource utilisation.
Multi-Cloud
Multi-cloud refers to a cloud architecture that integrates multiple cloud services. Various cloud providers supply these services. They can either be public clouds or private clouds, depending on the specific use case.
Every hybrid cloud is a multi-cloud, yet not every multi-cloud is a hybrid. When various clouds link through some form of integration or orchestration, a multi-cloud transforms into a hybrid cloud.
You can plan a multi-cloud environment for better control over sensitive data. It can also serve as extra storage to improve disaster recovery. Sometimes, it happens by accident because of shadow IT. This shows that more companies are using multi-cloud to boost security and performance by reaching more environments.
Cloud Computing Service Models
Cloud computing models, or service models, currently fall into three main categories: IaaS, PaaS, and SaaS. Each model represents a distinct part of the cloud computing stack.
IaaS (Infrastructure as a Service)
IaaS provides a cloud computing model that offers infrastructure resources (such as servers, storage, and networking) to users via virtualisation technology. In the IaaS model, users can rent virtualised infrastructure resources to build their applications, store data, and run services.
Features and Advantages:
Flexibility and Scalability: IaaS offers flexible infrastructure resources that users can scale up or down based on demand. This allows users to quickly respond to changing business needs.
Centralised Resource Management: IaaS centralises the management of infrastructure resources, including hardware devices, networking equipment, and virtualisation software. This allows users to focus more on application development and business innovation without worrying about infrastructure maintenance.
Flexible Payment Models: IaaS usually uses a pay-as-you-go model. Users pay only for the resources they use. This helps them avoid unnecessary expenses. This flexible payment model makes cost management more precise and controllable.
Applications:
Development and Testing Environments: IaaS provides development teams with flexible, scalable infrastructure resources to quickly set up and deploy development and testing environments.
High-Performance Computing is important for tasks that require a lot of computing power. This includes scientific calculations and data analysis. IaaS offers powerful computing and storage resources for these tasks.
Disaster Recovery and Business Continuity: By renting IaaS resources, organisations can create disaster recovery solutions to ensure business continuity and availability.
PaaS (Platform as a Service)
PaaS offers a complete platform environment needed for developing and running applications. In the PaaS model, cloud service providers handle hardware, operating systems, databases, and development tools. This lets developers focus only on building and deploying applications.
Features and Advantages:
Simplified Development Process: PaaS provides the necessary platform, including the operating system, databases, development tools, and runtime environment. Developers can focus on application development without managing the underlying infrastructure.
Rapid Deployment and Scaling: PaaS offers automated application deployment and scaling mechanisms, allowing developers to deploy and scale applications quickly. This speeds up delivery and enables rapid response to business needs.
Multi-Tenant Architecture: PaaS typically employs a multi-tenant architecture where multiple users share the same platform environment, improving resource utilisation. The system isolates users from each other to ensure security and stability.
Applications:
Web Application Development: PaaS provides comprehensive frameworks, tools, and services for quickly building and deploying web applications.
Mobile Application Development: PaaS supports mobile application development with appropriate tools and platform environments for building, testing, and publishing mobile apps.
Data Analysis and Big Data Processing: PaaS provides strong computing and storage resources for data analysis. It helps users manage and analyze large datasets effectively.
SaaS (Software as a Service)
SaaS delivers software applications to end-users via a cloud platform. In the SaaS model, users subscribe to applications from cloud service providers. They do not need to buy or install software.
Features and Advantages:
Zero Deployment and Maintenance Costs: In the SaaS model, users do not need to buy, install, or maintain software. They just subscribe and use it through the cloud platform. This lowers deployment and maintenance costs. It also makes things easier for IT teams.
Flexible Subscription Models: SaaS typically employs a subscription-based model, allowing users to choose plans based on actual needs. Users can adjust subscriptions as business requirements change, avoiding resource wastage.
Fast Upgrades and Updates: SaaS enables quick and easy software upgrades and updates. Cloud service providers can update software in the background. This lets users access the latest features and fixes automatically.
Applications:
Office Collaboration and Communication: SaaS is widely used in office collaboration and communication tools, such as online document editing, email services, and video conferencing.
Customer Relationship Management (CRM): SaaS providers of CRM software help businesses manage customer relationships, sales processes, and marketing activities.
Human Resources Management: SaaS offers HR management software, including functions for recruitment, training, and performance evaluation, simplifying HR processes for businesses.
Cloud Computing in the New Era
The smart industry has grown rapidly in recent years. It has unlocked the competitive power of digital and intelligent systems. These systems use cloud computing as the main hub. As the foundational computing power for large models, cloud computing has entered a new stage of development.
Traditional general-purpose cloud computing is rapidly merging with intelligent computing, evolving into an intelligent cloud. The intelligent cloud can support many chip types and open-source frameworks. It does this by combining and scheduling large computing resources. This enhances the efficiency of computing resource utilisation and ensures that various model algorithms can run efficiently and conveniently on the intelligent cloud platform.
The application of computing power models has driven the development of high-speed networks. FS has introduced high-speed modules and switch devices such as 400G and 800G, helping to enhance network performance.
FS has launched the H100 Infiniband solution. This solution relies on FS network architecture. It works with PicOS® and the AmpCon™ management platform.
Together, they improve high-performance computing networks. They also lower the overall network construction costs for users.
Conclusion
Each model has unique features and advantages, making it suitable for different application scenarios. Choosing the right cloud service model depends on business needs, resource requirements, and technical capabilities. Depending on the specific situation, a single model or a combination of multiple models can meet various demands. Cloud service models offer flexible, scalable, and cost-effective solutions, driving the development and adoption of cloud computing.
FS offers a variety of network equipment and custom solutions for users. Visit the FS website to enjoy free technology support.
In the digital age, servers are the core foundation supporting the internet and various technological applications. Whether browsing the web, sending emails, or watching online videos, a vast and complex server system operates behind the scenes. Despite enjoying digital conveniences, few people have an in-depth understanding of server hardware. This article will take you into the mysterious world of servers, exploring how they are composed of various hardware components.
Server Basics: Understanding the Core Components and Concepts
A server, a term we frequently encounter in daily life, is essentially the central nervous system of the internet. It operates tirelessly, ensuring our digital activities run smoothly. A server is a high-performance computer with a fast CPU, reliable long-term operation, and powerful external data throughput. Compared to ordinary computers, servers have significant advantages in processing power, stability, reliability, security, scalability, and manageability. They are the unsung heroes supporting our digital lives, not just the core of data processing.The hardware makeup of a server involves several critical components, including the central processing unit (CPU), memory (RAM), storage devices (hard drives and solid-state drives), motherboard, power supply unit, and network interface cards. These components work together to provide robust computing and storage capabilities.
Central Processing Unit (CPU)
The CPU is the brain of the server, responsible for executing computational tasks and processing data. The primary difference between server processors and ordinary desktop processors lies in their design focus; server processors emphasise multi-core performance and high parallel processing capabilities. The CPU’s performance directly impacts the server’s overall computational power and response speed. Common CPU brands in servers include Intel and AMD (Advanced Micro Devices). Multi-core processors are widely used in servers as they can handle multiple tasks simultaneously, enhancing concurrency and efficiency.
Core Count: Server CPUs typically have multiple cores, ranging from 4 to 64 or more.
Hyper-Threading Technology: Technologies like Intel’s Hyper-Threading allow a single core to handle two threads simultaneously, further improving efficiency.
Random-Access Memory (RAM)
Random-Access Memory is where a server temporarily stores data and programs. When applications running on the server need to read or write data, it is temporarily loaded into Random-Access Memory for faster access and processing. The size and speed of memory are crucial to the server’s performance. High-capacity and high-speed Random-Access Memory helps avoid memory bottlenecks and improves the server’s operational efficiency.
Type: Servers typically use ECC (Error-Correcting Code) memory, which can detect and correct common types of data corruption, ensuring data accuracy and system stability.
Capacity: Server memory capacity usually ranges from tens of gigabytes to several terabytes, depending on the server’s purpose and workload requirements.
Storage Devices
Servers are usually equipped with various storage devices, including hard disk drives (HDD) and solid-state drives (SSD). HDDs are traditional storage devices that offer large storage capacities at lower prices. SSDs, on the other hand, are favoured for their high-speed read/write capabilities and lower access times, particularly in scenarios requiring rapid data retrieval. Server administrators typically select the appropriate storage configuration based on needs and budget. The choice of storage devices directly impacts data access speed and capacity.
Hard Disk Drives (HDD): Provide large storage space at a lower cost, suitable for storing large volumes of data.
Solid-State Drives (SSD): Offer fast speeds, short response times, and high durability, ideal for caching and frequently accessed data.
NVMe SSDs: Use high-speed PCIe channels and are faster than regular SSDs, suitable for extremely high-speed data processing needs.
Motherboard
The motherboard is the core of the server hardware, connecting all hardware components and facilitating communication and data transfer. It contains CPU sockets, memory slots, expansion slots, and various input/output (I/O) interfaces. The quality and design of the motherboard are crucial to the server’s stability and reliability.
Chipset: The chipset on the motherboard determines the types of CPUs and memory it supports, their maximum capacity, and the types and numbers of expansion slots available.
Expansion Slots: PCIe expansion slots are used to install additional network cards, storage controllers, or specialised processors like GPUs.
Power Supply Unit (PSU)
The power supply unit provides the necessary power for the server. Given that servers typically need to run continuously, the stability and efficiency of the PSU are critical for maintaining server reliability and reducing energy consumption.
Power: The power rating of the PSU needs to match the total power requirements of all installed hardware, usually with some extra capacity for safety.
Redundancy: High-end servers often feature redundant power supplies, allowing the system to continue running even if one PSU fails.
Network Interface Card (NIC)
The server communicates with other devices and networks through the network interface card. These NICs can be Ethernet cards, fibre channel cards, or other types, depending on the server’s connectivity needs and network architecture.
Speed: Modern server NIC speeds range from 1Gbps to 100Gbps, with 200G and 400G NICs now emerging.
Port Quantity: Multiple network ports can provide network load balancing or redundant connections, enhancing reliability.
The Evolution of Server Hardware: From Basics to Innovations
Server hardware has undergone significant evolution and innovation over the years. With continuous technological advancements, server hardware has become more powerful, efficient, and reliable. Here are the main trends in the evolution of server hardware:
Multi-Core Processors
As computer science has progressed, CPUs have evolved from single-core to multi-core. Multi-core processors allow multiple threads and tasks to be executed simultaneously, significantly enhancing the server’s concurrency performance. Multi-core server processors have become standard in modern servers.
Virtualisation Technology
Virtualisation technology enables a single physical server to run multiple virtual servers simultaneously, thereby utilising server resources more efficiently. This technology helps reduce hardware costs, save energy, and simplify server management and maintenance.
Proliferation of Solid-State Drives (SSDs)
With the decreasing cost and increasing capacity of SSDs, their use in servers has become widespread. Compared to traditional mechanical hard drives, SSDs offer faster read and write speeds and lower power consumption, significantly boosting server performance and energy efficiency.
High-Performance Computing (HPC) and GPU Acceleration
The advent of high-performance computing and graphics processing units (GPUs) allows servers to process complex scientific calculations and graphic rendering tasks more rapidly. This plays a crucial role in scientific research, artificial intelligence, and deep learning.
The Future of Server Technology: What’s Next?
Exploring the hardware composition of servers reveals the extensive and coordinated efforts of a dedicated tech team. From processors to storage devices, from memory to network interfaces, each hardware component plays a crucial role in delivering efficient, stable, and secure internet services. In this digital age, server hardware is constantly evolving to meet the growing demands of the internet and technology.
The use of multi-core processors, high-capacity memory, high-speed SSDs, and GPU acceleration equips servers with enhanced computing and storage capabilities, enabling them to handle more complex tasks and vast amounts of data.
With the widespread adoption of virtualisation technology, a single server can run multiple virtual servers, improving resource utilisation and flexibility. Virtualisation also simplifies server management. Through virtual machine management software, administrators can easily create, deploy, and migrate virtual servers, achieving dynamic resource allocation and load balancing.
Additionally, server energy efficiency is becoming increasingly important. Server power consumption significantly impacts data centre and enterprise operating costs. To reduce energy consumption, some servers incorporate energy-saving designs such as intelligent power management, thermal management technologies, and low-power components.
Besides common server hardware components, some specialised servers may feature customised hardware. For instance, database servers might be equipped with dedicated high-speed storage devices for handling extensive database operations, while video encoding servers might be fitted with high-performance GPUs to accelerate video encoding and decoding.
In the future, with continuous technological advancements, server hardware will continue to evolve and innovate. With the ongoing development of cloud computing, the Internet of Things (IoT), and artificial intelligence, servers will require higher performance, larger storage capacities, and greater energy efficiency. Consequently, hardware manufacturers and tech companies will continue to invest heavily in developing new server hardware technologies to meet the growing demands.
Conclusion
In summary, the hardware composition of servers is a complex and diverse field that spans various disciplines within computer science, engineering, and electronics. Understanding server hardware is crucial for comprehending the technological infrastructure and internet services of the digital age. Through ongoing research and innovation, we can expect future servers to continue playing a vital role in driving technological progress and societal development.
How FS Can Help
As a provider of network solutions, FS offers a wide range of servers and can also customise servers to meet specific user needs. Our expert team can design tailored solutions for building cost-effective and high-quality data centres. Visit the FS website now to learn more about our products and solutions, and our professional technicians are always available to answer any questions you may have.
In today’s era of global digital transformation, emerging technologies such as cloud computing, the Internet of Things (IoT), and big data are undeniably at the forefront of driving digital transformation for businesses. However, the implementation and application of these innovative technologies rely heavily on robust underlying computing support. As the cornerstone of computing, servers play an indispensable role in the digital transformation of enterprises. This article will introduce different types of servers from various perspectives to help you gain a deeper understanding of network servers.
Essential Functions of a Network Server
A network server is a computer system or device that provides services, stores, and shares resources with other devices or users connected to a network. They exist in both hardware and software forms and are responsible for receiving, processing, and responding to requests from other devices on the network. The functions of a network server include, but are not limited to:
Storage and Resource Sharing: Network servers can store data, files, applications, and other resources, sharing them with other devices or users over the network. These resources may include documents, images, videos, and databases.
Providing Services: Network servers can offer various services such as web hosting, email services, file transfer, database management, and remote access. These services enable users to perform various operations and communicate over the network.
Processing Requests: When other devices or users on the network send requests, the network server receives and processes these requests, providing the appropriate services or resources based on the type of request. This may involve data processing, computation, and storage operations.
Maintaining Security: Network servers are responsible for maintaining the security of the system and data. This includes access control, authentication, encrypted transmission, and other measures to ensure data confidentiality, integrity, and availability.
Managing Network Traffic: Network servers can manage and schedule network traffic, ensuring efficient data transmission across the network and optimising network performance to enhance the user experience.
Classification of Network Servers by Form Factor
Network servers can be categorised based on their physical form factor, including rack servers, GPU servers, tower servers, high-density servers, blade servers, and cabinet servers. Each type has unique characteristics and suitable application scenarios.
Rack Servers
Rack servers are designed to be installed in standard 19-inch racks. Typically, they are standalone, rectangular metal enclosures that fit into data centre racks or cabinets, occupying one or more rack units (U) in height. They are suited for various workloads, from network services to database applications.
Features:
Space-saving, easily installed in standardised server racks, promoting server consolidation and simplified cabling.
High scalability, suitable for server deployments of various sizes.
Focused on high-density computing capability, ideal for handling large-scale data and high-concurrency tasks.
Application Scenarios:
Data Centres: Widely used due to their high density and performance, supporting cloud computing, big data processing, and virtualisation.
Enterprise Computing: Suitable for medium to large enterprise environments, supporting business applications, databases, email servers, and file servers.
High-Performance Computing (HPC): Commonly used in HPC clusters, providing powerful computing capabilities and scalability for scientific research, engineering simulations, and financial analysis.
GPU Servers
GPU servers are based on GPUs for rapid, stable, and flexible computing services in scenarios like video encoding/decoding, deep learning, and scientific computing. They are equipped with one or more graphics processing units (GPUs) to handle compute-intensive tasks, benefiting from GPU parallel processing capabilities.
Features:
High performance, suitable for compute-intensive tasks and scientific computing.
Excellent computing performance through GPU parallel processing.
Ideal for fields requiring large-scale parallel computation, such as deep learning and graphics rendering.
Application Scenarios:
Massive Data Processing: GPU servers can perform extensive data computations quickly, such as search, big data recommendations, and intelligent input methods, significantly reducing the time required for tasks.
Deep Learning Models: Serve as platforms for deep learning training, providing accelerated computing services and cloud storage integration for large datasets.
Tower Servers
Tower servers resemble traditional desktop computers with larger chassis to accommodate multiple hard drives, expansion cards, and other hardware components. They typically feature high-performance processors, ECC memory, and RAID controllers to ensure data integrity and system stability. Tower servers also come with redundant power supplies and cooling systems to prevent downtime due to hardware failures.
Features:
Lower purchase and maintenance costs, ideal for small to medium-sized enterprises focusing on budget control.
Low space requirements, with independent active cooling solutions and low noise levels, are suitable for office environments.
High versatility and strong expansion capabilities with many slots and ample internal space for hardware redundancy.
Application Scenarios:
Small to Medium-Sized Enterprises: Meet certain computing needs without requiring large server clusters, offering flexibility in hardware configuration and easy placement in office environments.
Office Environments: Suitable for office use due to low noise levels and a design that fits well within the office setting.
High-Density Servers
High-density servers pack numerous processing cores or nodes into relatively small physical enclosures or rack spaces to maximise computing power while saving space and power consumption.
Features and Applications:
Maximise processing capability with minimal physical space and power consumption.
Suitable for data centres and large-scale server deployments.
Highly efficient with excellent resource utilisation, ideal for large-scale data centres, cloud computing infrastructure, and supercomputers.
Blade Servers
Blade servers are compact servers designed to minimise physical space and energy consumption. Unlike traditional rack servers, blade servers integrate multiple server modules into a single chassis, each module acting as an independent server.
Features:
High Server Density: Known for high server density, optimising data centre space usage, and maximising computing power.
Reduced Power and Cooling Requirements: Designed for energy efficiency with shared resources, reducing operational costs and supporting greener data centres.
Simplified Management and Scalability: Centralised management interface for easy configuration, monitoring, and maintenance, with high scalability to adapt to changing workloads.
Cost-Effective and Lower Total Cost of Ownership (TCO): Despite higher initial investment, lower TCO due to reduced power consumption, simplified management, and space optimisation.
Optimised Network and Storage Connections: Integrated high-speed network and storage options like 10GbE for efficient cable management.
Flexible Blade Configuration: Allows configuration to meet specific workload needs, making it versatile for different applications.
Simplified Hardware Maintenance: Hot-swappable blade modules for hardware upgrades or replacements without downtime, enhancing system uptime.
Space Efficiency in Data Centres: Compact form factor optimises physical space, providing room for additional infrastructure or future expansion.
Application Scenarios:
Data Centres and Enterprise Environments: General computing workloads, virtualisation environments, private cloud infrastructure.
High-Performance Computing (HPC): Computationally intensive tasks in scientific research, engineering simulations, and financial analysis.
Edge Computing and IoT: Real-time data processing and analysis in edge computing and Industrial IoT scenarios.
Telecom Infrastructure: Supporting telecom infrastructure, network function virtualisation (NFV), and telco data centres.
Specialised Applications: Graphics and media processing, big data analytics, healthcare IT systems, educational and research institutions.
Public Cloud Infrastructure: Used by cloud service providers for scalable and efficient cloud computing services.
Cabinet Servers
Cabinet servers represent the core infrastructure of future data centres, integrating computing, networking, and storage into a unified system. They provide comprehensive solutions with software deployment for different applications.
Features and Application Scenarios:
Integrated Design: Simplifies deployment and management with an all-in-one approach.
Multi-Functionality: Supports automated deployment across various applications.
Ease of Management and Maintenance: Reduces operational costs with straightforward management.
Ideal for: Enterprise data centres, small to medium cloud service providers, and virtualisation environments.
Exploring the Diverse World of Server Types
In addition to the previously mentioned network servers categorised by form factor, there are other types of servers based on different classification criteria. This section provides a brief introduction to these types.
Network Servers by Application
File Servers
File servers specialise in storing and retrieving data files, making them accessible over a network. They act as central nodes for data storage and sharing, providing users with convenient file access services. File servers offer file storage and sharing capabilities, allowing users to access and manage files via the network.
Hardware configurations typically focus on storage capacity and data transfer speed, supporting multi-user access with robust security and permissions management. They are suitable for enterprise file sharing and collaboration, educational institutions’ teaching material sharing, and media file sharing in home networks.
Database Servers
Database servers are dedicated to managing and querying databases, offering simplified data access and operations for authorised users. They serve as central nodes for data storage and processing, supporting persistent storage and efficient data retrieval. Database servers are used to store and manage large volumes of structured data, supporting efficient data queries and operations. They provide database management system (DBMS) software such as MySQL, Oracle, and SQL Server, featuring high availability and fault tolerance to ensure data security and integrity.
Applications include internal data management and business applications for enterprises, product information and order management for e-commerce websites, and experimental data recording and analysis for scientific research institutions.
Application Servers
Application servers provide business logic for a range of programs, facilitating data access and processing over a network. They act as intermediaries between applications and users, handling user requests and interacting with database servers. Application servers offer an execution environment for applications, supporting various programming languages and frameworks. They handle user requests, execute business logic, and perform data processing operations.
Typically integrated with web servers, they provide services through APIs or web service interfaces. Suitable for internal business application systems such as Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP), as well as internet applications like social media, email services, and online shopping.
Network Servers by Processor Count
Single-Processor Servers
Single-processor servers are equipped with one processor, suitable for small-scale and small-to-medium applications, such as small business networks and personal website hosting. They have limited processing capacity but are cost-effective for budget-conscious scenarios.
Dual-Processor Servers
Dual-processor servers feature two processors, offering higher processing power and performance, making them a common choice in commercial environments. They support greater processing capacity and larger workloads, suitable for medium-sized enterprises, data centres, and other scenarios requiring higher performance.
Multi-Processor Servers
Multi-processor servers come with more than two processors, often four or more, providing superior processing power and performance. They are ideal for large-scale data processing and high-performance computing tasks, commonly used in large enterprises and scientific research institutions with high-performance requirements.
Network Servers by Instruction Set
CISC Servers (x86 Servers)
CISC servers are based on Complex Instruction Set Computer (CISC) architecture, with the x86 architecture being the most typical example. This architecture has a long history and is characterised by a complex instruction set capable of executing various types of operations, offering rich functionality. It boasts strong compatibility, supporting a wide range of software and operating systems, and is user-friendly, with relatively simple development and programming.
RISC Servers
RISC servers use Reduced Instruction Set Computer (RISC) architecture, focusing on improving the efficiency of executing common tasks, typically used in scenarios requiring high performance and low power consumption. They enhance execution efficiency for common operations, suitable for processing large-scale data and high-concurrency tasks.
VLIW Servers
VLIW servers utilise Very Long Instruction Word (VLIW) architecture, employing Explicitly Parallel Instruction Computing (EPIC) technology to achieve high levels of parallel processing. This improves computational efficiency and performance, offering better cost-effectiveness and power control compared to traditional architectures. VLIW servers are suitable for tasks requiring extensive parallel computation.
Finding the Ideal Server: Key Considerations and Tips
After understanding the various types of servers, the wide range of options can make it challenging for buyers to decide. This section outlines some principles or factors to help buyers choose the most suitable server.
Stability Principle
Stability is the most crucial aspect of a server. To ensure the normal operation of the network, it is essential to guarantee the stable running of the server. If the server fails to operate correctly, it can result in irreparable losses.
Specificity Principle
Different network services have varying requirements for server configurations. For instance, file servers, FTP servers, and video-on-demand servers require large memory, high-capacity, and high read-rate disks, as well as sufficient network bandwidth, but do not need high CPU clock speeds. Conversely, database servers require high-performance CPUs and large memory, preferably with a multi-CPU architecture, but do not have high demands for hard disk capacity.
Web servers also require large memory but do not need high disk capacity or CPU clock speeds. Therefore, users should choose server configurations based on the specific network applications they intend to use.
Miniaturisation Principle
Except for providing advanced network services that necessitate high-performance servers, it is advisable not to purchase high-performance servers just to host all services on a single server. Firstly, higher-performance servers are more expensive and offer lower cost-effectiveness. Secondly, despite a certain level of stability, if a server fails, it will disrupt all services. Thirdly, when multiple services experience high concurrent access, it can significantly affect response speed and even cause system crashes.
Therefore, it is recommended to configure different servers for different network services to distribute access pressure. Alternatively, purchasing several lower-spec servers and using load balancing or clustering can meet network service needs, saving on costs while greatly improving network stability.
Sufficiency Principle
Server configurations are continually improving, and prices are constantly decreasing. Therefore, it is essential to meet current service needs with a slightly forward-looking approach. When existing servers can no longer meet network demands, they can be repurposed for services with lower performance requirements (such as DNS or FTP servers), appropriately expanded, or used in a cluster to enhance performance. New servers can then be purchased for new network needs.
Rack Principle
When a network requires multiple servers, it is advisable to consider rack-mounted servers. Rack-mounted servers can be uniformly installed in standard cabinets, reducing space occupancy and eliminating the need for multiple monitors and keyboards. More importantly, they facilitate power management and clustering operations.
Conclusion
Choosing the right server architecture is a strategic decision tailored to specific needs. Each type of server has its advantages and disadvantages, depending on an organisation’s particular circumstances and goals. In practice, some organisations opt for a hybrid deployment, utilising different server architectures based on workload requirements. This hybrid model can maximise the strengths of various architectures, providing more flexible solutions. We hope this article helps readers gain a comprehensive understanding of different server types to better meet their business needs.
As a network solutions provider, FS offers a variety of products and custom solutions to help you build high-quality data centres. Visit the FS website to explore more products and solutions, and our professionals are available 24/7 to assist you.
The rise of virtualisation technology has revolutionised data centres, enabling the operation of multiple virtual machines on the same physical infrastructure. However, traditional data centre network designs are not well-suited to these new applications, necessitating a new approach to address these challenges. NVGRE and VXLAN were created to meet this need. This article delves into NVGRE and VXLAN, exploring their differences, similarities, and advantages in various scenarios.
Unleashing the Power of NVGRE Technology
NVGRE (Network Virtualization using Generic Routing Encapsulation) is a network virtualisation method designed to overcome the limitations of traditional VLANs in complex virtual environments.
How It Works
NVGRE encapsulates data packets by adding a Tenant Network Identifier (TNI) to the packet, transmitting it over existing IP networks, and then decapsulating and delivering it on the target host. This enables large-scale virtual networks to be more flexible and scalable on physical infrastructure.
1.Tenant Network Identifier (TNI)
NVGRE introduces a 24-bit TNI to identify different virtual networks or tenants. Each TNI corresponds to a separate virtual network, allowing multiple virtual networks to operate on the same physical infrastructure without interference.
2. Packet Encapsulation
Source MAC Address: The MAC address of the sending VM.
Destination MAC Address: The MAC address of the receiving VM.
TNI: The 24-bit virtual network identifier.
Original Ethernet Frame: Includes the source MAC address, destination MAC address, Ethernet protocol type (usually IPv4 or IPv6), etc.
Data packets are encapsulated into NVGRE packets for communication between VMs.
3. Transport Network
NVGRE packets are transmitted over existing IP networks, including physical or virtual networks. The IP header information is used for routing, while the TNI identifies the target virtual network.
4. Decapsulation
When NVGRE packets reach the host of the target VM, the host decapsulates them, extracting the original Ethernet frame and delivering it to the target VM.
5. MAC Address Table Maintenance
NVGRE hosts maintain a MAC address table to map VM MAC addresses to TNIs. When a host receives an NVGRE packet, it looks up the MAC address table to determine which VM to deliver the packet to.
6. Broadcast and Multicast Support
NVGRE uses broadcast and multicast to support communication within virtual networks, allowing VMs to perform broadcast and multicast operations for protocols like ARP and Neighbor Discovery.
Features
Network Virtualisation Goals: NVGRE aims to provide a larger number of VLANs for multi-tenancy and load balancing, overcoming the limited VLAN capacity of traditional networks.
Encapsulation and Tunneling: Uses encapsulation and tunneling to isolate virtual networks, making VM communication appear direct without considering the underlying physical network.
Cross-Data Centre Scalability: Designed to support cross-location virtual networks, ideal for distributed data centre architectures.
A Comprehensive Look at VXLAN Technology
VXLAN (Virtual Extensible LAN) is a network virtualisation technology designed to address the shortage of virtual networks in large cloud data centres.
How It Works
VXLAN encapsulates data packets by adding a Virtual Network Identifier (VNI), transmitting them over existing IP networks, and then decapsulating and delivering them on the target host.
1.Virtual Network Identifier (VNI)
VXLAN introduces a 24-bit VNI to distinguish different virtual networks. Each VNI represents a separate virtual network, allowing multiple virtual networks to operate on the same physical infrastructure without interference.
2.Packet Encapsulation
Source IP Address: The IP address of the sending VM.
Destination IP Address: The IP address of the receiving VM.
UDP Header: Contains source and destination port information to identify VXLAN packets.
VNI: The 24-bit virtual network identifier.
Original Ethernet Frame: Includes the source MAC address, destination MAC address, Ethernet protocol type, etc.
Data packets are encapsulated into VXLAN packets for communication between VMs.
3.Transport Network VXLAN packets are transmitted over existing IP networks. The IP header information is used for routing, while the VNI identifies the target virtual network.
4.Decapsulation When VXLAN packets reach the host of the target VM, the host decapsulates them, extracting the original Ethernet frame and delivering it to the target VM.
5.MAC Address Table Maintenance VXLAN hosts maintain a MAC address table to map VM MAC addresses to VNIs. When a host receives a VXLAN packet, it looks up the MAC address table to determine which VM to deliver the packet to.
6.Broadcast and Multicast Support VXLAN uses multicast to simulate broadcast and multicast behaviour within virtual networks, supporting protocols like ARP and Neighbor Discovery.
Features
Expanded VLAN Address Space: Extends VLAN identifier capacity from 4096 to 16 million with a 24-bit segment ID.
Virtual Network Isolation: Allows multiple virtual networks to coexist on the same infrastructure, each with a unique segment ID.
Multi-Tenancy Support: Ideal for environments where different tenants need isolated virtual networks.
Layer 2 and 3 Extension: Supports complex network topologies and routing configurations.
Industry Support: Widely supported by companies like Cisco, VMware, and Arista Networks.
NVGRE vs VXLAN: Uncovering the Best Virtualization Tech
NVGRE and VXLAN are both technologies for virtualising data centre networks, aimed at addressing issues in traditional network architectures such as isolation, scalability, and performance. While their goals are similar, they differ in implementation and several key aspects.
Supporters and Transport Protocols
NVGRE is supported mainly by Microsoft, using GRE as the transport protocol. VXLAN is driven by Cisco, using UDP.
Packet Format
VXLAN packets have a 24-bit VNI for 16 million virtual networks. NVGRE uses the GRE header’s lower 24 bits as the TNI, also supporting 16 million virtual networks.
Transmission Method
VXLAN uses multicast to simulate broadcast and multicast for MAC address learning and discovery. NVGRE uses multiple IP addresses for enhanced load balancing without relying on flooding and IP multicast.
Fragmentation
NVGRE supports fragmentation to manage MTU sizes, while VXLAN typically requires the network to support jumbo frames and does not support fragmentation.
Conclusion
VXLAN and NVGRE represent significant advancements in network virtualisation, expanding virtual network capacity and enabling flexible, scalable, and high-performance cloud and data centre networks. With support from major industry players, these technologies have become essential for building agile virtualised networking environments.
How FS Can Help
FS offers a wide range of data centre switches, from 1G to 800G, to meet various network requirements and applications. FS switches support VXLAN EVPN architectures and MPLS forwarding, with comprehensive protocol support for L3 unicast and multicast routing, including BGP, OSPF, EIGRP, RIPv2, PIM-SM, SSM, and MSDP. Explore FS high-quality switches and expert solutions tailored to enhance your network at the FS website.
Businesses are growing and networks are becoming more complex. Single-device solutions are having trouble meeting the high availability and performance requirements of modern data centres. To address this, two horizontal virtualisation technologies have emerged: Stacking and Multichassis Link Aggregation Group (MLAG). This article compares Stacking and MLAG. It discusses their principles, features, advantages, and disadvantages. This comparison can help you choose the best option for your network environment.
Understanding Stacking Technology
Stacking technology involves combining multiple stackable devices into a single logical unit. Users can control and use multiple devices together, increasing ports and switching abilities while improving reliability with mutual backup between devices.
Advantages of Stacking:
Simplified Management: Managed via a single IP address, reducing management complexity. Administrators can configure and monitor the entire stack from one interface.
Increased Port Density: Combining multiple switches offers more ports, meeting the demands of large-scale networks.
Seamless Redundancy: If one stack member fails, others seamlessly take over, ensuring high network availability.
Enhanced Performance: Increased interconnect bandwidth among switches improves data exchange efficiency and performance.
Unlocking the Power of MLAG Technology
Multichassis Link Aggregation Group (MLAG) is a newer cross-device link aggregation technology. It allows two access switches to negotiate link aggregation as if they were one device. This cross-device link aggregation enhances reliability from the single-board level to the device level, making MLAG suitable for modern network topologies requiring redundancy and high availability.
Advantages of MLAG:
High Availability: Increases network availability by allowing smooth traffic transition between switches in case of failure. There are no single points of failure at the switch level.
Improved Bandwidth: Aggregating links across multiple switches significantly increases accessible bandwidth, beneficial for high-demand environments.
Load Balancing: Evenly distributes traffic across member links, preventing overloads and maximising network utilisation.
Compatibility and Scalability: Better compatibility and scalability, able to negotiate link aggregation with devices from different vendors.
Stacking vs. MLAG: Which Network Virtualisation Tech Reigns Supreme?
Both Stacking and MLAG are crucial for achieving redundant access and link redundancy, significantly enhancing the reliability and scalability of data centre networks. Despite their similarities, each has distinct advantages, disadvantages, and suitable application scenarios. Understanding the concepts and advantages of Stacking and MLAG is crucial. Here’s a detailed comparison to help you distinguish between the two:
Reliability
Stacking: Centralised control plane shared by all switches, with the master switch managing the stack. Failure of the master switch can affect the entire system despite backup switches.
MLAG: Each switch operates with an independent control plane. Consequently, the failure of one switch does not impact the functionality of the other, effectively isolating fault domains and enhancing overall network reliability.
Configuration Complexity
Stacking: Appears as a single device logically, simplifying configuration and management.
MLAG: Requires individual configuration of each switch but can be simplified with modern management tools and automation scripts.
MLAG: Requires peer-link cables, which incur costs comparable to stacking cables.
Performance
Stacking: Performance may be limited by the master switch’s CPU load, affecting overall system performance.
MLAG: Each switch independently handles data forwarding, distributing CPU load and enhancing performance.
Upgrade Complexity
Stacking: Higher upgrade complexity, needing synchronised upgrades of all member devices, with longer operation times and higher risks.
MLAG: Lower upgrade complexity, allowing independent upgrades of each device, reducing complexity and risk.
Upgrade Downtime
Stacking: The duration of downtime varies between 20 seconds and 1 minute, contingent upon the traffic load.
MLAG: Minimal downtime, usually within seconds, with negligible impact.
Network Design
Stacking: Simpler design, appearing as a single device, easier to manage and design.
MLAG: More complex design, logically still two separate devices, requiring more planning and management.
Enhancing Display Networks: Stacking vs. MLAG Applications
This section explains how these technologies are used in real-world situations after learning about Stacking and MLAG differences. This will help you make informed decisions when setting up a network.
Stacking is suitable for small to medium-sized network environments that require simplified management and configuration and enhanced redundancy. It is widely used in enterprise campus networks and small to medium-sized data centres.
MLAG, on the other hand, is ideal for large data centres and high-density server access environments that require high availability and high performance. It offers redundancy and load balancing across devices. The choice between these technologies depends on the specific needs, scale, and complexity of your network.
In practical situations, Stacking and MLAG technologies can be combined to take advantage of their strengths. This creates a synergistic effect that is stronger than each technology individually. Stacking technology simplifies the network topology, increasing bandwidth and fault tolerance. MLAG technology provides redundancy and load balancing, enhancing network availability.
Therefore, consider integrating Stacking and MLAG technologies to achieve better network performance and reliability when designing and deploying enterprise networks.
Conclusion
Both Multichassis Link Aggregation (MLAG) and stackable switches offer unique advantages in modern network architectures. MLAG ensures backup and reliability with cross-switch link aggregation. Stackable switches allow for easy management and scalability by acting as one unit. Understanding the specific requirements and use cases of each technology is essential for designing resilient and efficient network infrastructures.
How FS Can Help
FS, a trusted global ICT products and solutions provider, offers a range of data centre switches to meet diverse enterprise needs. FS data centre switches support a variety of features and protocols, including stacking, MLAG, and VXLAN, making them suitable for diverse network construction. Customised solutions tailored to your requirements can assist with network upgrades. Visit the FS website to explore products and solutions that can help you build a high-performance network today.
In recent years, the advancement of cloud computing, virtualisation, and containerisation technologies has driven the adoption of network virtualisation. Both MPLS and VXLAN leverage virtualisation concepts to create logical network architectures, enabling more complex and flexible domain management. However, they serve different purposes. This article will compare VXLAN and MPLS, explaining why VXLAN is more popular than MPLS in metropolitan and wide area networks.
Understanding VXLAN and MPLS: Key Concepts Unveiled
VXLAN
Virtual Extensible LAN (VXLAN) encapsulates Layer 2 Ethernet frames within Layer 3 UDP packets, enabling devices and applications to communicate over a large physical network as if they were on the same Layer 2 Ethernet network. VXLAN technology uses the existing Layer 3 network as an underlay to create a virtual Layer 2 network, known as an overlay. As a network virtualisation technology, VXLAN addresses the scalability challenges associated with large-scale cloud computing setups and deployments.
MPLS
Multi-Protocol Label Switching (MPLS) is a technology that uses labels to direct data transmission quickly and efficiently across open communication networks. The term “multi-protocol” indicates that MPLS can support various network layer protocols and is compatible with multiple Layer 2 data link layer technologies. This technology simplifies data transmission between two nodes by using short path labels instead of long network addresses. MPLS allows the addition of more sites with minimal configuration. It is also independent of IP, merely simplifying the implementation of IP addresses. MPLS over VPN adds an extra layer of security since MPLS itself lacks built-in security features.
Data Centre Network Architecture Based on MPLS
MPLS Layer 2 VPN (L2VPN) provides Layer 2 connectivity across a Layer 3 network, but it requires all routers in the network to be IP/MPLS routers. Virtual networks are isolated using MPLS pseudowire encapsulation and can stack MPLS labels, similar to VLAN tag stacking, to support a large number of virtual networks.
IP/MPLS is commonly used in telecom service provider networks, so many service providers’ L2VPN services are implemented using MPLS. These include point-to-point L2VPN and multipoint L2VPN implemented according to the Virtual Private LAN Service (VPLS) standard. These services typically conform to the MEF Carrier Ethernet service definitions of E-Line (point-to-point) and E-LAN (multipoint).
Because MPLS and its associated control plane protocols are designed for highly scalable Layer 3 service provider networks, some data centre operators have adopted MPLS L2VPN in their data centre networks to overcome the scalability and resilience limitations of Layer 2 switched networks, as shown in the diagram.
Why is VXLAN Preferred Over MPLS in Data Centre Networks?
Considering the features and applications of both technologies, the following points summarise why VXLAN is more favoured:
Cost of MPLS Routers
For a long time, some service providers have been interested in building cost-effective metropolitan networks using data centre-grade switches. Over 20 years ago, the first generation of competitive metro Ethernet service providers, like Yipes and Telseon, built their networks using the most advanced gigabit Ethernet switches available in enterprise networks at the time. However, such networks struggled to provide the scalability and resilience required by large service providers (SPs). Consequently, most large SPs shifted to MPLS (as shown in the diagram below). However, MPLS routers are more expensive than ordinary Ethernet switches, and this cost disparity has persisted over the decades. Today, data centre-grade switches combined with VXLAN overlay architecture can largely eliminate the shortcomings of pure Layer 2 networks without the high costs of MPLS routing, attracting a new wave of SPs.
Tight Coupling Between Core and Edge
MPLS-based VPN solutions require tight coupling between edge and core devices, meaning every node in the data centre network must support MPLS. In contrast, VXLAN only requires a VTEP (VXLAN Tunnel Endpoint) in edge nodes (e.g., leaf switches) and can use any IP-capable device or IP transport network to implement data centre spine and data centre interconnect (DCI).
MPLS Expertise
Outside of large service providers, MPLS technology is challenging to learn, and relatively few network engineers can easily build and operate MPLS-based networks. VXLAN, being simpler, is becoming a fundamental technology widely mastered by data centre network engineers.
Advancements in Data Centre Switching Technology
Modern data centre switching chips have integrated numerous functions that make metro networks based on VXLAN possible. Here are two key examples:
Expanded tables providing the routing and forwarding scale required to create resilient, scalable Layer 3 underlay networks and multi-tenant overlay services.
Additionally, newer data centre-grade switches have powerful CPUs capable of supporting advanced control planes crucial for extended Ethernet services, whether it’s BGP EVPN (a protocol-based approach) or an SDN-based protocol-less control plane. Therefore, in many metro network applications, specialised (and thus high-cost) routing hardware is no longer necessary.
VXLAN Overlay Architecture for Metropolitan and Wide Area Networks
Overlay networks have been widely adopted in various applications such as data centre networks and enterprise SD-WAN. A key commonality among these overlay networks is their loose coupling with the underlay network. Essentially, as long as the network provides sufficient capacity and resilience, the underlay network can be constructed using any network technology and utilise any control plane. The overlay is only defined at the service endpoints, with no service provisioning within the underlay network nodes.
One of the primary advantages of SD-WAN is its ability to utilise various networks, including broadband or wireless internet services, which are widely available and cost-effective, providing sufficient performance for many users and applications. When VXLAN overlay is applied to metropolitan and wide area networks, similar benefits are also realised, as depicted in the diagram.
When building a metropolitan network to provide services like Ethernet Line (E-Line), Multipoint Ethernet Local Area Network (E-LAN), or Layer 3 VPN (L3VPN), it is crucial to ensure that the Underlay can meet the SLA (Service Level Agreement) requirements for such services.
VXLAN-Based Metropolitan Network Overlay Control Plane Options
So far, our focus has mainly been on the advantages of VXLAN over MPLS in terms of network architecture and capital costs, i.e., the advantages of the data plane. However, VXLAN does not specify a control plane, so let’s take a look at the Overlay control plane options.
The most prominent control plane option for creating VXLAN Overlay and providing Overlay services should be BGP EVPN, which is a protocol-based approach that requires service configuration in each edge node. The main drawback of BGP EVPN is the complexity of operations.
Another protocol-less approach is using SDN and services defined in an SDN controller to programme the data plane of each edge node. This approach eliminates much of the operational complexity of protocol-based BGP EVPN. Nonetheless, the centralised SDN controller architecture, suitable for single-site data centre architectures, presents significant scalability and resilience issues when implemented in metropolitan and wide area networks. As a result, it’s unclear whether it’s a superior alternative to MPLS for metropolitan networks.
There’s also a third possibility—decentralised or distributed SDN, in which the SDN controller’s functionality is duplicated and spread across the network. This can also be referred to as a “controller-less” SDN because it doesn’t necessitate a separate controller server/device, thereby completely resolving the scalability and resilience problems associated with centralised SDN control while maintaining the advantages of simplified and expedited service configuration.
Deployment Options
Due to VXLAN’s ability to decouple Overlay services delivery from the Underlay network, it creates deployment options that MPLS cannot match, such as virtual service Overlays on existing IP infrastructure, as shown in the diagram. VXLAN-based switch deployments at the edge of existing networks, scalable according to business requirements, allow for the addition of new Ethernet and VPN services and thus generate new revenue without altering the existing network.
The metropolitan network infrastructure shown in Figure 2 can support all services offered by an MPLS-based network, including commercial internet, Ethernet and VPN services, as well as consumer triple-play services. Moreover, it completely eliminates the costs and complexities associated with MPLS.
Conclusion
VXLAN has become the most popular overlay network virtualization protocol in data centre network architecture, surpassing many alternative solutions. When implemented with hardware-based VTEPs in switches and DPUs, and combined with BGP EVPN or SDN control planes and network automation, VXLAN-based overlay networks can provide the scalability, agility, high performance, and resilience required for distributed cloud networks in the foreseeable future.
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With the rapid development of cloud computing and virtualisation technologies, data centre networks are facing increasing challenges. Traditional network architectures have limitations in meeting the demands of large-scale data centres, particularly in terms of scalability, isolation, and flexibility. To overcome these limitations and provide better performance and scalability for data centre networks, VXLAN (Virtual Extensible LAN) has emerged as an innovative network virtualisation technology. This article will detail the principles and advantages of VXLAN, its applications in data centre networks, and help you understand the differences between VXLAN and VLAN.
The Power of VXLAN: Transforming Data Centre Networks
VXLAN is a network virtualisation technology designed to overcome the limitations of traditional Ethernet, offering enhanced scalability and isolation. It enables the creation of a scalable virtual network on existing infrastructure, allowing virtual machines (VMs) to move freely within a logical network, regardless of the underlying physical network topology. VXLAN achieves this by creating a virtual Layer 2 network over an existing IP network, encapsulating traditional Ethernet frames within UDP packets for transmission. This encapsulation allows VXLAN to operate on current network infrastructure without requiring extensive modifications.
VXLAN uses a 24-bit VXLAN Network Identifier (VNI) to identify virtual networks, allowing multiple independent virtual networks to coexist simultaneously. The destination MAC address of a VXLAN packet is replaced with the MAC address of the virtual machine or physical host within the VXLAN network, enabling communication between virtual machines. VXLAN also supports multipath transmission through MP-BGP EVPN and provides multi-tenant isolation within the network.
How it works
Encapsulation: When a virtual machine (VM) sends an Ethernet frame, the VXLAN module encapsulates it in a UDP packet. The source IP address of the packet is the IP address of the host where the VM resides, and the destination IP address is that of the remote endpoint of the VXLAN tunnel. The VNI field in the VXLAN header identifies the target virtual network. The UDP packet is then transmitted through the underlying network to reach the destination host.
Decapsulation: Upon receiving a VXLAN packet, the VXLAN module parses the UDP packet header to extract the encapsulated Ethernet frame. By examining the VNI field, the VXLAN module identifies the target virtual network and forwards the Ethernet frame to the corresponding virtual machine or physical host.
This process of encapsulation and decapsulation allows VXLAN to transparently transport Ethernet frames over the underlying network, while simultaneously providing logically isolated virtual networks.
Key Components
VXLAN Identifier (VNI): Used to distinguish different virtual networks, similar to a VLAN identifier.
VTEP (VXLAN Tunnel Endpoint): A network device responsible for encapsulating and decapsulating VXLAN packets, typically a switch or router.
Control Plane and Data Plane: The control plane is responsible for establishing and maintaining VXLAN tunnels, while the data plane handles the actual data transmission.
The Benefits of VXLAN: A Changer for Virtual Networks
VXLAN, as an emerging network virtualisation technology, offers several advantages in data centre networks:
Scalability
VXLAN uses a 24-bit VNI identifier, supporting up to 16,777,216 virtual networks, each with its own independent Layer 2 namespace. This scalability meets the demands of large-scale data centres and supports multi-tenant isolation.
Cross-Subnet Communication
Traditional Ethernet relies on Layer 3 routers for forwarding across different subnets. VXLAN, by using the underlying IP network as the transport medium, enables cross-subnet communication within virtual networks, allowing virtual machines to migrate freely without changing their IP addresses.
Flexibility
VXLAN can operate over existing network infrastructure without requiring significant modifications. It is compatible with current network devices and protocols, such as switches, routers, and BGP. This flexibility simplifies the creation and management of virtual networks.
Multipath Transmission
VXLAN leverages multipath transmission (MP-BGP EVPN) to achieve load balancing and redundancy in data centre networks. It can choose the optimal path for data transmission based on network load and path availability, providing better performance and reliability.
Security
VXLAN supports tunnel encryption, ensuring data confidentiality and integrity over the underlying IP network. Using secure protocols (like IPsec) or virtual private networks (VPNs), VXLAN can offer a higher level of data transmission security.
VXLAN vs. VLAN: Unveiling the Key Differences
VXLAN (Virtual Extensible LAN) and VLAN (Virtual Local Area Network) are two distinct network isolation technologies that differ significantly in their implementation, functionality, and application scenarios.
Implementation
VLAN: VLAN is a Layer 2 (data link layer) network isolation technology that segments a physical network into different virtual networks using VLAN identifiers (VLAN IDs) configured on switches. VLANs use VLAN tags within a single physical network to identify and isolate different virtual networks, achieving isolation between different users or devices.
VXLAN: VXLAN is a Layer 3 (network layer) network virtualisation technology that extends Layer 2 networks by creating virtual tunnels over an underlying IP network. VXLAN uses VXLAN Network Identifiers (VNIs) to identify different virtual networks and encapsulates original Ethernet frames within UDP packets to enable communication between virtual machines, overcoming physical network limitations.
Functionality
VLAN: VLANs primarily provide Layer 2 network segmentation and isolation, allowing a single physical network to be divided into multiple virtual networks. Different VLANs are isolated from each other, enhancing network security and manageability.
VXLAN: VXLAN not only provides Layer 2 network segmentation but also creates virtual networks over an underlying IP network, enabling extensive dynamic VM migration and inter-data centre communication. VXLAN offers greater network scalability and flexibility, making it suitable for large-scale cloud computing environments and virtualised data centres.
Application Scenarios
VLAN: VLANs are suitable for small to medium-sized network environments, commonly found in enterprise LANs. They are mainly used for organisational user segmentation, security isolation, and traffic management.
VXLAN: VXLAN is ideal for large data centre networks, especially in cloud computing environments and virtualised data centres. It supports large-scale dynamic VM migration, multi-tenant isolation, and network scalability, providing a more flexible and scalable network architecture.
These distinctions highlight how VXLAN and VLAN cater to different networking needs and environments, offering tailored solutions for varying levels of network complexity and scalability.
Enhancing Data Centres with VXLAN Technology
The application of VXLAN enhances the flexibility, efficiency, and security of data centre networks, forming a crucial part of modern data centre virtualisation. Here are some typical applications of VXLAN in data centres:
Virtual Machine Migration
VXLAN allows virtual machines to migrate freely between different physical hosts without changing IP addresses. This flexibility and scalability are vital for achieving load balancing, resource scheduling, and fault tolerance in data centres.
Multi-Tenant Isolation
By using different VNIs, VXLAN can divide a data centre into multiple independent virtual networks, ensuring isolation between different tenants. This isolation guarantees data security and privacy for tenants and allows each tenant to have independent network policies and quality of service guarantees.
Inter-Data Centre Connectivity
VXLAN can extend across multiple data centres, enabling the establishment of virtual network connections between them. This capability supports resource sharing, business expansion, and disaster recovery across data centres.
Cloud Service Providers
VXLAN helps cloud service providers build highly scalable virtualised network infrastructures. By using VXLAN, cloud service providers can offer flexible virtual network services and support resource isolation and security in multi-tenant environments.
Virtual Network Functions (VNF)
Combining VXLAN with Network Functions Virtualisation (NFV) enables the deployment and management of virtual network functions. VXLAN serves as the underlying network virtualisation technology, providing flexible network connectivity and isolation for VNFs, thus facilitating rapid deployment and elastic scaling of network functions.
Conclusion
In summary, VXLAN offers powerful scalability, flexibility, and isolation, providing new directions and solutions for the future development of data centre networks. By utilising VXLAN, data centres can achieve virtual machine migration, multi-tenant isolation, inter-data centre connectivity, and enhanced support for cloud service providers.
How FS Can Help
As an industry-leading provider of network solutions, FS offers a variety of high-performance data centre switches supporting multiple protocols, such as MLAG, EVPN-VXLAN, link aggregation, and LACP. FS switches come pre-installed with PicOS®, equipped with comprehensive SDN capabilities and the compatible AmpCon™ management software. This combination delivers a more resilient, programmable, and scalable network operating system (NOS) with lower TCO. The advanced PicOS® and AmpCon™ management platform enables data centre operators to efficiently configure, monitor, manage, and maintain modern data centre fabrics, achieving higher utilisation and reducing overall operational costs.
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