Category Archives: Data Center

Optimizing Data Centers with Large Layer 2 Network

In modern data center, large Layer 2 network play a crucial role in supporting high-performance and reliable networking for critical business applications. They simplify network management and enable adoption of new technologies, making them essential to data center architecture. This article will explore the necessity of a large Layer 2 network and the technologies used to implement them.

Why Is a Large Layer 2 Network Needed?

Traditional data center architecture typically follows a combination of Layer 2 (L2) and Layer 3 (L3) network designs, restricting the movement of servers across different Layer 2 domains. However, as data centers evolve from traditional setups to virtualized and cloud-based environments, the emergence of server virtualization technology demands the capability for dynamic VM migration. This process involves migrating a virtual machine from one physical server to another, ensuring it remains operational and unnoticed by end users. It enables administrators to flexibly allocate server resources or perform maintenance and upgrades on physical servers without disrupting users.

The key to dynamic VM migration is ensuring that services on the VM are uninterrupted during the transfer, which requires the VM’s IP address and operational state to remain unchanged. Therefore, dynamic VM migration can only occur within the same Layer 2 domain and not across different Layer 2 domains.

To achieve extensive or even cross-regional dynamic VM migration, all servers potentially involved in the migration must be included in the same Layer 2 domain, forming a larger Layer 2 network. This larger network allows for seamless, unrestricted VM migration across a wide area, known as a large Layer 2 network.

Large Layer 2 Network

How to Achieve a Truly Large Layer 2 Network?

The technologies for implementing large Layer 2 network can be divided into two main categories based on their source. One category is proposed by network equipment manufacturers, including network device virtualization and routing optimized Layer 2 forwarding technologies. The other category is proposed by IT manufacturers, including overlay technology and EVN technology.

Network Device Virtualization

Network device virtualization technology combines two or more physical network devices that are redundant with each other and virtualizes them into a logical network device, which is presented as only one node in the entire network. By combining network device virtualization with link aggregation technology, the original multi-node, multi-link structure can be transformed into a logical single-node, single-link structure. This eliminates the possibility of loops and removes the need for deploying loop prevention protocols. Consequently, the scale of the Layer 2 network is no longer constrained by these protocols, thereby achieving a large Layer 2 network.

Building a large Layer 2 network using network virtualization technology results in a logically simple network that is easy to manage and maintain. However, compared to other technologies, the network scale is relatively small. In addition, these technologies are the private technologies of each vendor, and can only use devices from the same vendor for networking, which is usually suitable for building large Layer 2 networks at the level of small and medium-sized PODs.

Routing Optimized Layer 2 Forwarding Technology

The core issue with traditional Layer 2 network is the loop problem. To address this, manufacturers insert additional headers in front of Layer 2 packets and use routing calculations to control data forwarding across the entire network. This approach extends the Layer 2 network’s scale to cover the entire network without being limited by the number of core switches, thereby achieving a large Layer 2 network.


The forwarding of Layer 2 messages by means of route computation requires the definition of new protocol mechanisms. These new protocols include TRILL, FabricPath, SPB, etc. Taking TRILL as an example, it transparently transmits the original Ethernet frame by encapsulating it with a TRILL header and a new outer Ethernet frame. TRILL switches forward packets using the Nickname in the TRILL header, which can be collected, synchronized, and updated through the IS-IS routing protocol. When VMs migrate within a TRILL network, IS-IS can automatically update the forwarding tables on each switch, maintaining the VM’s IP address and state, thus enabling dynamic migration.

TRILL enables the creation of larger Layer 2 network and, being an IETF standard protocol, simplifies vendor interoperability. This makes it ideal for large PODs or entire data centers. However, TRILL deployment often necessitates new hardware and software, which can result in higher investment costs.

Overlay Technology

Overlay technology involves encapsulating the original Layer 2 packets sent by the source host, transmitting them transparently through the existing network, and then decapsulating them at the destination to retrieve the original packets, which are then forwarded to the target host. This process achieves Layer 2 communication between hosts. By encapsulating and decapsulating packets, an additional large Layer 2 network is effectively overlaid on top of the existing physical network, so it is called overlay technology.

Overlay technology

This is equivalent to virtualizing the entire bearer network into a huge Layer 2 switch. Each virtual machine is directly connected to a port of this switch, so naturally there is no loop. The dynamic migration of a virtual machine is equivalent to changing the virtual machine from one port of the switch to another port, and the status can remain unchanged.

The overlay solution is proposed by IT vendors, such as VXLAN and NVGRE. In order to bulid an overlay network, FS has launched a VXLAN network solution, which uses VXLAN technology to fully improve network utilization and scalability. In the overlay solution, the bearer network only needs to meet the basic switching and forwarding capabilities, and the encapsulation and decapsulation of the original packets can be carried out by the virtual switches in the server, without relying on network devices.

EVN Technology

EVN (Easy Virtual Network) technology is designed for Layer 2 interconnection across data centers rather than within a single data center. Traditional methods like VPLS or enhanced VPLS over GRE often suffer from complex configurations, low bandwidth utilization, high deployment costs, and significant resource consumption. However, EVN, based on VXLAN tunnels, effectively addresses these issues and can be seen as an extension of VXLAN.

EVN technology uses the MP-BGP protocol to exchange MAC address information between Layer 2 networks and generates MAC address table entries for packet forwarding. It supports automatic VXLAN tunnel creation, multi-homing load balancing, BGP route reflection, and ARP caching. These features effectively address the issues found in VPLS and other Layer 2 interconnection technologies, making EVN an ideal solution for data center Layer 2 interconnection.


In this article, we discussed the importance of a large Layer 2 network in modern data centers, emphasizing its role in supporting virtualization, dynamic VM migrations, and the technologies needed for scalability. As an ICT company, FS is committed to being the top provider for businesses seeking dependable, cost-effective solutions for their network architecture. Utilizing our company’s advanced switches can significantly enhance the scalability of data centers, ensuring robust support for large Layer 2 networks. Register on our website today for more information and personalized recommendations.

Unlock Network Stability: Master Fault Detection Tech

With the rapid development of information technology, the network has become an indispensable part of data center operations. From individual users to large enterprises, everyone relies on the network for communication, collaboration, and information exchange within these centralized hubs of computing power. However, the continuous expansion of network scale and increasing complexity within data centers also brings about numerous challenges, prominently among them being network faults. This article will take you through several common fault detection technologies, including CFD, BFD, DLDP, Monitor Link, MAC SWAP, and EFM, as well as their applications and working principles in different network environments.

What is Fault Detection Technology?

Fault detection technology is a set of methods, tools, and techniques used to identify and diagnose abnormalities or faults within systems, processes, or equipment. The primary goal is to detect deviations from normal operation promptly, allowing for timely intervention to prevent or minimize downtime, damage, or safety hazards. Fault detection technology finds applications in various industries, including manufacturing, automotive, aerospace, energy, telecommunications, and healthcare. By enabling early detection of faults, these technologies help improve reliability, safety, and efficiency while reducing maintenance costs and downtime.

Common Types of Network Faults

Networks are integral to both our daily lives and professional endeavors, yet they occasionally fall victim to various faults. This holds particularly true within data centers, where the scale and complexity of networks reach unparalleled levels. In this part, we’ll delve into common types of network faults and explore general solutions for addressing them. Whether you’re a home user or managing an enterprise network, understanding these issues is crucial for maintaining stability and reliability, especially within the critical infrastructure of data centers.

What Causes Network Failure?

Network faults can arise from various sources, often categorized into hardware failures, software issues, human errors, and external threats. Understanding these categories provides a systematic approach to managing and mitigating network disruptions.

  • Hardware Failures:Hardware failures are physical malfunctions in network devices, leading to impaired functionality or complete downtime.
  • Software Issues: Software-related problems stem from errors or bugs in the operating systems, firmware, or applications running on network devices. Common software faults include operating system crashes, firmware bugs, configuration errors and protocol issues.
  • Human Errors: Human errors, such as misconfigurations or mistakes during maintenance activities, can introduce vulnerabilities or disrupt network operations. Common human-induced faults include unintentional cable disconnections, misconfigurations, inadequate documentation or lack of training.
  • External Threats: External threats pose significant risks to network security and stability, potentially causing extensive damage or data loss. Common external threats include cyberattacks, malware attacks, physical security breaches or environmental factors.

By recognizing and addressing these common types of network faults, organizations can implement proactive measures to enhance network resilience, minimize downtime, and safeguard critical assets against potential disruptions.

What Can We Do to Detect These Failures?

  • Connectivity testing: Checks for proper connectivity between devices on a network. This can be accomplished through methods such as a ping test, which detects network connectivity by sending packets to a target device and waiting for a response.
  • Traffic analysis: Monitor data traffic in the network to detect unusual traffic patterns or sudden increases in traffic. This may indicate a problem in the network, such as congestion or a malicious attack.
  • Fault tree analysis: A fault tree model is created by analyzing the various possibilities that can lead to a fault. This helps in determining the probability of a fault occurring and the path to diagnose it.
  • Log analysis: Analyze log files of network devices and systems to identify potential problems and anomalies. Error messages and warnings in the logs often provide important information about the cause of the failure.
  • Remote monitoring: Utilize remote monitoring tools to monitor the status of network devices in real time. This helps to identify and deal with potential faults in a timely manner.
  • Self-healing network technologies: Introducing self-healing mechanisms to enable the network to recover automatically when a failure is detected. This may involve automatic switching to backup paths, reconfiguration of devices, etc.
  • Failure simulation: Tests the network’s performance under different scenarios by simulating different types of failures and assessing its tolerance and resilience to failures.

Commonly Used Fault Detection Technologies

In the next section, we will explore some common fault detection technologies essential for maintaining the robustness of networks, particularly within the dynamic environment of data centers. These technologies include CFD, BFD, DLDP, Monitor Link, MAC SWAP, and EFM, each offering unique capabilities and operating principles tailored to different network contexts. Understanding their applications is vital for effectively identifying and addressing network faults, ensuring the uninterrupted performance of critical data center operations.


CFD (Connectivity Fault Detection), which adheres to the IEEE 802.1ag Connectivity Fault Management (CFM) standard, is an end-to-end per-VLAN link layer Operations, Administration, and Maintenance (OAM) mechanism utilized for link connectivity detection, fault verification, and fault location. It is a common feature found in networking equipment and protocols. Its primary function is to identify faults or disruptions in network connectivity between devices. Typically, it operates through the following steps: monitoring connectivity, expecting responses, detecting faults, and triggering alerts or actions. By continuously monitoring network connectivity and promptly detecting faults, CFD ensures the reliability and stability of network communications, facilitating quicker issue resolution and minimizing downtime.


BFD (Bidirectional Forwarding Detection) is a function that checks the survival status of the forwarding path between two adjacent routers, quickly detect failures, and notify the routing protocol. It is designed to achieve the fastest fault detection with minimal overhead and is typically used to monitor links between two network nodes. The BFD can be said to be an effective function when there is an L2 switch between adjacent routers and a failure occurs where the link status cannot be transmitted. FS offers a range of data center switches equipped with BFD functions, guaranteeing optimal network performance and stability. Opting for FS enables you to construct a robust and dependable data center network, benefiting from the enhanced network reliability facilitated by BFD.

Bidirectional Forwarding Detection


DLDP (Device Link Detection Protocol) is instrumental in bolstering the reliability and efficiency of Ethernet networks within data centers. Serving as an automatic link status detection protocol, DLDP ensures the timely detection of connection issues between devices. DLDP maintains the status of links by periodically sending messages, and once it detects any abnormality in the link, it promptly notifies the relevant devices and takes necessary actions to rectify the issue, ensuring network stability and reliability. This proactive approach not only enhances network stability and reliability but also streamlines fault troubleshooting processes within Ethernet-based data center networks, ultimately optimizing operational performance.

Device Link Detection Protocol

Monitor Link

Monitor Link is to trigger the change of the downlink port state by monitoring the change of the uplink port state of the device, thus triggering the switching of the backup link. This scheme is usually used in conjunction with Layer 2 topology protocols to realize real-time monitoring and switching of links. Monitor Link is mainly used in scenarios that require high network redundancy and link backup, such as in enterprise or business-critical networks that require high availability.

As the figure shows, once a change in uplink status is monitored, the Monitor Link system triggers a corresponding change in downlink port status. This may include closing or opening the downlink port, triggering a switchover of the backup link. In a data center network, Monitor Link can be used to monitor the connection status between servers. When the primary link fails, Monitor Link can quickly trigger the switchover of the backup link, ensuring high availability in the data center.

Monitor Link application scenario


“MAC SWAP” refer to MAC address swap, which is a communication technique in computer networking. This involves swapping the source and destination MAC addresses during the transmission of data packets, typically performed by network devices such as switches or routers. This swapping usually occurs as packets pass through network devices, which forward packets to the correct port based on their destination MAC addresses.

Within the intricate network infrastructure of data centers, MAC address swapping is pervasive, occurring as packets traverse various network devices. This process guarantees the efficient routing and delivery of data, essential for maintaining seamless communication within both local area networks (LANs) and wide area networks (WANs) encompassed by data center environments.

Overall, MAC SWAP enables real-time monitoring of link status, providing timely link information and embodies flexibility to some extent, but may also introduce additional bandwidth overhead and have impact on network performance.


EFM (Ethernet in the First Mile), as its name suggests, is a technology designed to solve link problems common in the last mile of Ethernet access and provide high-speed Ethernet services over the first mile of connection. The last-mile problem usually refers to the last physical link in the network access layer between the subscriber’s equipment and the service provider’s network, and EFM is committed to improving the performance and stability of this link to ensure that subscribers can get reliable network access services.

EFM is often used as a broadband access technology for delivering high-speed Internet access, voice services, and other data services to businesses and residential customers within data center environments. EFM supports various deployment scenarios, including point-to-point and point-to-multipoint configurations. This flexibility allows service providers to tailor their network deployments based on factors such as geographic coverage, subscriber density, and service offerings.

As data centers strive to expand Ethernet-based connectivity to the access network, EFM plays a pivotal role in enabling service providers to deliver high-speed, reliable, and cost-effective Ethernet services to their customers. This technology significantly contributes to the overall efficiency and functionality of data center operations by ensuring seamless and dependable network connectivity for all stakeholders involved.


In the face of evolving network environments, it is increasingly important to accurately and rapidly identify and resolve fault problems. Mastering fault detection techniques will definitely unleash your network’s stability. Integrating fault detection techniques into network infrastructure, especially in data center environments, is critical to maintaining high availability and minimizing downtime.

How FS Can Help

The comprehensive networking solutions and product offerings not only save costs but also reduce power consumption, delivering higher value. Would you like to reduce the occurrence rate of failures? FS tailors customized solutions for you and provide free technical support. By choosing FS, you can confidently build a powerful and reliable data center network and enjoy improvement in network reliability.

Unveiling Storage Secrets: The Power of Distributed Systems

In the realm of data center storage solutions, understanding the intricacies of expansion methods is paramount. Effective storage is crucial for managing the growing volumes of data and ensuring secure, efficient access. As data centers evolve, reliable and flexible storage options are essential to meet the ever-changing demands of businesses. With this foundation, this article will start with traditional storage systems and move towards distributed storage fundamentals and their diverse applications.

Direct Attached Storage

Direct Attached Storage (DAS) refers to storage devices directly connected to a server, utilizing interfaces like SATA, SAS, and USB. It offers cost-effective and simple installation, with good performance for applications like operating systems and databases. However, DAS has limited scalability and challenges in resource sharing among servers. Additionally, server failures can impact storage access, highlighting the need for careful consideration in its implementation.


Centralized Network Storage

Unlike DAS, NAS and SAN storage is networked storage, where NAS has its own file system that can be accessed and used directly through a PC, while SAN does not have its own file system, but has dedicated switches that provide storage services to servers over a dedicated network.

  • NAS

NAS (Network Attached Storage) is a specialized storage server designed to provide file-level data access over a network. Connected through Ethernet, it enables access via protocols such as NFS and CIFS/SMB. NAS offers centralized management, facilitating easy sharing and good scalability for storage needs. However, compared to DAS, NAS typically incurs a higher cost. Furthermore, its performance is susceptible to network conditions, which can affect data access speeds. Despite these drawbacks, NAS remains a popular choice for organizations seeking efficient and centralized file storage solutions.

  • SAN

SAN (Storage Area Network) is a high-speed dedicated network designed to facilitate block-level data access, primarily tailored for enterprise-level applications. SANs typically utilize advanced technologies like Fiber Channel (FC) or Ethernet, establishing connections between servers and storage devices via protocols such as FC-SAN or iSCSI. These networks offer numerous advantages, including high performance, scalability, and suitability for large-scale data storage and mission-critical applications. SANs also support data redundancy and robust disaster recovery mechanisms. However, the implementation of SANs comes with notable drawbacks, such as high initial costs, complex configuration and management requirements, necessitating specialized knowledge and technical support throughout their lifecycle.


In summary, DAS is like a large-scale portable hard drive, suitable for small environments or personal use; NAS is a storage device within a network, ideal for small businesses or households requiring file sharing capabilities; SAN is a network within storage devices, designed for high-performance, high-availability storage solutions for large enterprises and data centers.

Basics of Distributed Storage

From the organization structure of storage, storage can be divided into three types: direct attached storage (DAS), centralized network storage (NAS and SAN), and distributed network storage. Next, we will explore distributed storage in detail, examining its core principles, advantages, classifications and applications.

Distributed storage is a data storage architecture that disperses data across multiple independent physical storage devices (nodes) over a network, rather than centrally storing it on a single or a few devices like traditional storage. This technology is designed to enhance the scalability, performance, reliability, and efficiency of storage systems. Consequently, it is particularly suitable for handling large-scale data storage and access requirements.

Advantages of Distributed Storage

Distributed storage systems offer numerous benefits that make them a preferred choice for modern data storage needs, especially in large-scale and geographically dispersed environments. Here are some of the key advantages:

  • Reliability and Redundancy: These systems typically replicate data across multiple nodes, ensuring that even if one node fails, the data can still be retrieved from another node. This replication enhances the reliability and availability of the data. Additionally, distributed storage systems are designed to be fault-tolerant, allowing them to continue operating smoothly even in the event of hardware failures. For instance, if a data center is rendered inoperative due to a natural disaster, other data centers can still provide data access services, ensuring continuous availability.
  • Scalability: Distributed storage systems can easily expand storage capacity by adding nodes, an approach known as horizontal scaling. In contrast, centralized systems need to expand by adding capacity to individual storage devices, known as vertical scaling, which is typically less efficient and more costly. In addition, distributed storage systems can balance workloads across multiple nodes, preventing a single node from becoming a performance bottleneck. This scalability makes distributed storage suitable for a wide range of needs, from small businesses to large-scale Internet services.
  • Cost Efficiency: Distributed storage systems often utilize commodity hardware, which is more economical than specialized storage solutions. This reduces hardware costs and allows organizations to build large-scale storage systems using affordable equipment.
  • Improved Disaster Recovery: By storing data in multiple locations, these systems are better protected against natural disasters, power outages and other localized disruptions. Cloud storage providers typically back up data in different geographic locations to ensure high availability and security.

In summary, distributed storage represents a powerful and versatile solution for modern data management, offering significant advantages in reliability, scalability, cost efficiency, and disaster recovery. These advantages make it an essential component of enterprise storage architectures, capable of meeting the diverse needs of today’s data-driven organizations.

Classification of distributed storage

Based on the characteristics and requirements of different scenarios, distributed storage products can be classified into four main categories based on storage objects, product forms, storage mediums, and deployment methods.

  • Classification by storage object

In terms of storage objects, it includes distributed block storage, distributed file storage, distributed object storage, and distributed unified storage. Distributed block storage examples include Ceph and vSAN, while distributed file storage examples are Ceph, HDFS, and GFS. Distributed object storage, such as Ceph and Swift, is designed for handling unstructured data like text, audio, and video. Distributed unified storage supports block, file, and object storage, catering to the diverse needs of virtualization, cloud, and container platforms.

  • Classification by product form

When it comes to product forms, distributed storage can be delivered as appliances, pure hardware, or pure software. Appliances integrate hardware and software for high compatibility and performance. Pure hardware solutions, such as disk arrays and flash clusters, offer reliable storage for sensitive data. Pure software solutions provide customized application software and platform licenses, ideal for optimizing existing storage hardware in legacy data centers.

  • Classification by storage medium

Regarding storage mediums, distributed storage can be all-flash or hybrid. Distributed all-flash storage, composed entirely of SSDs, offers exceptionally high read and write speeds, making it suitable for performance-intensive applications. Distributed hybrid flash storage combines SSDs and HDDs, balancing cost and performance, and is currently the mainstream choice for many enterprises.

  • Classification by deployment method

Deployment methods for distributed storage include virtualization integration, container integration, and separation. Virtualization integration involves deploying storage and server virtualization on the same hardware node, simplifying architecture and reducing costs. Container integration is designed for environments like Kubernetes, offering seamless integration and efficient resource management. Lastly, the separation method keeps storage nodes and applications distinct, allowing flexible adaptation to different computing environments and ensuring scalability and performance for large-scale data storage needs.

Mainstream Technologies in Distributed Storage

  • Ceph

Currently, the most widely used distributed storage technology, Ceph, is the result of Sage’s doctoral studies, published in 2004 and subsequently contributed to the open-source community. It has garnered support from numerous cloud computing and storage vendors. Supporting object storage, block device storage, and file storage, it demands high technical proficiency in operations and maintenance. During Ceph expansion, its characteristic of balanced data distribution may lead to a decrease in overall system performance.

  • GPFS

Developed by IBM, GPFS is a shared file system, and many vendor products are based on it. It is a parallel disk file system that ensures all nodes within a resource group can access the entire file system in parallel. GPFS consists of network shared disks (NSD) and physical disks, allowing clients to share files distributed across different nodes’ disks, resulting in excellent performance. GPFS supports traditional centralized storage arbitration mechanisms and file locking, ensuring data security and integrity, which other distributed storage systems cannot match.

  • HDFS

HDFS (Hadoop Distibuted File System), a storage component of the Hadoop big data architecture, is primarily used for storing large data. It employs multi-copy data protection, suitable for low write and multiple read businesses. It has high data transfer throughput but poor data read latency, making it unsuitable for frequent data writes.

  • GFS

Google’s distributed file storage system, designed specifically for storing massive search data. The HDFS system was initially designed and implemented based on the concept of GFS (Google File System). Similarly suitable for large file read/write operations, it is unsuitable for small file storage. Ideal for processing large-scale file reads, requiring high bandwidth, and insensitive to data access latency for search-like businesses.

  • Swift

Swift is also an open-source storage project primarily oriented towards object storage, similar to the object storage service provided by Ceph. It is mainly used to address unstructured data storage issues, targeting object storage businesses that require high data processing efficiency but low data consistency. In OpenStack, the object storage service uses Swift rather than Ceph.

  • Lustre

An open-source cluster file system based on the Linux platform, jointly developed by HP, Intel, Cluster File System, and the U.S. Department of Energy, formally open-sourced in 2003, mainly used in the HPC supercomputing field. It supports tens of thousands of client systems and can support PB-level storage capacity, with a single file supporting a maximum of 320TB capacity. It supports RDMA networks and optimizes large file read/write fragmentation. It lacks a replica mechanism, leading to single points of failure. If a client or node fails, the data stored on that node will be inaccessible until it is restarted.

  • Amazon S3

Amazon S3(Simple Storage Service) is a cloud storage service provided by Amazon and belongs to distributed object storage. It allows users to store and retrieve any amount of data and provides high reliability and durability. It is widely used in backup, archiving, static website hosting, and other fields.

  • GlusterFS

GlusterFS is a scalable distributed file system that supports distributed data volumes and can store data across multiple servers. It adopts decentralized architecture, providing high availability and performance, suitable for large file storage and content distribution.

Applications of Distributed Storage

In the realm of modern technology, distributed storage has emerged as a pivotal solution, catering to a diverse array of needs across various sectors. Here’s how distributed storage is transforming data management:

  • Cloud Storage: At the core of cloud service providers, distributed storage facilitates elastic scalability and ensures data isolation and security in multi-tenant environments.
  • Big Data Analytics: Powering platforms like Hadoop with HDFS, distributed file systems enable the storage and processing of massive datasets, supporting large-scale data analytics.
  • Containerization and Microservices: With tools like Kubernetes, distributed storage offers persistent storage volumes, ensuring data persistence across containerized environments, vital for container orchestration and microservices architecture.
  • Media and Entertainment: Meeting the high-throughput and large-capacity demands of media storage and streaming services, distributed storage solutions excel in scenarios requiring seamless handling of multimedia content.
  • Enterprise Backup and Archiving: Leveraging its high scalability and cost-effectiveness, distributed storage emerges as an ideal choice for enterprise backup and long-term data archiving, ensuring data integrity and accessibility over extended periods.

In essence, distributed storage applications are revolutionizing data management practices, offering unparalleled scalability, resilience, and efficiency across a spectrum of industries.


In the rapidly evolving landscape of data centers, the shift from traditional storage systems to distributed storage solutions has become increasingly pivotal. This article explores the foundational knowledge of distributed storage, including its concepts, advantages, and classifications. We delve into mainstream technologies driving this innovation and highlight their diverse applications across various industries.

As a leading technology company specializing in network solutions and telecommunication products, FS leverages advanced distributed storage to enhance data center operations, offering scalable and efficient solutions tailored to modern enterprise needs. Join us to explore further insights and knowledge, and discover our range of storage products.