Smart Data Center \u2013 An Irreversible Trend<\/strong><\/p>\n\n\n AI in the Data Center is no longer a science fiction story. As early as 2018, Google pioneered the transfer of cooling control in several hyperscale data centers to an AI system, thereby reducing cooling energy consumption by up to 40%. This is proof that AI can bring clear and measurable benefits.<\/p><\/p>\n\n\n\n The COVID-19 pandemic has accelerated this trend, said Mr. Tabet, an expert from Dell Technologies. Businesses today are not only looking for stability but also for resilience and continuous operation, leading to the need for a \u201cDigital Data Center\u201d powered by AI.<\/p><\/p>\n\n\n\n Practical Application: Great Opportunity \u2013 But Many Barriers<\/strong><\/p>\n\n\n\n However, not every company has the scale and resources of Google. According to Daniel Bizo, senior analyst at 451 Research, most AI applications today are just support: analyzing equipment health, processing events, or optimizing cooling. Building a fully automated data center is still a long-term goal that requires years of development.<\/p><\/p>\n\n\n\n One of the biggest barriers is the human factor. According to Gartner, the lack of IT and data science skills is a serious problem in Data Center Operations teams. Michael Bushong of Juniper Networks says that \u201cthe biggest barrier is always people,\u201d not just due to a lack of skills but also due to a fear of change. Many IT engineers still believe that \u201cAI will take my job,\u201d leading to resistance or slow adoption of new technology.<\/p><\/p>\n\n\n\n AI and the Performance Problem \u2013 From Energy to Workload<\/strong><\/p>\n\n\n\n Optimize Energy Consumption<\/strong><\/em><\/p>\n\n\n Data Centers consume about 3% of the world\u2019s total electricity, contributing about 2% of greenhouse gas emissions. With such a significant number, AI is expected to help businesses not only save costs but also improve environmental responsibility.<\/p><\/p>\n\n\n\n AI systems can monitor, analyze, and predict cooling system anomalies \u2013 from uneven cold air distribution to inefficient HVAC operation. By automatically adjusting parameters, AI can improve performance without manual intervention.<\/p><\/p>\n\n\n\n Optimize Workload and Productivity<\/em><\/strong><\/p>\n\n\n\n AI also helps solve the problem of \u201cdoing more with less.\u201d Instead of just monitoring temperature or power consumption, modern systems can proactively move workloads away from overloaded or at-risk servers\u2014avoiding service disruptions.<\/p><\/p>\n\n\n\n \u201cThe focus is no longer on pure power management, but on optimizing performance per watt \u2013 which means working smarter,\u201d says StorageIO\u2019s Greg Schulz.<\/p><\/p>\n\n\n\n Proactive Equipment Monitoring \u2013 Smart Maintenance<\/em><\/strong><\/p>\n\n\n\n Modern Data Centers contain thousands of physical devices \u2013 from servers, storage devices to network switches. Manual monitoring and maintenance is nearly impossible. AI can help change this approach completely.<\/p><\/p>\n\n\n\n Machine learning algorithms can continuously collect telemetry data, detecting anomalies or trends that signal impending failure. Instead of scheduled maintenance, businesses can switch to condition-based maintenance, saving time and money.<\/p><\/p>\n\n\n\n In addition, AI also helps monitor \u201cconfiguration drift\u201d \u2013 a common phenomenon when device configurations are changed without strict control, which is a potential cause of security or performance errors.<\/p><\/p>\n\n\n\n Enhanced Security \u2013 Rapid Detection and Response<\/em><\/strong><\/p>\n\n\n\n Data security is always a top priority for any Data Center. AI simplifies the security incident handling process by analyzing millions of events and alerts to filter out real threats.<\/p><\/p>\n\n\n\n AI can even detect unusual behavior in real time, isolate threats, and suggest immediate responses \u2013 something humans cannot do with huge amounts of data and requiring instantaneous responses.<\/p><\/p>\n\n\n\n The Future: Dynamic Workload Optimization<\/strong><\/p>\n\n\n AI can not only help manage physical infrastructure, but can also automatically make decisions about distributing workloads across multiple platforms \u2013 from physical servers to different cloud environments. The algorithm will consider many factors: performance, cost, security, regulations, and even environmental sustainability.<\/p><\/p>\n\n\n\n However, as Bushong points out, currently only hyperscale providers like Google, Amazon, or Microsoft have the resources to implement comprehensive workload optimization models. For conventional enterprise data centers, this path is still challenging.<\/p><\/p>\n\n\n\n AI is clearly the future of the Data Center, but to get there, businesses need to start with small changes \u2013 optimizing cooling systems, monitoring smart devices, or simply early warning of system failures.<\/p><\/p>\n\n\n\n Instead of chasing hype, experts recommend focusing on \u201cboring innovations\u201d\u2014but ones that deliver real value. Ultimately, success comes not from leaps and bounds, but from persistent incremental improvements.<\/p><\/p>","protected":false},"excerpt":{"rendered":" Tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o (AI) \u0111ang \u0111\u1ecbnh h\u00ecnh l\u1ea1i c\u00e1ch c\u00e1c doanh nghi\u1ec7p qu\u1ea3n l\u00fd h\u1ea1 t\u1ea7ng c\u00f4ng ngh\u1ec7 c\u1ee7a m\u00ecnh \u2013 \u0111\u1eb7c bi\u1ec7t l\u00e0 trong l\u0129nh v\u1ef1c Trung t\u00e2m D\u1eef li\u1ec7u. Khi th\u1ebf gi\u1edbi ng\u00e0y c\u00e0ng s\u1ed1 h\u00f3a, c\u00e1c doanh nghi\u1ec7p bu\u1ed9c ph\u1ea3i t\u1ed1i \u01b0u h\u00f3a v\u1eadn h\u00e0nh, n\u00e2ng cao hi\u1ec7u su\u1ea5t v\u00e0 gi\u1ea3m […]","protected":false},"author":1,"featured_media":6657,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[3,10],"tags":[],"class_list":["post-6656","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tin-tuc","category-tin-tuc-noi-bat"],"_links":{"self":[{"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/posts\/6656","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/comments?post=6656"}],"version-history":[{"count":5,"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/posts\/6656\/revisions"}],"predecessor-version":[{"id":6665,"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/posts\/6656\/revisions\/6665"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/media\/6657"}],"wp:attachment":[{"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/media?parent=6656"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/categories?post=6656"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dchhk.com\/en\/wp-json\/wp\/v2\/tags?post=6656"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"https:\/\/dchhk.com\/wp-content\/uploads\/2025\/04\/ai-server-racks-modern-data-center_1029744-309-1024x512.avif\")
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