How machine learning and AI are changing data center management - 5 minutes read
How machine learning and AI are changing data center management
Data center environments must stay consistent regarding things like humidity and temperature. Otherwise, the costly equipment inside them could begin malfunctioning. Moreover, data center clients want assurances that the valuable information stored within a facility will be available whenever they need it, and maintaining consistency comes into play there, too.
Here are four ways machine learning and artificial intelligence (AI) are upending data center management.
Energy efficiency is a constant concern for data center managers. However, thanks to recent high-tech advances, it's a more achievable goal. In 2016, Google started working on a project that involved using AI to meet climate control needs in the brand's data centers.
The resulting system takes snapshots of conditions by collecting data from thousands of sensors every five minutes. Then, deep learning neural networks use that information to predict how combinations of future actions would affect energy consumption. Each option has a confidence rating, and low-confidence choices automatically get eliminated.
Google's engineers say the system taught them new best practices to follow, plus they believe the focus on energy efficiency will have a positive effect on climate change mitigation.
Paying attention to cybersecurity is essential for most of today's businesses, including data centers. Analysts believe AI will have a significant impact concerning from hackers. Since AI processes vast amounts of information much faster than humans could, it's beneficial in helping data center operators detect anomalies.
AI and machine learning shouldn't replace the cybersecurity pros who work in data centers, but those technologies supplement human expertise. Algorithms often detect things people miss, helping them proactively respond to possible threats.
As mentioned earlier, clients look for data center providers that can meet their needs and give them the kind of reliability they need to do business with confidence. AI presents opportunities for data center companies to implement the technology and then demonstrate to clients that their high-tech updates set them apart in the marketplace.
This shift will likely affect businesses in numerous ways, such as when representatives research or enterprise resource planning software. If they choose to install AI-based features at their data center facilities or work with companies that offer them, the clients can then focus on those offerings to demonstrate their preparedness for the future.
Some pioneering companies offer AI services similar to the ones Google uses for energy efficiency. One of them is . Thanks to businesses like that one, data center executives have more options for upgrading their data centers and implementing AI, whether those facilities are on-premise or cloud-based.
AI and machine learning can also cut down or eliminate the number of staff members needed to work at data centers. Or, it could allow the employees to focus on more rewarding and stimulating tasks instead of emphasizing continual monitoring to check for problems.
One example of what the future looks like is Microsoft's underwater data center, being investigated under an initiative called Project Natick. It uses AI to screen for abnormalities that could mean equipment failure. Plus, AI algorithms compile information to help engineers pinpoint the positive and negative effects of deploying a data center underwater.
One of the most impressive things about Project Natick is how the team behind the trial designed it to function for five years without maintenance. It's too early to know how feasible it is to expect data centers to run that long without the usual pattern of ongoing human intervention. But, the data gathered for this project will undoubtedly shape upcoming projects like it.
Data centers are instrumental to the functionality of the websites, apps and gadgets that people use daily. As this list shows, AI and machine learning are positively affecting the quest for hassle-free data center management -- and they seem poised to continue doing so moving forward.
is a senior writer at MakeUseOf and a freelance writer for Digital Trends. To read more from Kayla, visit her websiteproductivitybytes.com.
Source: Betanews.com
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Machine learning • Artificial intelligence • Data center • Data center • Natural environment • Humidity • Temperature • Data center • Information • Machine learning • Artificial intelligence • Artificial intelligence • Data center • Management • Efficient energy use • Data center • Management • High tech • Goal • Google • Project management • Artificial intelligence • HVAC • Brand • Data center • System • Sensor • Deep learning • Artificial neural network • Information theory • Google • Engineering • System • Best practice • Efficient energy use • Positivism • Climate change mitigation • Computer security • Data center • Artificial intelligence • Security hacker • Artificial intelligence • Information • Data center • Artificial intelligence • Machine learning • Computer security • Technology • Algorithm • Customer • Data center • Reliability engineering • Business • Artificial intelligence • Data center • Company • Technology • Customer • High tech • Business • Medical research • Enterprise resource planning • Artificial intelligence • Data center • Employment • Company • Customer • Innovation • Company • Artificial intelligence • Service (economics) • Google • Efficient energy use • Business • Data center • Data center • Artificial intelligence • On-premises software • Cloud computing • Artificial intelligence • Machine learning • Employment • Employment • Microsoft • Data center • Natick, Massachusetts • Artificial intelligence • Military technology • Artificial intelligence • Algorithm • Compiler • Information • Military engineering • Causality • Data center • Natick, Massachusetts • Mobile app • Gadget • Time management • Artificial intelligence • Machine learning • Data center • MakeUseOf • Digital Trends •
Data center environments must stay consistent regarding things like humidity and temperature. Otherwise, the costly equipment inside them could begin malfunctioning. Moreover, data center clients want assurances that the valuable information stored within a facility will be available whenever they need it, and maintaining consistency comes into play there, too.
Here are four ways machine learning and artificial intelligence (AI) are upending data center management.
Energy efficiency is a constant concern for data center managers. However, thanks to recent high-tech advances, it's a more achievable goal. In 2016, Google started working on a project that involved using AI to meet climate control needs in the brand's data centers.
The resulting system takes snapshots of conditions by collecting data from thousands of sensors every five minutes. Then, deep learning neural networks use that information to predict how combinations of future actions would affect energy consumption. Each option has a confidence rating, and low-confidence choices automatically get eliminated.
Google's engineers say the system taught them new best practices to follow, plus they believe the focus on energy efficiency will have a positive effect on climate change mitigation.
Paying attention to cybersecurity is essential for most of today's businesses, including data centers. Analysts believe AI will have a significant impact concerning from hackers. Since AI processes vast amounts of information much faster than humans could, it's beneficial in helping data center operators detect anomalies.
AI and machine learning shouldn't replace the cybersecurity pros who work in data centers, but those technologies supplement human expertise. Algorithms often detect things people miss, helping them proactively respond to possible threats.
As mentioned earlier, clients look for data center providers that can meet their needs and give them the kind of reliability they need to do business with confidence. AI presents opportunities for data center companies to implement the technology and then demonstrate to clients that their high-tech updates set them apart in the marketplace.
This shift will likely affect businesses in numerous ways, such as when representatives research or enterprise resource planning software. If they choose to install AI-based features at their data center facilities or work with companies that offer them, the clients can then focus on those offerings to demonstrate their preparedness for the future.
Some pioneering companies offer AI services similar to the ones Google uses for energy efficiency. One of them is . Thanks to businesses like that one, data center executives have more options for upgrading their data centers and implementing AI, whether those facilities are on-premise or cloud-based.
AI and machine learning can also cut down or eliminate the number of staff members needed to work at data centers. Or, it could allow the employees to focus on more rewarding and stimulating tasks instead of emphasizing continual monitoring to check for problems.
One example of what the future looks like is Microsoft's underwater data center, being investigated under an initiative called Project Natick. It uses AI to screen for abnormalities that could mean equipment failure. Plus, AI algorithms compile information to help engineers pinpoint the positive and negative effects of deploying a data center underwater.
One of the most impressive things about Project Natick is how the team behind the trial designed it to function for five years without maintenance. It's too early to know how feasible it is to expect data centers to run that long without the usual pattern of ongoing human intervention. But, the data gathered for this project will undoubtedly shape upcoming projects like it.
Data centers are instrumental to the functionality of the websites, apps and gadgets that people use daily. As this list shows, AI and machine learning are positively affecting the quest for hassle-free data center management -- and they seem poised to continue doing so moving forward.
is a senior writer at MakeUseOf and a freelance writer for Digital Trends. To read more from Kayla, visit her websiteproductivitybytes.com.
Source: Betanews.com
Powered by NewsAPI.org
Keywords:
Machine learning • Artificial intelligence • Data center • Data center • Natural environment • Humidity • Temperature • Data center • Information • Machine learning • Artificial intelligence • Artificial intelligence • Data center • Management • Efficient energy use • Data center • Management • High tech • Goal • Google • Project management • Artificial intelligence • HVAC • Brand • Data center • System • Sensor • Deep learning • Artificial neural network • Information theory • Google • Engineering • System • Best practice • Efficient energy use • Positivism • Climate change mitigation • Computer security • Data center • Artificial intelligence • Security hacker • Artificial intelligence • Information • Data center • Artificial intelligence • Machine learning • Computer security • Technology • Algorithm • Customer • Data center • Reliability engineering • Business • Artificial intelligence • Data center • Company • Technology • Customer • High tech • Business • Medical research • Enterprise resource planning • Artificial intelligence • Data center • Employment • Company • Customer • Innovation • Company • Artificial intelligence • Service (economics) • Google • Efficient energy use • Business • Data center • Data center • Artificial intelligence • On-premises software • Cloud computing • Artificial intelligence • Machine learning • Employment • Employment • Microsoft • Data center • Natick, Massachusetts • Artificial intelligence • Military technology • Artificial intelligence • Algorithm • Compiler • Information • Military engineering • Causality • Data center • Natick, Massachusetts • Mobile app • Gadget • Time management • Artificial intelligence • Machine learning • Data center • MakeUseOf • Digital Trends •