{"id":18341,"date":"2025-12-10T10:04:55","date_gmt":"2025-12-10T10:04:55","guid":{"rendered":"https:\/\/www.fibermall.com\/blog\/?p=18341"},"modified":"2025-12-10T10:05:02","modified_gmt":"2025-12-10T10:05:02","slug":"key-design-principles-for-ai-clusters-scale-efficiency-and-flexibility","status":"publish","type":"post","link":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm","title":{"rendered":"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility"},"content":{"rendered":"\n<p>In the era of trillion-parameter AI models, building high-performance AI clusters has become a core competitive advantage for cloud providers and AI enterprises. This article deeply analyzes the unique network requirements of AI workloads, compares architectural differences between AI clusters and traditional data centers, and introduces two mainstream network design paradigms proposed by Arista \u2014 <strong>Endpoint-Scheduled (NSF)<\/strong>\u00a0and <strong>Switch-Scheduled (DSF)<\/strong>\u00a0\u2014 while providing practical guidance on topology selection and <a href=\"https:\/\/www.fibermall.com\/store-21994-800g-ndr-infiniband.htm\" target=\"_blank\" rel=\"noreferrer noopener\">800G interconnection<\/a> technology for different scales.<\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_76 ez-toc-wrap-left counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Network_Requirements_and_Traffic_Characteristics_of_AI_Clusters\" >Network Requirements and Traffic Characteristics of AI Clusters<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Core_Requirements_Extreme_Scale_Efficiency_and_Flexibility\" >Core Requirements: Extreme Scale, Efficiency, and Flexibility<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Four_Unique_Characteristics_of_AI_Traffic\" >Four Unique Characteristics of AI Traffic<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Architectural_Differences_Between_AI_Clusters_and_Traditional_Data_Center_Clusters\" >Architectural Differences Between AI Clusters and Traditional Data Center Clusters<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Two_Core_Network_Design_Paradigms_for_AI_Clusters\" >Two Core Network Design Paradigms for AI Clusters<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Endpoint-Scheduled_Architecture_NSF_%E2%80%93_Network_Scheduled_Fabric\" >Endpoint-Scheduled Architecture (NSF \u2013 Network Scheduled Fabric)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Switch-Scheduled_Architecture_DSF_%E2%80%93_Direct_Switch_Fabric\" >Switch-Scheduled Architecture (DSF \u2013 Direct Switch Fabric)<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Topology_and_800G_Interconnect_Technology_Selection\" >Topology and 800G Interconnect Technology Selection<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Multi-Plane_Topology_%E2%80%94_The_Foundation_for_Million-Scale_XPUs\" >Multi-Plane Topology \u2014 The Foundation for Million-Scale XPUs<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#800G_Interconnect_Technology_Selection_by_Scenario\" >800G Interconnect Technology Selection by Scenario<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Conclusion_and_Future_Trends\" >Conclusion and Future Trends<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Key_Takeaways_for_Architecture_Selection\" >Key Takeaways for Architecture Selection<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\/#Future_Trends\" >Future Trends<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Network_Requirements_and_Traffic_Characteristics_of_AI_Clusters\"><\/span><strong>Network Requirements and Traffic Characteristics of AI Clusters<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Core_Requirements_Extreme_Scale_Efficiency_and_Flexibility\"><\/span><strong>Core Requirements: Extreme Scale, Efficiency, and Flexibility<\/strong><strong><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<figure class=\"wp-block-image aligncenter size-large is-resized\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"491\" src=\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/Network-Requirements-and-Traffic-Characteristics-of-AI-Clusters-1024x491.png\" alt=\"Network Requirements and Traffic Characteristics of AI Clusters\" class=\"wp-image-18346\" style=\"width:800px\" srcset=\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/Network-Requirements-and-Traffic-Characteristics-of-AI-Clusters-1024x491.png 1024w, https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/Network-Requirements-and-Traffic-Characteristics-of-AI-Clusters-300x144.png 300w, https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/Network-Requirements-and-Traffic-Characteristics-of-AI-Clusters-768x368.png 768w, https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/Network-Requirements-and-Traffic-Characteristics-of-AI-Clusters.png 1080w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>As AI models rapidly scale to trillions of parameters, training and inference clusters place unprecedented demands on the underlying network:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Ultra-Large-Scale Expansion<\/strong>: Must support collaborative computing across hundreds of thousands to millions of XPUs (GPUs\/NPUs), covering everything from single-rack to multi-data-center scenarios.<\/li>\n\n\n\n<li><strong>High Efficiency and Ultra-Low Latency<\/strong>: Frequent collective communication operations (e.g., AllReduce, AllGather) between XPUs require microsecond-level latency and \u226590% bandwidth utilization.<\/li>\n\n\n\n<li><strong>Heterogeneous Adaptation<\/strong>: Must seamlessly support XPUs from different vendors, varying rack power budgets, and mixed workloads (training + inference), avoiding performance degradation due to the \u201cwooden barrel effect\u201d (overall performance limited by the slowest node).<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Four_Unique_Characteristics_of_AI_Traffic\"><\/span><strong>Four Unique Characteristics of AI Traffic<\/strong><strong><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Compared with traditional data center traffic, AI traffic exhibits distinctly different patterns that directly shape network design decisions:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>High Synchronization<\/strong>: Training jobs exchange gradients and parameters in fixed cycles, resulting in \u201clong-burst, highly synchronized\u201d traffic that easily triggers Incast congestion.<\/li>\n\n\n\n<li><strong>Heavy RDMA Dependence<\/strong>: Requires a Lossless Network**: RDMA over Converged Ethernet (RoCEv2) is the de facto standard; any packet loss triggers retransmission and dramatic latency spikes.<\/li>\n\n\n\n<li><strong>Stable Flow Characteristics<\/strong>: Individual flows have long lifetimes (from job start to completion), extremely high rates, and low entropy (relatively fixed paths), rendering traditional ECMP load-balancing inefficient.<\/li>\n\n\n\n<li><strong>Reliability Shifted to the Network<\/strong>: AI applications offload reliability responsibility entirely to the network \u2014 even a single packet loss can corrupt an entire training iteration.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Architectural_Differences_Between_AI_Clusters_and_Traditional_Data_Center_Clusters\"><\/span><strong>Architectural Differences Between AI Clusters and Traditional Data Center Clusters<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Traditional clusters are \u201cCPU-server-centric,\u201d with the network primarily serving horizontal traffic among data ingestion, storage, and compute. In contrast, modern AI clusters are \u201cXPU-centric\u201d and clearly separate:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Frontend Network<\/strong>&nbsp;\u2013 CPU-to-CPU and CPU-to-storage traffic (similar to traditional DC).<\/li>\n\n\n\n<li><strong>Backend Network (Rail)<\/strong>&nbsp;\u2013 High-bandwidth, low-latency XPU-to-XPU interconnect, which becomes the performance bottleneck and primary design focus.<\/li>\n<\/ul>\n\n\n\n<p>This dual-network architecture significantly increases overall complexity.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Two_Core_Network_Design_Paradigms_for_AI_Clusters\"><\/span><strong>Two Core Network Design Paradigms for AI Clusters<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Arista classifies current AI cluster backend networks into two mainstream paradigms based on where scheduling responsibility resides:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Endpoint-Scheduled_Architecture_NSF_%E2%80%93_Network_Scheduled_Fabric\"><\/span><strong>Endpoint-Scheduled Architecture (NSF \u2013 Network Scheduled Fabric)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Core Concept<\/strong><strong><\/strong><\/h4>\n\n\n\n<p>All scheduling intelligence resides at the endpoints (NIC\/DPU\/IPU). The network fabric only performs basic packet forwarding \u2014 essentially an optimized extension of traditional Ethernet.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Key Technical Characteristics<\/strong><strong><\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Topology: Classic flattened Spine-Leaf or Super-Spine Clos, switches only need high radix and 800G ports.<\/li>\n\n\n\n<li>Endpoint Requirements: NICs must support Dynamic Load Balancing (DLB), Adaptive Routing, packet spraying, and end-to-end congestion control (ECN\/WRED).<\/li>\n\n\n\n<li>Advantages: Simple architecture, flexible cabling, fully compatible with existing Ethernet ecosystem, ideal for small-to-medium clusters (\u226410K XPUs).<\/li>\n\n\n\n<li>Limitations: Strong vendor lock-in at the NIC layer; scheduling complexity explodes at very large scale, prone to load imbalance and hot spots.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Switch-Scheduled_Architecture_DSF_%E2%80%93_Direct_Switch_Fabric\"><\/span><strong>Switch-Scheduled Architecture (DSF \u2013 Direct Switch Fabric)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Core Concept<\/strong><strong><\/strong><\/h4>\n\n\n\n<p>Scheduling responsibility is completely offloaded to the network switches. Endpoints use commodity NICs, while the fabric achieves lossless, high-performance delivery through cell-based switching and credit-based flow control.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Key Technical Characteristics<\/strong><strong><\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Topology: Leaf switches handle cell segmentation, VOQ (Virtual Output Queuing), scheduling, and credit management; Spine\/Super-Spine switches are simple low-power forwarders.<\/li>\n\n\n\n<li>Lossless Mechanism: Credit Request\/Grant protocol + PFC + ECN guarantees zero buffer overflow end-to-end.<\/li>\n\n\n\n<li>Scaling Capability: A single system supports 4.6K \u00d7 800G or 9.2K \u00d7 400G XPUs; two-tier extension reaches 32K+ GPUs.<\/li>\n\n\n\n<li>Advantages: NIC vendor agnostic, extremely stable performance at ultra-large scale, precise congestion control.<\/li>\n\n\n\n<li>Limitations: Higher switch hardware complexity and cost; cabling must align with cell-switching requirements.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Topology_and_800G_Interconnect_Technology_Selection\"><\/span><strong>Topology and 800G Interconnect Technology Selection<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Multi-Plane_Topology_%E2%80%94_The_Foundation_for_Million-Scale_XPUs\"><\/span><strong>Multi-Plane Topology \u2014 The Foundation for Million-Scale XPUs<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>To achieve linear scaling to hundreds of thousands or millions of XPUs, Arista strongly recommends the <strong>Multi-Plane<\/strong>&nbsp;architecture:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Each plane is an independent Spine-Leaf fabric (typically 4K\u201310K XPUs).<\/li>\n\n\n\n<li>Multiple planes operate in parallel and are interconnected via an aggregation layer.<\/li>\n\n\n\n<li>10 planes can easily exceed 100K XPUs while maintaining fault isolation and linear bandwidth scaling.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"800G_Interconnect_Technology_Selection_by_Scenario\"><\/span><strong>800G Interconnect Technology Selection by Scenario<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full is-resized\"><img decoding=\"async\" width=\"991\" height=\"581\" src=\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/800G-Interconnect-Technology-Selection-by-Scenario.png\" alt=\"800G Interconnect Technology Selection by Scenario\" class=\"wp-image-18347\" style=\"width:800px\" srcset=\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/800G-Interconnect-Technology-Selection-by-Scenario.png 991w, https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/800G-Interconnect-Technology-Selection-by-Scenario-300x176.png 300w, https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/800G-Interconnect-Technology-Selection-by-Scenario-768x450.png 768w\" sizes=\"(max-width: 991px) 100vw, 991px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Scenario<\/strong><strong><\/strong><\/td><td><strong>Recommended Technology<\/strong><strong><\/strong><\/td><td><strong>Distance<\/strong><strong><\/strong><\/td><td><strong>Power Consumption<\/strong><strong><\/strong><\/td><td><strong>Cost<\/strong><strong><\/strong><\/td><td><strong>Notes<\/strong><strong><\/strong><\/td><\/tr><tr><td>Intra-Rack (&lt;2 m)<\/td><td>DAC \/ ACC<\/td><td>\u22642 m<\/td><td>Extremely low<\/td><td>Lowest<\/td><td>Direct Attach Copper \/ Active Copper Cable<\/td><\/tr><tr><td>Intra-Row \/ Short-Reach<\/td><td>LPO \/ LRO<\/td><td>\u226450 m<\/td><td>Very low<\/td><td>Low<\/td><td>Linear-drive Pluggable Optics \u2014 significant power saving vs DSP<\/td><\/tr><tr><td>Medium-Reach (\u2264500 m)<\/td><td>DSP Coherent<\/td><td>\u2264500 m<\/td><td>Moderate<\/td><td>Medium<\/td><td>Traditional DSP optics, mature ecosystem<\/td><\/tr><tr><td>Long-Reach (2\u2013100 km)<\/td><td>DSP + DWDM<\/td><td>\u2264100 km+<\/td><td>Higher<\/td><td>Higher<\/td><td>Required for multi-building or campus-level clusters<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Conclusion_and_Future_Trends\"><\/span><strong>Conclusion and Future Trends<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Key_Takeaways_for_Architecture_Selection\"><\/span><strong>Key Takeaways for Architecture Selection<\/strong><strong><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u226410K XPUs \u2192 Prefer <strong>Endpoint-Scheduled (NSF)<\/strong>&nbsp;for cost and deployment flexibility.<\/li>\n\n\n\n<li>\u226532K XPUs \u2192 Must adopt <strong>Switch-Scheduled (DSF)<\/strong>&nbsp;to guarantee stable performance and eliminate endpoint bottlenecks.<\/li>\n\n\n\n<li>Million-scale \u2192 <strong>Multi-Plane + DSF<\/strong>&nbsp;is currently the only proven production-grade solution.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Future_Trends\"><\/span><strong>Future Trends<\/strong><strong><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Deeper optimization of collective communication primitives (AllReduce, AllGather, etc.) at the network layer.<\/li>\n\n\n\n<li>Standardized benchmarking for MPI\/NCCL\/RCCL over real AI networks.<\/li>\n\n\n\n<li>Integration of emerging standards such as Ultra Ethernet Consortium (UEC) and UALink to drive the industry from \u201ccustom silos\u201d toward open, standardized, ultra-low-latency interconnects.<\/li>\n<\/ul>\n\n\n\n<p>Building the next-generation AI supercomputer is no longer just about buying more GPUs \u2014 the network has become the decisive battleground for performance, scalability, and total cost of ownership.<\/p>\n\n\n\n<p><\/p>\n<style>\r\n\r\n        .lwrp.link-whisper-related-posts{\r\n            \r\n            margin-top: 40px;\nmargin-bottom: 30px;\r\n        }\r\n        .lwrp .lwrp-title{\r\n            \r\n            \r\n        }\r\n        .lwrp .lwrp-description{\r\n            \r\n            \r\n\r\n        }\r\n        .lwrp .lwrp-list-container{\r\n        }\r\n        .lwrp .lwrp-list-multi-container{\r\n            display: flex;\r\n        }\r\n        .lwrp .lwrp-list-double{\r\n            width: 48%;\r\n        }\r\n        .lwrp .lwrp-list-triple{\r\n            width: 32%;\r\n        }\r\n        .lwrp .lwrp-list-row-container{\r\n            display: flex;\r\n            justify-content: space-between;\r\n        }\r\n        .lwrp .lwrp-list-row-container .lwrp-list-item{\r\n            width: calc(100% - 20px);\r\n        }\r\n        .lwrp .lwrp-list-item:not(.lwrp-no-posts-message-item){\r\n            \r\n            list-style: decimal;\r\n        }\r\n        .lwrp .lwrp-list-item img{\r\n            max-width: 100%;\r\n            height: auto;\r\n        }\r\n        .lwrp .lwrp-list-item.lwrp-empty-list-item{\r\n            background: initial !important;\r\n        }\r\n        .lwrp .lwrp-list-item .lwrp-list-link .lwrp-list-link-title-text,\r\n        .lwrp .lwrp-list-item .lwrp-list-no-posts-message{\r\n            \r\n                \r\n        }\r\n        @media screen and (max-width: 480px) {\r\n            .lwrp.link-whisper-related-posts{\r\n                \r\n                \r\n            }\r\n            .lwrp .lwrp-title{\r\n                \r\n                \r\n            }\r\n            .lwrp .lwrp-description{\r\n                \r\n                \r\n            }\r\n            .lwrp .lwrp-list-multi-container{\r\n                flex-direction: column;\r\n            }\r\n            .lwrp .lwrp-list-multi-container ul.lwrp-list{\r\n                margin-top: 0px;\r\n                margin-bottom: 0px;\r\n                padding-top: 0px;\r\n                padding-bottom: 0px;\r\n            }\r\n            .lwrp .lwrp-list-double,\r\n            .lwrp .lwrp-list-triple{\r\n                width: 100%;\r\n            }\r\n            .lwrp .lwrp-list-row-container{\r\n                justify-content: initial;\r\n                flex-direction: column;\r\n            }\r\n            .lwrp .lwrp-list-row-container .lwrp-list-item{\r\n                width: 100%;\r\n            }\r\n            .lwrp .lwrp-list-item:not(.lwrp-no-posts-message-item){\r\n                \r\n                \r\n            }\r\n            .lwrp .lwrp-list-item .lwrp-list-link .lwrp-list-link-title-text,\r\n            .lwrp .lwrp-list-item .lwrp-list-no-posts-message{\r\n                \r\n                    \r\n            }\r\n        }<\/style>\r\n<div id=\"link-whisper-related-posts-widget\" class=\"link-whisper-related-posts lwrp\">\r\n            <h3 class=\"lwrp-title\">Related Posts<\/h3>    \r\n        <div class=\"lwrp-list-container\">\r\n                                            <ul class=\"lwrp-list lwrp-list-single\">\r\n                    <li class=\"lwrp-list-item\"><a href=\"https:\/\/www.fibermall.com\/blog\/advances-in-400g-optical-transmission.htm\" class=\"lwrp-list-link\"><span class=\"lwrp-list-link-title-text\">Advances in 400G Optical Transmission Technology<\/span><\/a><\/li><li class=\"lwrp-list-item\"><a href=\"https:\/\/www.fibermall.com\/blog\/ai-high-performance-computing-and-optical-module-trends.htm\" class=\"lwrp-list-link\"><span class=\"lwrp-list-link-title-text\">Artificial Intelligence: High-Performance Computing and High-Speed Optical Module Technology Trends<\/span><\/a><\/li><li class=\"lwrp-list-item\"><a href=\"https:\/\/www.fibermall.com\/blog\/qsfp28-switch.htm\" class=\"lwrp-list-link\"><span class=\"lwrp-list-link-title-text\">High-Performance Managed Switch with 4x 100G QSFP28 and 6 x 100GbE Ports &#8211; Best Networking Solutions<\/span><\/a><\/li><li class=\"lwrp-list-item\"><a href=\"https:\/\/www.fibermall.com\/blog\/infiniband-vs-ethernet-the-battle-between-broadcom-and-nvidia.htm\" class=\"lwrp-list-link\"><span class=\"lwrp-list-link-title-text\">InfiniBand vs. Ethernet: The Battle Between Broadcom and NVIDIA for AI Scale-Out Dominance<\/span><\/a><\/li><li class=\"lwrp-list-item\"><a href=\"https:\/\/www.fibermall.com\/blog\/mikrotik-qsfp28.htm\" class=\"lwrp-list-link\"><span class=\"lwrp-list-link-title-text\">Everything You Need to Know About Mikrotik QSFP28 Modules and Routers<\/span><\/a><\/li>                <\/ul>\r\n                        <\/div>\r\n<\/div>","protected":false},"excerpt":{"rendered":"<p>In the era of trillion-parameter AI models, building high-performance AI clusters has become a core competitive advantage for cloud providers and AI enterprises. This article deeply analyzes the unique network requirements of AI workloads, compares architectural differences between AI clusters and traditional data centers, and introduces two mainstream network design paradigms proposed by Arista \u2014 [&hellip;]<\/p>\n","protected":false},"author":227,"featured_media":18354,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":"","_wpscppro_dont_share_socialmedia":false,"_wpscppro_custom_social_share_image":0,"_facebook_share_type":"default","_twitter_share_type":"default","_linkedin_share_type":"default","_pinterest_share_type":"default","_linkedin_share_type_page":"default","_instagram_share_type":"default","_medium_share_type":"default","_threads_share_type":"default","_google_business_share_type":"default","_selected_social_profile":[{"id":"skM9ewvR8O","platform":"linkedin","platformKey":0,"name":"Jason Xue","type":"person","thumbnail_url":"https:\/\/media.licdn.com\/dms\/image\/C5603AQErPqKD0j6qBg\/profile-displayphoto-shrink_100_100\/0\/1599138392315?e=1723075200&v=beta&t=joEkh1OeKQ0F-QpAPv4xxQyBdGlHyccIQZauRSs6RvU","share_type":"default"}],"_wpsp_enable_custom_social_template":false,"_wpsp_social_scheduling":{"enabled":false,"datetime":null,"platforms":[],"status":"template_only","dateOption":"today","timeOption":"now","customDays":"","customHours":"","customDate":"","customTime":"","schedulingType":"absolute"},"_wpsp_active_default_template":true},"categories":[2],"tags":[],"class_list":["post-18341","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.13 (Yoast SEO v25.8) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility - fibermall.com<\/title>\n<meta name=\"description\" content=\"In the era of trillion-parameter AI models, building high-performance AI clusters has become a core competitive advantage for cloud providers and AI enterprises.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility\" \/>\n<meta property=\"og:description\" content=\"In the era of trillion-parameter AI models, building high-performance AI clusters has become a core competitive advantage for cloud providers and AI\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\" \/>\n<meta property=\"og:site_name\" content=\"fibermall.com\" \/>\n<meta property=\"article:published_time\" content=\"2025-12-10T10:04:55+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-10T10:05:02+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"900\" \/>\n\t<meta property=\"og:image:height\" content=\"600\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Catherine\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Catherine\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\"},\"author\":{\"name\":\"Catherine\",\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/person\/bd2cf8d53f883c88f6ebaa5c3ed1258d\"},\"headline\":\"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility\",\"datePublished\":\"2025-12-10T10:04:55+00:00\",\"dateModified\":\"2025-12-10T10:05:02+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\"},\"wordCount\":903,\"publisher\":{\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg\",\"articleSection\":[\"Blog\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\",\"url\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\",\"name\":\"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility - fibermall.com\",\"isPartOf\":{\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg\",\"datePublished\":\"2025-12-10T10:04:55+00:00\",\"dateModified\":\"2025-12-10T10:05:02+00:00\",\"description\":\"In the era of trillion-parameter AI models, building high-performance AI clusters has become a core competitive advantage for cloud providers and AI enterprises.\",\"breadcrumb\":{\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#primaryimage\",\"url\":\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg\",\"contentUrl\":\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg\",\"width\":900,\"height\":600,\"caption\":\"ai cluster\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.fibermall.com\/blog.htm\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#website\",\"url\":\"https:\/\/www.fibermall.com\/blog.htm\/\",\"name\":\"fibermall.com\",\"description\":\"Optical Communication Expert\",\"publisher\":{\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.fibermall.com\/blog.htm\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#organization\",\"name\":\"fibermall.com\",\"url\":\"https:\/\/www.fibermall.com\/blog.htm\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2024\/12\/cropped-Fiber-Mall-Logo.jpg\",\"contentUrl\":\"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2024\/12\/cropped-Fiber-Mall-Logo.jpg\",\"width\":200,\"height\":67,\"caption\":\"fibermall.com\"},\"image\":{\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/logo\/image\/\"}},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/person\/bd2cf8d53f883c88f6ebaa5c3ed1258d\",\"name\":\"Catherine\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/3a11235a453567962b9c9bb843b31bb4396259dd8abad3f3c3758babd287d778?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/3a11235a453567962b9c9bb843b31bb4396259dd8abad3f3c3758babd287d778?s=96&d=mm&r=g\",\"caption\":\"Catherine\"},\"description\":\"Optical Communications Engineer\",\"sameAs\":[\"https:\/\/www.fibermall.com\/\"],\"url\":\"https:\/\/www.fibermall.com\/blog.htm?author=227\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility - fibermall.com","description":"In the era of trillion-parameter AI models, building high-performance AI clusters has become a core competitive advantage for cloud providers and AI enterprises.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm","og_locale":"en_US","og_type":"article","og_title":"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility","og_description":"In the era of trillion-parameter AI models, building high-performance AI clusters has become a core competitive advantage for cloud providers and AI","og_url":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm","og_site_name":"fibermall.com","article_published_time":"2025-12-10T10:04:55+00:00","article_modified_time":"2025-12-10T10:05:02+00:00","og_image":[{"width":900,"height":600,"url":"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg","type":"image\/jpeg"}],"author":"Catherine","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Catherine","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#article","isPartOf":{"@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm"},"author":{"name":"Catherine","@id":"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/person\/bd2cf8d53f883c88f6ebaa5c3ed1258d"},"headline":"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility","datePublished":"2025-12-10T10:04:55+00:00","dateModified":"2025-12-10T10:05:02+00:00","mainEntityOfPage":{"@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm"},"wordCount":903,"publisher":{"@id":"https:\/\/www.fibermall.com\/blog.htm\/#organization"},"image":{"@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#primaryimage"},"thumbnailUrl":"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg","articleSection":["Blog"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm","url":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm","name":"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility - fibermall.com","isPartOf":{"@id":"https:\/\/www.fibermall.com\/blog.htm\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#primaryimage"},"image":{"@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#primaryimage"},"thumbnailUrl":"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg","datePublished":"2025-12-10T10:04:55+00:00","dateModified":"2025-12-10T10:05:02+00:00","description":"In the era of trillion-parameter AI models, building high-performance AI clusters has become a core competitive advantage for cloud providers and AI enterprises.","breadcrumb":{"@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#primaryimage","url":"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg","contentUrl":"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2025\/12\/4df9f150e15d6f0ccb1129e4b1410ebc.jpg","width":900,"height":600,"caption":"ai cluster"},{"@type":"BreadcrumbList","@id":"https:\/\/www.fibermall.com\/blog\/key-design-principles-for-ai-clusters.htm#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.fibermall.com\/blog.htm"},{"@type":"ListItem","position":2,"name":"Key Design Principles for AI Clusters: Scale, Efficiency, and Flexibility"}]},{"@type":"WebSite","@id":"https:\/\/www.fibermall.com\/blog.htm\/#website","url":"https:\/\/www.fibermall.com\/blog.htm\/","name":"fibermall.com","description":"Optical Communication Expert","publisher":{"@id":"https:\/\/www.fibermall.com\/blog.htm\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.fibermall.com\/blog.htm\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.fibermall.com\/blog.htm\/#organization","name":"fibermall.com","url":"https:\/\/www.fibermall.com\/blog.htm\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/logo\/image\/","url":"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2024\/12\/cropped-Fiber-Mall-Logo.jpg","contentUrl":"https:\/\/www.fibermall.com\/blog\/wp-content\/uploads\/2024\/12\/cropped-Fiber-Mall-Logo.jpg","width":200,"height":67,"caption":"fibermall.com"},"image":{"@id":"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/logo\/image\/"}},{"@type":"Person","@id":"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/person\/bd2cf8d53f883c88f6ebaa5c3ed1258d","name":"Catherine","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.fibermall.com\/blog.htm\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/3a11235a453567962b9c9bb843b31bb4396259dd8abad3f3c3758babd287d778?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/3a11235a453567962b9c9bb843b31bb4396259dd8abad3f3c3758babd287d778?s=96&d=mm&r=g","caption":"Catherine"},"description":"Optical Communications Engineer","sameAs":["https:\/\/www.fibermall.com\/"],"url":"https:\/\/www.fibermall.com\/blog.htm?author=227"}]}},"_links":{"self":[{"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=\/wp\/v2\/posts\/18341","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=\/wp\/v2\/users\/227"}],"replies":[{"embeddable":true,"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=18341"}],"version-history":[{"count":4,"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=\/wp\/v2\/posts\/18341\/revisions"}],"predecessor-version":[{"id":18356,"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=\/wp\/v2\/posts\/18341\/revisions\/18356"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=\/wp\/v2\/media\/18354"}],"wp:attachment":[{"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=18341"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=18341"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.fibermall.com\/blog.htm\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=18341"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}