Data Centers have evolved from being just a storage facility to a business IT infrastructure. As data centers are seen as a supercomputer, modern data centers use multiple servers to optimize further and boost their processing and computing power. Almost every organization these days needs a data center to process tasks and information every day.
Artificial Intelligence (AI) & Machine Learning (ML)
Technologies such as Artificial Intelligence and Machine Learning are beginning to enter different computing applications revolutionizing businesses’ data center management.
AI powered data centers will help companies to drive data-driven decision making. AI in data centers can significantly improve data security as these centers are more vulnerable to cyber threats. AI also identifies normal behavior and detects cyber risks based on abnormalities and deviation in the networks.
Machine learning-powered systems could potentially contribute to predictive and preventive maintenance. They can provide Cooling efficiency by improving energy efficiency, controlling temperature and adjusting cooling systems.
AI and machine learning can also be used to monitor server performance, network congestions and disk utilization that help detect and envisage data outages. Thus, AI and machine learning revolution can enhance data center infrastructure and facilitate more intelligent and automated data management.
Reason why AI could revolutionize the Data center:
- Enhanced Cyber Security
- Better Management
- Cooling Efficiency
- High Density Servers
Benefits of ML in Data Center
- Efficiency Analysis
- Capacity Planning
- Risk Analysis
- Customer Churn Analysis
- Impact Analysis and Modeling
Edge computing is a distributed, open IT architecture that features decentralized processing power, enabling mobile computing and Internet of Things (IoT) technologies. In edge computing, data is processed by the device or by a local computer or server, rather than being transmitted to a data center.
Why Edge Computing?
Edge computing enables data stream acceleration, including real-time data processing without latency. It allows smart applications and devices to respond to data almost instantaneously without any lag time.
Edge computing allows efficient data processing in that large amounts of data can be processed near the source, reducing Internet bandwidth usage. This eliminates costs and ensures that applications can be used effectively in remote locations. In addition, the ability to process data without ever putting it into a public cloud adds a useful layer of security for sensitive data.
Benefits of Edge Computing
- Minimal Latency
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