This morning, Shanghai once again conducted a nationwide nucleic acid screening, braving the rain, everyone in their respective neighborhoods lined up for a new round of nucleic acid. However, the nucleic acid code on the "with the application" has collapsed again! So, many people worked hard to line up for an hour of queuing in vain, to wait for the repair and then do the nucleic acid 。。。。。。

This is a completely avoidable accident from our professional point of view in O&M. I guess the organization with the bid should not have applied "intelligent operation and maintenance" to the system maintenance, and even did not recognize the importance of intelligent operation and maintenance.

In the past, the traditional centralized monitoring method only collects alarm information centrally, and the cluttered and redundant alarm events make the programmers always on the way to another emergency treatment. Especially in the current Internet era, the surge in data volume so that the efficiency of traditional technology and management tools plummeted, the difficulty of operation and maintenance management has gradually increased, then the system crash, downtime is also expected.

And in this urgent need, with the help of artificial intelligence means to empower the traditional operation and maintenance has become an urgent task, AIOps intelligent operation and maintenance came into being. AIOps intelligent operation and maintenance adopts advanced AI technology, giving full play to the machine learning ability, assisting operation and maintenance personnel to improve the performance of operation and maintenance, in the enterprise greatly saves the cost of manpower, at the same time, but also for the protection of business.

Particularly in the alarm, the risk of system changes may not be avoided, but there can be early warning and more quickly locate the root cause. Because, operation and maintenance data processing analysis due to its special requirements, not only is the data size, and data processing timeliness requirements are extremely high, this is because many operation and maintenance data need to be in the high-speed streaming engine to carry out complex aggregation, computation, judgment and comparison of operations to meet the requirements of the machine learning algorithms, which is also a feature of the operation and maintenance work scenarios, that is, it must be "fast! This is also a feature of the O&M scenario, which is that it must be "fast", otherwise once the failure occurs for a long time, everything will be lost in the analysis.

And intelligent O&M is a new kind of digital O&M capability, and will be a must for digital transformation. Intelligent operation and maintenance compared to the traditional operation and maintenance mode, can be in the operation and maintenance of data governance, business digital risk, operation and maintenance of labor costs and business side of the impact of the four aspects of the essence of the efficiency of the improvement.

In terms of alerting,

1.? Improved business assurance capabilities by enabling more timely and effective detection of problems with lower labor costs;

2.? The ability to gain deeper insight and analyze alarms, improving troubleshooting effectiveness;

3.? The ability to utilize the wisdom of human-machine integration to establish a mechanism for continuous improvement, and provides a guiding direction for further intelligent transformation in other areas such as basic indicator monitoring and log analysis.

Intelligent O&M development is in full swing, and Gartner foresees it as the next generation of O&M, believing that by 2022, more than 50% of the world's enterprises will be using AIOps to replace the traditional means of IT O&M management.

The spreading epidemic is not only a test of epidemic prevention and control measures, but also a test of smart cities. In the tide of enterprise digital transformation, "smart" is the way operation and maintenance should have been.