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Cloud native system observation method and system based on information entropy
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An information entropy and observation system technology, applied in the cloud-native field, can solve the problems of changing and updating index weights, relying on engineers, and not being able to achieve universality, etc., and achieve the effects of high accuracy, easy observation, and strong objectivity
Active Publication Date: 2021-08-06
EISOO SOFTWARE
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[0012] First, it can only monitor the basic information of middleware components, such as CPU usage and network traffic, but cannot extract and display higher-level semantic information;
[0013] The second is that for custom indicators, they often rely too much on the personal experience of engineers and cannot achieve versatility; custom indicators are often static and cannot update the indicator weight with system changes, resulting in the need to reset the weight after a period of time; Indicators are usually local and cannot take into account global hierarchical information
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Embodiment 1
[0067] A cloud-native system observation method based on information entropy, such as figure 1 ,include:
[0068] 1) Construct a system topology diagram including each component node of the cloud native system;
[0069] 2) Calculate the global entropy of the cloud native system and the node importance factor and component entropy of component nodes;
[0070] 3) Calculate the observation index ARO according to the global entropy, node importance factor and component entropy;
[0071] 4) Observe the operating status of each component node in the system topology diagram through the observation index ARO.
[0072] The calculation formula of the observation index ARO is:
[0073] AROs i =g*n i *e i
[0074] Among them, ARO i is the observation indicator of the i-th component node, g is the global entropy of the cloud native system, n i is the node importance factor of the i-th component node, e i is the component entropy of the i-th component node, g, n i and e i Obtain...
[0096] The topology construction module is used for the system topology diagram of the cloud-native system, which includes each component node of the cloud-native system;
[0097] The indicator calculation module includes a global statistical unit, a weight statistical unit, a local statistical unit, a measurement statistical unit and a time series statistical unit;
[0098] The global computing unit is used to calculate the global entropy g of the cloud native system;
[0099] The weight statistics unit is used to count the node importance factor n of each component node;
[0100] The local statistical unit is used to count the component entropy e of each component node;
[0101] The measurement statistics unit is used to calculate the observation index ARO of each component node;
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Abstract
The invention relates to a cloud native systemobservation method and system based on information entropy. The method comprises the following steps: constructing a systemtopological graph comprising each component node of a cloud native system; and observing the operation condition of each component node in the topological graph of the system through the observation index ARO. Compared with the prior art, the observation index ARO is based on the alarm log and the information entropy, more aggregated information can be provided for observers from the system perspective, multi-dimensional consideration is carried out from the global and local perspective through the combination of the global entropy, the node importance factor and the component entropy, the real operation condition of the system can be displayed more effectively. And meanwhile, the method can dynamically change along with the operation of the cloud native system, manual weight setting is not needed, automation is realized, and the efficiency is high.
Description
technical field [0001] The present invention relates to the cloud native field, in particular to an information entropy-based cloud native system observation method and system. Background technique [0002] The development of servitization, as well as the continuous evolution of various technologies such as containerized arrangement, microservice framework, and service mesh, provide technical support for distributed services, but building microservices alone is not enough. For a complete set of technologies As far as the system is concerned, in addition to development, it also needs strong support from operation and maintenance. With the continuous evolution of the microservice architecture, the number of applications and services continues to increase, and the call relationship becomes more and more complex. It is impossible to describe the system deployment under the microservice architecture through a static architecture diagram. Therefore, from the perspective of operati...
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