Micro-service automatic telescoping system and method, corresponding equipment and storage medium

Abstract

The invention discloses a micro-service automatic telescoping system and method, corresponding equipment and a storage medium, and the system comprises a monitoring module which is used for monitoringthe execution of a service logic code in each online micro-service copy, carrying out the statistics of the number of service requests, and providing a monitoring result query interface in a servicemode; an acquisition module which is used for regularly polling the monitoring result query interface of each micro-service copy and acquiring the real-time access traffic of the service request; a storage module which is used for storing the collected real-time access traffic in a database; a conversion module which is used for converting the service request real-time access traffic of the same micro service into a monitoring index of the HPA adaptive to the Kubernetes; and an expansion and contraction module which is used for automatically expanding and contracting the capacity of the corresponding micro-service based on a preset HPA capacity expansion and contraction rule according to the monitoring indexes. According to the system, the micro-service can be more accurately and automatically expanded and contracted, different resource requirements in different periods are dynamically met, and the utilization efficiency of resources is improved.

Description

technical field [0001] The present application relates to the field of electrical digital data processing, and in particular to a microservice automatic scaling system, method, corresponding equipment and storage medium. Background technique [0002] With the prevalence of microservice software architecture, the original single software application is often split into multiple microservices with high cohesion, low coupling, and stateless characteristics. With the continuous development of business, the number of microservices will also increase accordingly. How to coordinate various services running online and guarantee the SLA of the service is a big challenge to the service architecture and operation and maintenance personnel. With the expansion of business scale, some microservices have tight resource usage during peak traffic periods, while other unpopular services have excessive resource usage. In order to reasonably allocate the resource occupancy of each service, dy...

AI Technical Summary

Problems solved by technology

[0003] One of the existing dynamic scaling micro-service solutions is human intervention. This solution can accurately identify traffic peaks and valleys, but it often takes a long time and the response time is relatively slow, which increases the labor cost of operation and maintenance personnel and increases The unexpected risk factors caused by human misoperation; the other is automatic service elastic scaling through Kubernetes HPA. However, this solution identifies business peaks and valleys by using computing resources, that is, CPU and / or memory resource occupancy as an indicator, which is not accurate. It represents the peak and trough of business traffic, and there may be unnecessary expansion and contraction. For example, unnecessary expansion may be caused by a short-term increase in CPU or memory, and there are certain deficiencies.

Images