[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”4.27.4″ custom_margin=”0px||||false|false” custom_padding=”0px||0px||false|false” da_disable_devices=”off|off|off” global_colors_info=”{}” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row admin_label=”row” _builder_version=”4.27.2″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” width=”100%” custom_margin=”||0px||false|false” custom_padding=”0px||30px||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/zpesystems.com\/wp-content\/uploads\/2025\/01\/Out-of-Band-Management-for-AI.jpg” alt=”Out-of-Band Management for AI” title_text=”Out-of-Band Management for AI” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n
Artificial intelligence is transforming every corner of industry. Machine learning algorithms are optimizing global logistics, while generative AI tools like ChatGPT are reshaping everyday work and communications. Organizations are rapidly adopting AI, with the global AI market expected to reach $826 billion by 2030, <\/span>according to Statista<\/span><\/a>. While this growth is reshaping operations and outcomes for organizations in every industry, it brings significant challenges for managing the infrastructure that supports AI workloads.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.27.2″ _module_preset=”default” background_color=”#f4f4f4″ width=”auto” custom_padding=”15px||||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.27.2″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”|||15px|false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”15px|15px||15px|false|true” global_colors_info=”{}”]<\/p>\n AI is no longer a technology that lives only in science fiction. It\u2019s real, and it has quickly become crucial to business strategy and the overall direction of many industries. Gartner reports that 70% of enterprise executives are actively exploring generative AI for their organizations, and McKinsey highlights that <\/span>72% of companies have already adopted AI<\/span><\/a> in at least one business function.<\/span><\/p>\n It’s easy to understand why organizations are rapidly adopting AI. Here are a few examples of how AI is transforming industries:<\/span><\/p>\n AI is a powerful tool that can bring profound outcomes wherever it\u2019s used. But it requires a sophisticated infrastructure of power distribution, cooling systems, computing, GPUs, servers, and networking gear, and the challenge lies in managing this infrastructure.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.27.4″ _module_preset=”default” width=”auto” custom_margin=”||0px||false|false” custom_padding=”30px||0px||false|false” border_color_top=”#78828A” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.27.2″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”30px||0px||false|false” border_color_top=”#D6D6D6″ global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_font=”||||||||” custom_margin=”||0px||false|false” custom_padding=”15px||0px||false|true” global_colors_info=”{}”]<\/p>\n AI environments are complex, with workloads that are both resource-intensive and latency-sensitive. This means organizations face several challenges that are unique to AI:<\/span><\/p>\n <\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.27.4″ _module_preset=”default” width=”auto” custom_margin=”0px||||false|false” custom_padding=”0px||0px||true|false” border_color_top=”#78828A” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.27.2″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” custom_margin=”0px||0px||false|false” custom_padding=”15px||0px||false|false” border_width_top=”1px” border_color_top=”#D6D6D6″ global_colors_info=”{}”]<\/p>\n Out-of-band (OOB) management is a must-have for organizations scaling their AI capabilities. Unlike traditional in-band systems that rely on the production network, OOB operates independently to give teams uninterrupted access and control. They can remotely perform monitoring and maintenance tasks to AI infrastructure, <\/span>troubleshooting<\/span><\/a>, and complete system recovery even if the production network goes offline.<\/span><\/p>\n <\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” custom_margin=”15px||0px||false|false” custom_padding=”30px||0px||false|false” border_width_top=”1px” border_color_top=”#D6D6D6″ global_colors_info=”{}”]<\/p>\n There\u2019s no shortage of use cases for AI, but organizations often overlook implementing out-of-band in their environment. Aside from using OOB in AI data centers, here are some real-world use cases of out-of-band management for AI.<\/span><\/p>\n Developers of self-driving technology find it difficult to manage their high-density AI clusters, especially because outages delay testing and development. By implementing OOB management, these developers can reduce recovery times from hours to minutes and shorten development timelines.<\/span><\/p>\n Banks deploy AI to detect and combat fraud, but these power-hungry systems often lead to inefficient energy usage in the data center. With OOB management, they can gain transparency into GPU and CPU utilization. Not only can they eliminate energy waste, but they can optimize resources to improve model processing speeds.<\/span><\/p>\n Universities run AI research on supercomputers, but this strains the underlying infrastructure with high temperatures that can cause failures. OOB management can provide real-time visibility into air temperature, device fan speed, and cooling systems to prevent infrastructure failures.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.27.4″ _module_preset=”default” background_color=”rgba(120,130,138,0.15)” custom_margin=”0px||0px||false|false” custom_padding=”0px||0px||false|false” da_disable_devices=”off|off|off” global_colors_info=”{}” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row column_structure=”3_5,2_5″ _builder_version=”4.27.4″ _module_preset=”default” background_color=”#214C64″ width=”auto” custom_margin=”30px||30px||true|false” custom_padding=”0px||||false|false” border_color_top=”#78828A” locked=”off” global_colors_info=”{}”][et_pb_column type=”3_5″ _builder_version=”4.27.2″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_font=”||||||||” text_text_color=”#FFFFFF” custom_padding=”15px|30px|15px|30px|true|true” border_color_top=”#D6D6D6″ global_colors_info=”{}”]<\/p>\n Out-of-band management is the key to having reliable, high-performing AI infrastructure. But what does it look like? What devices does it work with? How do you implement it?<\/span><\/p>\n Download our whitepaper <\/span>Solving AI Infrastructure Challenges with Out-of-Band Management<\/span><\/i> for answers. You\u2019ll also get Nvidia\u2019s SuperPOD reference design along with a list of devices that integrate with out-of-band. Click the button for your instant download.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”2_5″ _builder_version=”4.27.2″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/zpesystems.com\/wp-content\/uploads\/2025\/01\/SolutionGuide-OOBforAI.png” alt=”SolutionGuide-OOBforAI” title_text=”SolutionGuide-OOBforAI” url=”https:\/\/go.zpesystems.com\/rs\/004-BTR-463\/images\/Solution-Guide-Solving-AI-Infrastructure-Challenges-with-OOBM.pdf” _builder_version=”4.27.4″ _module_preset=”default” locked=”off” global_colors_info=”{}”][\/et_pb_image][et_pb_button button_url=”https:\/\/go.zpesystems.com\/rs\/004-BTR-463\/images\/Solution-Guide-Solving-AI-Infrastructure-Challenges-with-OOBM.pdf” button_text=”Download Whitepaper” button_alignment=”center” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_button][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.27.4″ _module_preset=”default” custom_margin=”15px||15px||true|false” custom_padding=”0px||0px||true|false” da_disable_devices=”off|off|off” global_colors_info=”{}” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row _builder_version=”4.27.4″ _module_preset=”default” width=”auto” custom_margin=”0px||30px||false|false” custom_padding=”0px||||false|false” border_color_top=”#78828A” border_color_bottom=”#B5B5B5″ locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.27.2″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”30px||||false|false” border_color_top=”#D6D6D6″ global_colors_info=”{}”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Out-of-band management makes AI infrastructure resilient and efficient. Read our post and download our whitepaper to see how it works.<\/p>\n","protected":false},"author":5,"featured_media":227810,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","content-type":"","footnotes":""},"categories":[89,32,87,98,165,88,103,102,156,101,84,93,82,83,99,100,90,112,134],"tags":[],"class_list":["post-227741","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-actionable-data","category-datacenter-management","category-data-center-resilience","category-data-logging","category-edge-computing","category-failover-connectivity","category-improve-network-security","category-increase-productivity","category-micro-segmentation","category-minimize-impact-of-disruptions","category-monitoring-reporting","category-network-automation","category-out-of-band-management","category-power-management","category-remote-network-management","category-streamline-deployments","category-vendor-neutral-platform","category-zero-touch-provisioning","category-zero-trust-security"],"yoast_head":"\nThe Rapid Growth of AI Adoption<\/h2>\n
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Infrastructure Challenges Unique to AI<\/h2>\n
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The Role of Out-of-Band Management in AI<\/h2>\n
How OOB Management Solves Key Challenges:<\/h3>\n
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Use Cases: Out-of-Band Management for AI<\/h2>\n
1. Autonomous Vehicle R&D<\/h3>\n
2. Financial Services Firms<\/h3>\n
3. University AI Labs<\/h3>\n
Download Our Guide, Solving AI Infrastructure Challenges with Out-of-Band Management<\/i><\/h2>\n
Resources for Out-of-Band Management and AI<\/h2>\n
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