Managing large data future data center toward intelligent Management

Now, IT administrators need to organize a lot of statistics on tracking networks, storage and computing devices, and software programs to help them decide what resources to adjust or diagnose problems. Future data centers will be self optimized, using powerful analytics to detect patterns of dynamic data, and then make improvements accordingly.

Looking ahead again, it is clear that improving the automation of computing Systems management will improve the efficiency of the next generation computing system.

For now, while the enterprise deploys sensors in all of the data center's devices, IT administrators still need to organize a lot of statistics on tracking networks, storage and computing devices, and software programs to help them decide what resources to adjust or diagnose problems. The future datacenter will be self optimized, relying on analytics to understand how the system works, or to figure out how to improve the system to make it work better when it's not working.

Future IT directors will only need to set goals and rules based on business priorities. With these goals and rules, machines and software programs will be monitored from an integrated perspective. Http://www.aliyun.com/zixun/aggregation/8510.html "The feedback received by the >it Manager will then be circulated to software tools in real time, and the software tools are based on their requirements for existing resources, business applications, The goal of the human administrator set the understanding of automatic adjustment.

Intelligent Data Center

The shift from a general data center to an intelligent data center is absolutely necessary. The rapid popularity of virtual technologies in the server, storage, and networking world means that dozens of or even tens of thousands of discrete tasks can be run on each device, and can be transferred from one machine to another as needed, which also means a lot of manual processing.

In addition, IT managers now buy more computing, storage, and networking capabilities than they actually need, so that the demand peaks are covered. By using smarter management systems, IT managers can choose to use more efficient devices while shutting down unnecessary devices.

Another key factor is data management. Currently, most business data is stored in separate systems. For example, financial data is stored in the financial system, customer service information is stored in the CRM system, and orders are kept in the trading system. Such practices can lead to duplication of effort and create problems that make it difficult for businesses to understand basic information, such as who consumers are and what they need. To complicate things, new data will be emerging, such as sensors, cameras and the internet itself, which will create new data that needs to be sorted, analyzed, stored, and processed.

Review data

In order to meet these challenges, companies must look at data in a new perspective. Just as all server computers and storage devices in enterprise data centers can be handled as a single, large system, as is the case with the data itself, which is called a "virtualized data service"-a technical platform for managing, consolidating, and analyzing information on new and traditional data resources.

As enterprise IT departments transform data into Data services, enterprise employees will be more likely to get the information they need, simply by requiring the software application to provide specific data, or some type of information, and then the information will be delivered directly to the employee's desktop, simple and quick. Everyone who receives and processes the data does not need to know the exact location of the data, and they can use the data with ease.

This ease of use, and the integrity of the data, enables people to gain greater value from the data that the enterprise collects and stores.

By analyzing trends, predicting future activities based on past results, and observing the relevance of different activities, companies can use data to achieve business objectives and growth operations. In addition, the enterprise can collect and analyze the large-scale data stream collected in real time.

The use of powerful analytics to detect dynamic Data patterns can help improve jobs in all walks of life, such as banks can better detect and prevent fraud in credit card transactions, and government departments can redistribute traffic to avoid traffic jams. These can be achieved by automating IT systems and by improving the collection and digestion of large amounts of data.

(Responsible editor: The good of the Legacy)