Artificial intelligence (AI) has been a trendy issue in recent years, due to its capacity to produce code and poetry, among other things. Yet, the influence of AI on data centers has received insufficient attention.
While AI-powered data center monitoring solutions are necessary, they are not at the forefront of AI technology. Better physical security, efficient data center energy management, automated capacity management, effective incident response, and growing demand for AI-friendly data center hardware are some of the ways AI might affect the data center sector.
Preventing unauthorized access to data centers’ assets by intruders has traditionally been a costly affair requiring on-site security professionals to improve physical security. But, by analyzing data to detect physical incursions, AI can assist lower these expenses. AI can interpret video streams in real time, allowing it to identify persons who pose a risk and relieving humans of the burden of constantly watching videos.
Due to the multiple variables involved in energy management within data centers, finding and addressing energy concerns has generally needed people to do detailed investigations. With today’s powerful AI capabilities, AI can now take on some of these decision-making tasks. Although data center operators may still need humans to validate AI tool suggestions, AI may take the lead in controlling energy usage rather than depending on people to manually measure energy consumption and handle difficulties.
Managing aspects such as expanding infrastructure and ensuring physical space is in accordance with market demand has traditionally been a manual procedure in order to automate capacity management in data centers. But, AI may help in this process by analyzing the numerous factors that go into determining how much capacity data centers will require for various reasons and at different times. This would enable operators to make more informed judgments about capacity management.
When it comes to effective incident response, reacting to events is critical when problems develop in a data center. Management teams have previously developed incident response “playbooks” that detail how to tackle various sorts of difficulties. Yet, AI can analyze circumstances and develop answers faster than humans, especially when there is no predefined response playbook.
The growing need for sophisticated AI technologies has resulted in a huge increase in demand for data center hardware particularly suited for effectively performing AI workloads. Data center operators will gain significantly in the future by catering to this market niche, especially as AI-optimized hardware is not widely available from public clouds.
The sources for this piece include an article in DataCenterKnowledge.
