Method and system for dynamically adjusting system resources in distributed micro-service scene

Abstract

The invention discloses a system resource dynamic adjustment method and system in a distributed micro-service scene. The adjustment method comprises the following steps: setting a critical value and an adjustment weight value of each micro-service resource performance in a monitoring system; when the monitoring system recognizes that the current resource of the micro-service reaches a critical value, a resource index adjusting request is sent to the API gateway; and after receiving the resource adjustment weight request, the API gateway calls a cloud platform established by Kubernetes to carry out a micro-service resource adjustment request, and service node resources are updated. The problems that the system operation resources possibly cannot meet the current operation due to sudden increase of the system request page view, so that the request blockage response is overtime, and even the system crashes and cannot operate are solved.

Description

Technical Field

[0001] The present invention relates to the field of banking and financial systems, and in particular to a method and system for dynamically adjusting system resources in a distributed microservice scenario. Background Art

[0002] Distributed architectures are increasingly common in banking and financial systems. Within these systems, numerous inter-system calls occur. It's common for a system to connect to multiple systems, leading to high traffic volumes at certain times. This is especially true for systems connected to the internet. Currently, a common approach is to conduct a peak user traffic survey before a system goes live, determining the maximum resource requirements for system operation and configuring the system accordingly.

[0003] Due to the large number of interconnected systems, researching the traffic volume of all interconnected systems wastes a lot of manpower and resources, and often results in insufficient research. This leads to inadequate allocation of system resources. When traffic suddenly increases, the system's allocated resources may not be sufficient, causing request congestion, response timeouts, or even system crashes. This severely impacts user experience and can even lead to significant losses. The ability to flexibly and promptly increase system resources in response to surges in traffic has become a technical barrier to today's financial systems. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed to provide a method and system for dynamically adjusting system resources in a distributed microservice scenario to overcome the above problems or at least partially solve the above problems.

[0005] According to one aspect of the present invention, a method for dynamically adjusting system resources in a distributed microservice scenario is provided, the adjustment method comprising:

[0006] Set critical values ​​and adjustment weights for the performance of each microservice resource in the monitoring system;

[0007] When the monitoring system identifies that the current resources of a microservice have reached a critical value, it sends a resource indicator adjustment request to the API gateway;

[0008] After receiving the resource adjustment weight request, the API gateway calls the cloud platform built by Kubernetes to make a microservice resource adjustment request and update the service node resources.

[0009] Optionally, setting the critical value and adjustment weight value of each microservice resource performance in the system in the monitoring system specifically includes: when the microservice resource indicator is adjusted, the critical value monitored by the monitoring system is also adjusted.

[0010] Optionally, sending a resource indicator adjustment request to the API gateway includes: adjusting resource indicator parameters required by the system to facilitate the platform to adjust the service node according to the indicator.

[0011] Optionally, calling the cloud platform built by Kubernetes to make a microservice resource adjustment request includes:

[0012] The cloud platform for deploying and running system microservice applications uses Kubernetes technology to build a system operation system. Microservices are packaged through Dockerfile to generate image packages and uploaded to the cloud platform for direct operation. The cloud platform supports real-time changes to the nodes and resource environment where the images run.

[0013] The present invention also provides a system for dynamically adjusting system resources in a distributed microservice scenario, applying the above-mentioned method for dynamically adjusting system resources in a distributed microservice scenario. The adjustment system includes:

[0014] The setting module is used to set the critical value and adjustment weight value of each microservice resource performance in the monitoring system;

[0015] The first request module is used to send a resource indicator adjustment request to the API gateway when the monitoring system identifies that the current resources of the microservice have reached a critical value;

[0016] The second request module is used to call the cloud platform built by Kubernetes to make microservice resource adjustment requests and update service node resources after the API gateway receives the resource adjustment weight request;

[0017] The processing module is used by the cloud platform to adjust the resources of the microservices that receive the resource adjustment request.

[0018] The present invention provides a method and system for dynamically adjusting system resources in a distributed microservice scenario. The adjustment method includes: setting critical values ​​and adjustment weight values ​​for the performance of each microservice resource in the system in a monitoring system; when the monitoring system recognizes that the current resources of a microservice have reached the critical value, sending a resource indicator adjustment request to the API gateway; after receiving the resource adjustment weight request, the API gateway calls the cloud platform built by Kubernetes to make a microservice resource adjustment request and update the service node resources. This solves the problem that a sudden increase in system request access may cause the system operating resources to be unable to meet the current operation, resulting in request congestion and response timeout, and even causing the system to crash and become unable to operate.

[0019] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 This is a flowchart of a method for dynamically adjusting system resources in a distributed microservices scenario provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0023] The terms "comprises" and "comprising" and any variations thereof in the description, embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0024] The technical solution of the present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0025] The present invention provides a method for dynamically adjusting system resources in a distributed microservice scenario, which is used to solve the problem that a sudden increase in system request access volume may cause the system operating resources to be unable to meet the current operation, resulting in request congestion and response timeout, or even causing the system to crash and become unable to operate.

[0026] like Figure 1 As shown in the figure, a method for dynamically adjusting system resources in a distributed microservice scenario:

[0027] Set the critical values ​​and weights that need to be adjusted for each microservice resource performance in the monitoring system;

[0028] Including: When the microservice resource indicators are adjusted, the critical values ​​monitored by the monitoring system are also adjusted.

[0029] When the monitoring system identifies that the current resources of a microservice have reached a critical value, it sends a resource indicator adjustment request to the API gateway;

[0030] Including: The request sent to the API gateway includes the resource indicator parameters required by the system to facilitate the platform to adjust the service nodes according to the indicators.

[0031] After receiving the resource weight adjustment request, the API gateway calls the cloud platform built by Kubernetes to make microservice resource adjustment requests and update service node resources;

[0032] Including: The cloud platform for deploying and running system microservice applications uses Kubernetes technology to build a system operation system. Microservices are packaged through Dockerfile to generate image packages and uploaded to the cloud platform for direct operation. The cloud platform supports real-time changes to the nodes and resource environment where the images run.

[0033] The present invention provides a system for dynamically adjusting system resources in a distributed microservice scenario, comprising:

[0034] The setting module sets the critical values ​​of each microservice resource performance in the system and the resource indicator values ​​that need to be adjusted in the monitoring system;

[0035] The first request module sends a resource indicator adjustment request to the API gateway when the monitoring system identifies that the current resources of the microservice have reached a critical value;

[0036] In the second request module, after receiving the resource indicator adjustment request, the API gateway calls the cloud platform built by Kubernetes to make the microservice resource adjustment request;

[0037] In the processing module, the cloud platform adjusts the resources of the microservices that receive resource adjustment requests.

[0038] Beneficial effect: Solve the problem that the system operation resources may not be able to meet the current operation due to a sudden increase in system request access, causing request congestion and response timeout, or even causing the system to crash and be unable to run.

[0039] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for dynamically adjusting system resources in a distributed microservice scenario, characterized in that: The adjustment method includes: Set critical values ​​and adjustment weights for the performance of each microservice resource in the monitoring system; When the monitoring system identifies that the current resources of a microservice have reached a critical value, it sends a resource adjustment indicator request to the API gateway; After receiving the resource weight adjustment request, the API gateway calls the cloud platform built by Kubernetes to make microservice resource adjustment requests and update service node resources; The cloud platform adjusts resources for the microservices that receive resource adjustment requests.

2. The method for dynamically adjusting system resources in a distributed microservice scenario according to claim 1, characterized in that: The setting of the critical value and adjustment weight value of each microservice resource performance in the monitoring system specifically includes: when the microservice resource indicator is adjusted, the critical value monitored by the monitoring system is also adjusted.

3. The method for dynamically adjusting system resources in a distributed microservice scenario according to claim 1, characterized in that: The sending of the resource indicator adjustment request to the API gateway includes: adjusting the resource indicator parameters required by the system to facilitate the platform to adjust the service node according to the indicator.

4. The method for dynamically adjusting system resources in a distributed microservice scenario according to claim 1, characterized in that: The calling of the cloud platform built by Kubernetes to make a microservice resource adjustment request includes: The cloud platform for deploying and running system microservice applications uses Kubernetes technology to build a system operation system. Microservices are packaged through Dockerfile to generate image packages and uploaded to the cloud platform for direct operation. The cloud platform supports real-time changes to the nodes and resource environment where the images run.

5. A system for dynamically adjusting system resources in a distributed microservice scenario, applying a method for dynamically adjusting system resources in a distributed microservice scenario as described in any one of claims 1 to 4, characterized in that: The adjustment system comprises: The setting module is used to set the critical value and adjustment weight value of each microservice resource performance in the monitoring system; The first request module is used to send a resource indicator adjustment request to the API gateway when the monitoring system identifies that the current resources of the microservice have reached a critical value; The second request module is used to call the cloud platform built by Kubernetes to make microservice resource adjustment requests and update service node resources after the API gateway receives the resource adjustment weight request; The processing module is used by the cloud platform to adjust the resources of the microservices that receive the resource adjustment request.

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