Container platform resource monitoring method and device, container platform, equipment and medium

Abstract

The application provides a resource monitoring method and device of a container platform, a container platform, equipment and a medium. Specifically, in the cloud computing technology, a plurality of business clusters and a management and control cluster are deployed in the container platform. The method uses a first monitoring component in each business cluster to monitor a resource data collection component in each business cluster to obtain node resource usage data and cluster resource usage data collected by the resource data collection component; uses a second monitoring component in the management and control cluster to determine resource usage information of each business cluster and resource usage information of each node allocated to a private partition of each business cluster based on the node resource usage data and the cluster resource usage data uploaded by the first monitoring component; and uses a visual display component in the management and control cluster to display the resource usage information of each business cluster and the resource usage information of each node allocated to the private partition of each business cluster.

Description

Technical Field

[0001] This application relates to computer technology, specifically cloud computing technology, and more particularly to a resource monitoring method, apparatus, container platform, device, and medium for a container platform. Background Technology

[0002] Container platforms are application-centric and business-focused, providing capabilities for multiple data centers, multiple tenants, multiple environments, and multiple resource pools. They also enable resource management for hosts, storage, and networks, providing unified resource allocation and application deployment for tenants, with dynamic allocation and reclamation to ensure the rational use of resources.

[0003] Currently, existing monitoring solutions for container platforms can provide a visual representation of the overall resources of a single cluster within the platform. However, these solutions cannot monitor the resource usage of the corresponding resource pools when the container platform has multiple clusters and multiple private partition resource pools. Consequently, even when a single cluster has sufficient resources, applications in private partitions may fail to be created due to insufficient resources in the private partition resource pools, thus compromising the security and reliability of the service. Summary of the Invention

[0004] This application provides a resource monitoring method, apparatus, container platform, device, and medium for a container platform, which solves the problem in the prior art that the resource usage of a container platform with multiple clusters and multiple private partition resource pools cannot be monitored. The application achieves the technical effect of monitoring the resource usage information of one or more business clusters, as well as the resource usage information of each node of each business cluster allocated to the private partition.

[0005] On the one hand, this application provides a resource monitoring method for a container platform, wherein multiple business clusters and a management cluster are deployed in the container platform, and the method includes:

[0006] The first monitoring component in each of the above-mentioned business clusters is used to monitor the resource data acquisition component in each of the above-mentioned business clusters to obtain the resource usage data of the above-mentioned business clusters collected by the resource data acquisition component. The resource usage data includes: node resource usage data and cluster resource usage data.

[0007] Using the second monitoring component in the aforementioned control cluster, based on the node resource usage data and cluster resource usage data uploaded by the first monitoring component, the resource usage information of each of the aforementioned business clusters and the resource usage information of each node allocated to the private partition in each of the aforementioned business clusters are determined, wherein the second monitoring component and the first monitoring component in each of the aforementioned business clusters are communicatively connected.

[0008] The visualization components in the aforementioned management cluster are used to display the resource usage information of each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition by each of the aforementioned business clusters.

[0009] Furthermore, the first monitoring component in each of the aforementioned business clusters monitors the resource data acquisition component in each of the aforementioned business clusters, including:

[0010] The first monitoring component in each of the aforementioned business clusters is used to monitor the node resource data acquisition component in each of the aforementioned business clusters, so as to obtain the node resource usage data collected by the node resource data acquisition component, and

[0011] The first monitoring component in each of the aforementioned business clusters is used to monitor the cluster resource data acquisition component in each of the aforementioned business clusters, so as to obtain the cluster resource usage data collected by the aforementioned cluster resource data acquisition component.

[0012] Furthermore, the aforementioned visualization component is a resource overview dashboard, and the aforementioned method also includes:

[0013] The variable information of the above resource overview dashboard is pre-configured, including: data source, business cluster variables, and private partition variables;

[0014] In the aforementioned resource overview dashboard, multiple display panels are created for the aforementioned private partition, and corresponding query statements are configured for each of the aforementioned display panels. The aforementioned display panels include at least: a first panel for displaying node statistics, a second panel for displaying resource usage overview information of the private partition, and a third panel for displaying node resource usage overview information under the aforementioned private partition.

[0015] Furthermore, the variable information of the aforementioned pre-configured resource overview dashboard includes:

[0016] Configure the data sources that users can select in the resource overview dashboard mentioned above;

[0017] Configure the business cluster variable in the resource overview dashboard above so that users can select one or more business clusters to view;

[0018] Configure a private partition variable in the resource overview dashboard above so that users can select one or more private partitions to view.

[0019] Furthermore, the above method also includes:

[0020] In response to the private partition selected by the user in the first panel, obtain the query statement corresponding to the first panel.

[0021] Based on the query statement corresponding to the first panel above, calculate the number of nodes allocated by different business clusters in the private partition.

[0022] Furthermore, the above method also includes:

[0023] In response to the private partition selected by the user in the second panel, obtain the corresponding query statement for the second panel.

[0024] Based on the query statement corresponding to the second panel above, calculate the resource usage overview information corresponding to different business clusters in the private partition above. The resource usage overview information includes: total CPU computing resource usage, total memory computing resource usage, number of allocated CPU computing resources, number of allocated memory computing resources, CPU computing resource allocation rate, and memory computing resource allocation rate.

[0025] Furthermore, the above method also includes:

[0026] In response to the private partition selected by the user in the third panel, obtain the corresponding query statement for the third panel.

[0027] Based on the query statement corresponding to the second panel above, calculate the node resource usage overview information allocated to the private partition for each of the above business clusters. The node resource usage overview information includes: the total CPU computing resource usage of the node, the total memory computing resource usage of the node, the number of allocated CPU computing resources of the node, the number of allocated memory computing resources of the node, the actual utilization rate of the CPU computing resources of the node, and the actual utilization rate of the memory computing resources of the node.

[0028] On the other hand, this application provides a container platform, which includes:

[0029] Multiple business clusters, each of which is equipped with a first monitoring component and a resource data acquisition component. The first monitoring component in each of the aforementioned business clusters is used to monitor the resource data acquisition component to obtain the resource usage data of the aforementioned business cluster collected by the resource data acquisition component. The resource usage data includes node resource usage data and cluster resource usage data.

[0030] The management cluster is communicatively connected to each of the aforementioned business clusters. The management cluster is equipped with a second monitoring component and a visualization component. The second monitoring component is used to determine the resource usage information of each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition by each of the aforementioned business clusters, based on the node resource usage data and cluster resource usage data uploaded by the first monitoring component. The visualization component is used to display the resource usage information of each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition by each of the aforementioned business clusters.

[0031] On the other hand, this application provides a resource monitoring device for a container platform, wherein multiple business clusters and a management cluster are deployed in the container platform, and the device includes:

[0032] The monitoring module is used to monitor the resource data acquisition component in each of the aforementioned business clusters using the first monitoring component in each of the aforementioned business clusters, so as to obtain the resource usage data of the aforementioned business clusters collected by the resource data acquisition component, wherein the aforementioned resource usage data includes: node resource usage data and cluster resource usage data.

[0033] The determination module is used to use the second monitoring component in the above-mentioned control cluster to determine the resource usage information of each of the above-mentioned business clusters and the resource usage information of each node allocated to the private partition of each of the above-mentioned business clusters, based on the node resource usage data and the cluster resource usage data uploaded by the first monitoring component. The second monitoring component is communicatively connected to the first monitoring component in each of the above-mentioned business clusters.

[0034] The display module is used to display the resource usage information of each of the above-mentioned business clusters, as well as the resource usage information of each node allocated to the private partition by each of the above-mentioned business clusters, using the visualization display components in the aforementioned management cluster.

[0035] Furthermore, the aforementioned monitoring module includes:

[0036] The first monitoring unit is configured to use the first monitoring component in each of the aforementioned service clusters to monitor the node resource data acquisition component in each of the aforementioned service clusters, so as to obtain the node resource usage data collected by the node resource data acquisition component, and

[0037] The second monitoring unit is used to monitor the cluster resource data acquisition component in each of the aforementioned business clusters using the first monitoring component in each of the aforementioned business clusters, so as to obtain the cluster resource usage data collected by the aforementioned cluster resource data acquisition component.

[0038] Furthermore, the aforementioned visualization component is a resource overview dashboard, and the aforementioned device also includes:

[0039] The configuration module is used to pre-configure the variable information of the above resource overview dashboard, including: data source, business cluster variables, and private partition variables.

[0040] A creation module is used to create multiple display panels for the private partition in the resource overview dashboard, and to configure corresponding query statements for each display panel. The display panels include at least: a first panel for displaying node statistics, a second panel for displaying resource usage overview information of the private partition, and a third panel for displaying node resource usage overview information of the private partition.

[0041] Furthermore, the above configuration module includes:

[0042] The first configuration unit is used to configure the data source for user selection in the aforementioned resource overview dashboard;

[0043] The second configuration unit is used to configure business cluster variables in the above resource overview dashboard, so that users can select one or more business clusters to view.

[0044] The third configuration unit is used to configure private partition variables in the aforementioned resource overview dashboard, allowing users to select one or more private partitions to view.

[0045] Furthermore, the aforementioned device also includes:

[0046] The first acquisition module is used to acquire the query statement corresponding to the first panel in response to the private partition selected by the user in the first panel.

[0047] The first calculation module is used to calculate the number of nodes allocated by different business clusters in the private partition based on the query statement corresponding to the first panel.

[0048] Furthermore, the aforementioned device also includes:

[0049] The second acquisition module is used to acquire the query statement corresponding to the second panel in response to the private partition selected by the user in the second panel.

[0050] The second calculation module is used to calculate the resource usage overview information corresponding to different business clusters in the private partition based on the query statement corresponding to the second panel. The resource usage overview information includes: total CPU computing resources used, total memory computing resources used, number of allocated CPU computing resources, number of allocated memory computing resources, CPU computing resource allocation rate, and memory computing resource allocation rate.

[0051] Furthermore, the aforementioned device also includes:

[0052] The third acquisition module is used to retrieve the query statement corresponding to the third panel in response to the private partition selected by the user in the third panel.

[0053] The third calculation module is used to calculate the node resource usage overview information allocated to the private partition for each of the above-mentioned business clusters based on the query statement corresponding to the second panel. The node resource usage overview information includes: the total CPU computing resource usage of the node, the total memory computing resource usage of the node, the number of allocated CPU computing resources of the node, the number of allocated memory computing resources of the node, the actual utilization rate of the CPU computing resources of the node, and the actual utilization rate of the memory computing resources of the node.

[0054] On the other hand, this application provides an electronic device, including: a processor and a memory connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement any of the methods described above.

[0055] On the other hand, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement any of the methods described above.

[0056] On the other hand, this application provides a computer program product, including a computer program that, when executed by a processor, implements any of the methods described above.

[0057] This application provides a resource monitoring method, apparatus, container platform, device, and medium for a container platform. The resource monitoring method for a container platform provided in this application involves deploying multiple business clusters and a management cluster within the container platform. A first monitoring component in each business cluster monitors the resource data acquisition component in each business cluster to obtain resource usage data collected by the resource data acquisition component, namely node resource usage data and cluster resource usage data. Then, a second monitoring component in the management cluster, based on the node resource usage data and cluster resource usage data uploaded by the first monitoring component, determines the resource usage information of each business cluster, as well as the resource usage information of each node allocated to a private partition within each business cluster. Finally, a visualization component in the management cluster can be used to display the resource usage information of each of the aforementioned business clusters, and the resource usage information of each node allocated to the private partition within each of the aforementioned business clusters.

[0058] The resource monitoring method for container platforms provided in this application can solve the problem in the prior art that the resource usage of container platforms with multiple clusters and multiple private partition resource pools cannot be monitored. It can achieve the technical effect of monitoring the resource usage information of one or more business clusters, as well as the resource usage information of each node of each business cluster allocated to the private partition. Attached Figure Description

[0059] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0060] Figure 1 A schematic diagram of the architecture of a container platform provided in an embodiment of this application;

[0061] Figure 2 A schematic diagram of an optional container platform architecture provided for an embodiment of this application;

[0062] Figure 3 This is a flowchart illustrating a resource monitoring method for a container platform provided in an embodiment of the present invention;

[0063] Figure 4 This is a flowchart illustrating a resource monitoring method for a container platform provided in an embodiment of the present invention;

[0064] Figure 5 This is a flowchart illustrating a resource monitoring method for a container platform provided in an embodiment of the present invention;

[0065] Figure 6 A structural block diagram of a resource monitoring device for a container platform provided in this application embodiment;

[0066] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0067] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0068] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0069] First, let me explain the terms used in this application:

[0070] Kubernetes, or K8s for short, is an open-source container orchestration engine that uses the number 8 from "ubernete" to represent the eight characters in its name. It is used to manage containerized application platforms on multiple hosts in a cloud platform. It supports automated deployment, large-scale scalability, and application containerization management. The goal of Kubernetes is to make deploying containerized applications simple and efficient.

[0071] Private partition: It is a collection of multiple nodes in a multi-cluster. The platform provides namespace-level resource isolation based on business needs. It partitions the node resources used by the business by tagging and adding taints to provide the multi-resource pool capability of the container platform. Cluster nodes with private partitions are not allowed to be scheduled arbitrarily. Only members of the organization that has been allocated the private partition can use the partition, which ensures the physical isolation of important applications.

[0072] Prometheus, a monitoring component, is an open-source, complete monitoring solution used to collect and aggregate metrics as time-series data. It can monitor the Kubernetes platform while simultaneously monitoring applications deployed on it, and provides a suite of system tools and multi-dimensional monitoring metrics.

[0073] Grafana is a visualization component that provides dashboards and graph editors based on Graphite (an open-source, real-time graphing system for displaying time-series metrics) and InfluxDB (an open-source time-series database developed by InfluxData). Grafana is open-source visualization and analytics software that provides tools to transform time-series database (TSDB) data into beautiful graphs and visualizations. It offers features such as data visualization, alerts, and queries, allowing users to query collected data, visualize it, and receive timely notifications.

[0074] The resource monitoring method for container platforms provided in this application aims to solve the technical problem of existing technologies that cannot monitor the resource usage of container platforms with multiple clusters and multiple private partition resource pools. This resource monitoring method for container platforms can be applied to... Figure 1 The container platform shown.

[0075] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0076] like Figure 1 The diagram shows an architecture of a container platform 100, which includes:

[0077] Multiple business clusters, each of the aforementioned business clusters 200 is equipped with a first monitoring component 201 and a resource data acquisition component 202.

[0078] The management cluster 300 is communicatively connected to each of the aforementioned business clusters 200. The management cluster 300 is equipped with a second monitoring component 301 and a visualization component 302.

[0079] The first monitoring component 201 in each of the above-mentioned business clusters is used to monitor the above-mentioned resource data acquisition component 202 in order to obtain the resource usage data of the above-mentioned business clusters collected by the above-mentioned resource data acquisition component.

[0080] Optionally, the above resource usage data includes: node resource usage data and cluster resource usage data.

[0081] The second monitoring component 301 is used to determine the resource usage information of each of the above-mentioned business clusters and the resource usage information of each node of each of the above-mentioned business clusters allocated to the private partition based on the node resource usage data and the cluster resource usage data uploaded by the first monitoring component; the visualization component 302 is used to display the resource usage information of each of the above-mentioned business clusters and the resource usage information of each node of each of the above-mentioned business clusters allocated to the private partition.

[0082] Optionally, in this embodiment, the container platform can be a Kubernetes container cloud platform. The service cluster 200 in the container platform can be one or more.

[0083] In one example, a container cloud platform can be based on Docker container technology and combined with Kubernetes to achieve unified container orchestration and resource scheduling. It features intelligent dynamic resource scheduling and elastic scaling. It uses orchestration tools to manage container clusters and provides a complete set of functions such as application development, resource hosting and platform operation and maintenance, thereby improving the convenience of managing large-scale container clusters.

[0084] For example, in the Kubernetes container platform, multiple containers can be created, each running an application instance. Then, through the built-in load balancing strategy, the management, discovery, and access of this group of application instances can be achieved, and these details do not require complex manual configuration and processing by operations and maintenance personnel.

[0085] Optionally, the first monitoring component 201 in each of the aforementioned business clusters can be a Prometheus monitoring component. Prometheus provides an open-source system monitoring solution that can monitor the Kubernetes container cloud platform as well as the applications deployed on the Kubernetes container cloud platform, and provides a series of system toolsets and multi-dimensional monitoring metrics.

[0086] Optional, such as Figure 2 As shown, the resource data acquisition component 202 includes a node resource data acquisition component 203 and a cluster resource data acquisition component 204. The first monitoring component 201 in each of the aforementioned business clusters is used to monitor the node resource data acquisition component 203 to obtain node resource usage data, and to monitor the cluster resource data acquisition component 204 to obtain cluster resource usage data.

[0087] Optionally, the second monitoring component 301 in the control cluster 300 is communicatively connected to the first monitoring component 201 in each of the aforementioned service clusters 200. The second monitoring component 301 is used to receive node resource usage data and cluster resource usage data uploaded by each of the first monitoring components. Furthermore, based on the cluster resource usage data, the resource usage information of each of the aforementioned service clusters is determined, and based on the node resource usage data, the resource usage information of each node allocated to the private partition in each of the aforementioned service clusters is determined.

[0088] Optionally, the visualization component 302 mentioned above can be implemented using the visualization tool Grafana. This visualization component 302 is used to display the resource usage information of each of the above-mentioned business clusters, as well as the resource usage information of each node allocated to the private partition of each of the above-mentioned business clusters, in a visual display manner.

[0089] The multi-cluster resource monitoring and visualization solution for container platforms provided in this application enables the acquisition of resource usage information for each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition within each of the aforementioned business clusters, based on the Kubernetes container platform and the Prometheus monitoring component. Furthermore, the visualization tool Grafana is used to display the resource usage information for each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition within each of the aforementioned business clusters.

[0090] Still Figure 2 As shown in this embodiment, in multiple business clusters within the Kubernetes container platform, a first monitoring component 201 (e.g., a Prometheus monitoring component) is deployed in each cluster. All business clusters are equipped with resource data collection components such as a node resource data collection component 203 (e.g., Node-exporter) and a cluster resource data collection component 201 (e.g., a k8s cluster resource data collection component, Kube-state-metrics).

[0091] A second monitoring component 301 (e.g., a Prometheus monitoring component) is deployed in the management cluster 300 of the Kubernetes container platform to perform multi-service cluster monitoring data collection configuration, so as to obtain the resource usage data monitored by the first monitoring component 201 in multiple service clusters in the Kubernetes container platform. For example, the first monitoring component 201 is used to monitor the node resource usage data obtained by the node resource data collection component 203, and the cluster resource usage data obtained by the cluster resource data collection component 204.

[0092] In the Kubernetes container platform's management cluster 300, a visualization component 302 (e.g., Grafana visualization component) can also be deployed, which can display an overview of the resource usage of private partitions, as well as query and visualize the resource details of the private partition resource pool based on the visualization component.

[0093] Through this solution, for example, platform administrators and resource pool users of the container platform can intuitively view the resource usage and node status of each partition resource pool. They can quickly view abnormal node information and resource usage information of private partitions, which facilitates platform administrators to quickly replenish and adjust the resource usage of each system based on the current resource usage status, reduce the resource maintenance pressure on operation and maintenance personnel, ensure the continuous operation of business, and guarantee the security and reliability of services.

[0094] This application also provides a resource monitoring method for a container platform, wherein the container platform deploys multiple business clusters and a management cluster. Figure 3 This is a flowchart illustrating a resource monitoring method for a container platform provided in an embodiment of the present invention, as shown below. Figure 3 As shown, the method includes:

[0095] S101, using the first monitoring component in each of the above-mentioned business clusters, monitors the resource data acquisition component in each of the above-mentioned business clusters to obtain the resource usage data of the above-mentioned business clusters collected by the resource data acquisition component.

[0096] S102, using the second monitoring component in the aforementioned control cluster, based on the node resource usage data and cluster resource usage data uploaded by the first monitoring component, determine the resource usage information of each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition by each of the aforementioned business clusters.

[0097] S103, using the visualization display component in the aforementioned management cluster, displays the resource usage information of each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition by each of the aforementioned business clusters.

[0098] Optionally, the above resource usage data includes: node resource usage data and cluster resource usage data.

[0099] Optionally, the second monitoring component described above is communicatively connected to the first monitoring component in each of the aforementioned service clusters.

[0100] Optionally, in this embodiment, the container platform can be a Kubernetes container cloud platform. There can be one or more service clusters within the container platform. In each of the multiple service clusters within the Kubernetes container platform, a first monitoring component is deployed.

[0101] In one example, a container cloud platform can be based on Docker container technology and combined with Kubernetes to achieve unified container orchestration and resource scheduling. It features intelligent dynamic resource scheduling and elastic scaling. It uses orchestration tools to manage container clusters and provides a complete set of functions such as application development, resource hosting and platform operation and maintenance, thereby improving the convenience of managing large-scale container clusters.

[0102] For example, in the Kubernetes container platform, multiple containers can be created, each running an application instance. Then, through the built-in load balancing strategy, the management, discovery, and access of this group of application instances can be achieved, and these details do not require complex manual configuration and processing by operations and maintenance personnel.

[0103] Optionally, the first monitoring component in each of the aforementioned business clusters can be the Prometheus monitoring component. Prometheus provides an open-source system monitoring solution that can monitor both the Kubernetes container cloud platform and the applications deployed on the Kubernetes container cloud platform, and provides a series of system toolsets and multi-dimensional monitoring metrics.

[0104] Optionally, the aforementioned resource data acquisition components include: a node resource data acquisition component and a cluster resource data acquisition component. The first monitoring component in each of the aforementioned business clusters can monitor the node resource data acquisition component to obtain node resource usage data, and monitor the cluster resource data acquisition component to obtain cluster resource usage data.

[0105] Optionally, a second monitoring component is used to receive node resource usage data and cluster resource usage data uploaded by each of the first monitoring components. Then, based on the cluster resource usage data, the resource usage information of each of the aforementioned business clusters is determined, and based on the node resource usage data, the resource usage information of each node allocated to the private partition within each of the aforementioned business clusters is determined.

[0106] Optionally, the aforementioned visualization component can be implemented using the visualization tool Grafana. This visualization component is used to display the resource usage information of each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition of each of the aforementioned business clusters, in a visual display manner.

[0107] The multi-cluster resource monitoring and visualization solution for container platforms provided in this application enables the acquisition of resource usage information for each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition within each of the aforementioned business clusters, based on the Kubernetes container platform and the Prometheus monitoring component. Furthermore, the visualization tool Grafana is used to display the resource usage information for each of the aforementioned business clusters, as well as the resource usage information of each node allocated to the private partition within each of the aforementioned business clusters.

[0108] In one example, such as Figure 4 As shown, the first monitoring component in each of the aforementioned business clusters monitors the resource data acquisition component in each of the aforementioned business clusters, including:

[0109] S201, using the first monitoring component in each of the aforementioned service clusters, monitors the node resource data acquisition component in each of the aforementioned service clusters to obtain the node resource usage data collected by the node resource data acquisition component, and

[0110] S202, using the first monitoring component in each of the above-mentioned business clusters, monitor the cluster resource data acquisition component in each of the above-mentioned business clusters to obtain the cluster resource usage data collected by the above-mentioned cluster resource data acquisition component.

[0111] Optionally, in this embodiment of the application, the above-mentioned resource data acquisition component includes: a node resource data acquisition component and a cluster resource data acquisition component.

[0112] Therefore, by using the first monitoring component in each of the above-mentioned business clusters, it is possible to monitor the node resource data acquisition component to obtain node resource usage data, and also to monitor the cluster resource data acquisition component to obtain cluster resource usage data.

[0113] In another example, such as Figure 5 As shown, the above visualization component is a resource overview dashboard, and the above method also includes:

[0114] S301, pre-configure the variable information of the above resource overview dashboard, including: data source, business cluster variables, and private partition variables.

[0115] S302, In the above resource overview dashboard, create multiple display panels for the above private partition, and configure corresponding query statements for each of the above display panels.

[0116] In this embodiment, a monitoring platform can be built by deploying multiple business clusters across a Kubernetes container platform, i.e., multiple business clusters are equipped with one management cluster. Each business cluster deploys a first monitoring component, a node resource data collection component, and a cluster resource data collection component; the management cluster deploys a second monitoring component and a visualization component, and the pre-configured collection objects include: business cluster name and collection frequency.

[0117] Optionally, if the aforementioned visualization component is a resource overview dashboard, then this embodiment of the application can further pre-configure variable information for the resource overview dashboard, such as data source, business cluster variables, private partition variables, etc. Subsequently, in the aforementioned resource overview dashboard, multiple display panels are created for the aforementioned private partitions, and corresponding query statements are configured for each of the aforementioned display panels.

[0118] Optionally, the above display panel includes at least: a first panel for displaying node statistics, a second panel for displaying a resource usage overview of the private partition, and a third panel for displaying a node resource usage overview of the private partition.

[0119] In one example, the variable information of the resource overview dashboard that is pre-configured includes:

[0120] Configure the data sources that users can select in the resource overview dashboard mentioned above;

[0121] Configure the business cluster variable in the resource overview dashboard above so that users can select one or more business clusters to view;

[0122] Configure a private partition variable in the resource overview dashboard above so that users can select one or more private partitions to view.

[0123] In another example, the above method also includes:

[0124] S401, in response to the private partition selected by the user in the first panel, obtain the query statement corresponding to the first panel;

[0125] S402, based on the query statement corresponding to the first panel above, calculate the number of nodes allocated by different business clusters in the private partition above.

[0126] In this embodiment, a first panel displaying node statistics under a private partition is pre-created, and corresponding query statements are configured. For example, the first panel allows users to select a data source and enter a verification query statement in the indicator list, allowing users to select a specific private partition. For example, adding a new query statement and entering a verification query statement in the indicator list calculates the number of nodes allocated to different business clusters in the private partition.

[0127] In this embodiment, visualization information can also be configured, and variable names can be modified to Chinese names for easier viewing by users. By providing a visualization panel display scheme, users can select one or more business clusters and one or more private partitions to intuitively view the number of nodes allocated to the private partitions by each business cluster.

[0128] In another example, the above method also includes:

[0129] S601, in response to the private partition selected by the user in the second panel, obtain the query statement corresponding to the second panel.

[0130] S602, based on the query statement corresponding to the second panel above, calculate the resource usage overview information corresponding to different business clusters in the private partition above.

[0131] Optionally, the above resource usage overview information includes: total CPU computing resources used, total memory computing resources used, number of allocated CPU computing resources, number of allocated memory computing resources, CPU computing resource allocation rate, and memory computing resource allocation rate.

[0132] In this embodiment, a second panel pre-created with overview information of private partition resource usage is configured with corresponding query statements. For example, the second panel allows users to select a data source and enter review query statements in the indicator list, enabling users to select specific private partitions.

[0133] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the total CPU computing resources of different clusters in the private partition.

[0134] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the total amount of memory computing resources of different clusters in the private partition.

[0135] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the number of allocated CPU computing resources in different clusters in the private partition.

[0136] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the amount of allocated memory computing resources in different clusters in the private partition.

[0137] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the CPU computing resource allocation rate of different clusters in the private partition.

[0138] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the memory computing resource allocation rate of different clusters in the private partition.

[0139] In this embodiment of the application, a visualization panel can also be configured. Users can select one or more business clusters and one or more private partitions to intuitively view the resource usage status of each business cluster allocated to the private partition, and view the detailed allocation of computing resources such as CPU and memory in the private partition, so as to ensure sufficient resources.

[0140] In another example, the above method also includes:

[0141] S701, in response to the private partition selected by the user in the third panel, obtain the query statement corresponding to the third panel.

[0142] S702, based on the query statement corresponding to the second panel above, calculate the overview information of node resource usage allocated to the private partition for each of the above business clusters.

[0143] Optionally, the above node resource usage overview information includes: the total CPU computing resources used by the node, the total memory computing resources used by the node, the number of allocated CPU computing resources of the node, the number of allocated memory computing resources of the node, the actual utilization rate of the CPU computing resources of the node, and the actual utilization rate of the memory computing resources of the node.

[0144] In this embodiment, a third panel pre-created with overview information on node resource usage under a private partition is configured with corresponding query statements. For example, the third panel allows users to select a data source, and the second panel allows users to enter verification query statements in the indicator list, enabling users to select specific private partitions.

[0145] For example, a new query statement can be added. Enter the review query statement in the indicator list to query the specific node information allocated to the private partition for each business cluster.

[0146] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the total CPU computing resources of nodes in different clusters in the private partition.

[0147] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the total memory computing resources of nodes in different clusters in the private partition.

[0148] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the number of allocated CPU computing resources for nodes in different clusters in the private partition.

[0149] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the amount of allocated memory computing resources of nodes in different clusters in the private partition.

[0150] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the actual CPU computing resource utilization rate of nodes in different clusters in the private partition.

[0151] For example, add a new query statement, enter the review query statement in the indicator list, and calculate the actual utilization rate of memory computing resources of nodes in different clusters in the private partition.

[0152] In this embodiment of the application, a visualization panel can also be configured, which allows users to select one or more business clusters and one or more private partitions to intuitively view the resource usage status of each node allocated to the private partition by each business cluster.

[0153] Through this solution, for example, platform administrators and resource pool users of the container platform can intuitively view the resource usage and node status of each partition resource pool. They can quickly view abnormal node information and resource usage information of private partitions, which facilitates platform administrators to quickly replenish and adjust the resource usage of each system based on the current resource usage status, reduce the resource maintenance pressure on operation and maintenance personnel, ensure the continuous operation of business, and guarantee the security and reliability of services.

[0154] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0155] According to one or more embodiments of this application, a resource monitoring device for a container platform is provided, wherein multiple service clusters and a management and control cluster are deployed in the container platform. Figure 6 A structural block diagram of a resource monitoring device for a container platform provided in this application embodiment is shown below. Figure 6 As shown, the above-mentioned device includes:

[0156] The monitoring module 601 is used to monitor the resource data acquisition component in each of the above-mentioned business clusters using the first monitoring component in each of the above-mentioned business clusters, so as to obtain the resource usage data of the above-mentioned business clusters collected by the resource data acquisition component, wherein the resource usage data includes: node resource usage data and cluster resource usage data.

[0157] The determination module 602 is used to use the second monitoring component in the above-mentioned control cluster to determine the resource usage information of each of the above-mentioned business clusters and the resource usage information of each node allocated to the private partition of each of the above-mentioned business clusters, based on the node resource usage data and the cluster resource usage data uploaded by the first monitoring component. The second monitoring component is communicatively connected to the first monitoring component in each of the above-mentioned business clusters.

[0158] The display module 603 is used to display the resource usage information of each of the above-mentioned business clusters, as well as the resource usage information of each node of each of the above-mentioned business clusters allocated to the private partition, using the visualization display component in the above-mentioned management cluster.

[0159] According to one or more embodiments of this application, the monitoring module described above includes:

[0160] The first monitoring unit is configured to use the first monitoring component in each of the aforementioned service clusters to monitor the node resource data acquisition component in each of the aforementioned service clusters, so as to obtain the node resource usage data collected by the node resource data acquisition component, and

[0161] The second monitoring unit is used to monitor the cluster resource data acquisition component in each of the aforementioned business clusters using the first monitoring component in each of the aforementioned business clusters, so as to obtain the cluster resource usage data collected by the aforementioned cluster resource data acquisition component.

[0162] Furthermore, the aforementioned visualization component is a resource overview dashboard, and the aforementioned device also includes:

[0163] The configuration module is used to pre-configure the variable information of the above resource overview dashboard, including: data source, business cluster variables, and private partition variables.

[0164] A creation module is used to create multiple display panels for the private partition in the resource overview dashboard, and to configure corresponding query statements for each display panel. The display panels include at least: a first panel for displaying node statistics, a second panel for displaying resource usage overview information of the private partition, and a third panel for displaying node resource usage overview information of the private partition.

[0165] Furthermore, the above configuration module includes:

[0166] The first configuration unit is used to configure the data source for user selection in the aforementioned resource overview dashboard;

[0167] The second configuration unit is used to configure business cluster variables in the above resource overview dashboard, so that users can select one or more business clusters to view.

[0168] The third configuration unit is used to configure private partition variables in the aforementioned resource overview dashboard, allowing users to select one or more private partitions to view.

[0169] Furthermore, the aforementioned device also includes:

[0170] The first acquisition module is used to acquire the query statement corresponding to the first panel in response to the private partition selected by the user in the first panel.

[0171] The first calculation module is used to calculate the number of nodes allocated by different business clusters in the private partition based on the query statement corresponding to the first panel.

[0172] Furthermore, the aforementioned device also includes:

[0173] The second acquisition module is used to acquire the query statement corresponding to the second panel in response to the private partition selected by the user in the second panel.

[0174] The second calculation module is used to calculate the resource usage overview information corresponding to different business clusters in the private partition based on the query statement corresponding to the second panel. The resource usage overview information includes: total CPU computing resources used, total memory computing resources used, number of allocated CPU computing resources, number of allocated memory computing resources, CPU computing resource allocation rate, and memory computing resource allocation rate.

[0175] Furthermore, the aforementioned device also includes:

[0176] The third acquisition module is used to retrieve the query statement corresponding to the third panel in response to the private partition selected by the user in the third panel.

[0177] The third calculation module is used to calculate the node resource usage overview information allocated to the private partition for each of the above-mentioned business clusters based on the query statement corresponding to the second panel. The node resource usage overview information includes: the total CPU computing resource usage of the node, the total memory computing resource usage of the node, the number of allocated CPU computing resources of the node, the number of allocated memory computing resources of the node, the actual utilization rate of the CPU computing resources of the node, and the actual utilization rate of the memory computing resources of the node.

[0178] In an exemplary embodiment, this application also provides an electronic device, including: a processor, and a memory connected to the processor;

[0179] The aforementioned memory stores instructions executed by the computer;

[0180] The processor executes computer execution instructions stored in the memory to implement any of the methods described above.

[0181] In an exemplary embodiment, this application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods described above.

[0182] In an exemplary embodiment, this application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the methods described above.

[0183] To implement the above embodiments, this application also provides an electronic device. (See reference...) Figure 7 The diagram illustrates a structural schematic of an electronic device 700 suitable for implementing embodiments of this application. The electronic device 700 can be a terminal device or a server. The terminal device can include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, personal digital assistants (PDAs), portable Android devices (PADs), portable media players (PMPs), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 7 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0184] like Figure 7As shown, the electronic device 700 may include a processing unit (e.g., a central processing unit, a graphics processor, etc.) 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage device 708 into a random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the electronic device 700. The processing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0185] Typically, the following devices can be connected to I / O interface 705: input devices 706 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 707 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 708 including, for example, magnetic tapes, hard disks, etc.; and communication devices 709. Communication device 709 allows electronic device 700 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 An electronic device 700 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0186] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 709, or installed from storage device 708, or installed from ROM 702. When the computer program is executed by processing device 701, it performs the functions defined in the methods of embodiments of this application.

[0187] It should be noted that the computer-readable medium described above in this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0188] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0189] The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods shown in the above embodiments.

[0190] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0191] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0192] The units described in the embodiments of this application can be implemented in software or in hardware. The name of a unit does not necessarily limit the unit itself; for example, the first acquisition unit can also be described as "a unit that acquires at least two Internet Protocol addresses".

[0193] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0194] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

Claims

1. A resource monitoring method for a container platform, characterized in that, The container platform deploys multiple service clusters and one management cluster, and the method includes: The first monitoring component in each of the service clusters is used to monitor the resource data acquisition component in each of the service clusters to obtain the resource usage data of the service clusters collected by the resource data acquisition component. The resource usage data includes node resource usage data and cluster resource usage data. The second monitoring component in the control cluster is used to determine the resource usage information of each business cluster and the resource usage information of each node allocated to the private partition in each business cluster, based on the node resource usage data and the cluster resource usage data uploaded by the first monitoring component. The second monitoring component is communicatively connected to the first monitoring component in each business cluster. The private partition is a set of node resources divided in multiple business clusters by means of tags and taints. The visualization component in the management cluster is used to display the resource usage information of each business cluster, as well as the resource usage information of each node allocated to the private partition by each business cluster.

2. The method according to claim 1, characterized in that, The step of using a first monitoring component in each of the service clusters to monitor the resource data acquisition components in each of the service clusters includes: The first monitoring component in each of the service clusters is used to monitor the node resource data acquisition component in each service cluster, so as to obtain the node resource usage data collected by the node resource data acquisition component, and The first monitoring component in each of the service clusters is used to monitor the cluster resource data acquisition component in each of the service clusters to obtain the cluster resource usage data collected by the cluster resource data acquisition component.

3. The method according to claim 1, characterized in that, The visualization component is a resource overview dashboard, and the method further includes: The variable information of the resource overview dashboard is pre-configured, wherein the variable information includes: data source, business cluster variable, and private partition variable; In the resource overview dashboard, multiple display panels are created for the private partition, and a corresponding query statement is configured for each display panel. The display panels include at least: a first panel for displaying node statistics, a second panel for displaying resource usage overview information of the private partition, and a third panel for displaying node resource usage overview information of the private partition.

4. The method according to claim 3, characterized in that, The pre-configured variable information for the resource overview dashboard includes: Configure data sources for user selection in the resource overview dashboard; Configure service cluster variables in the resource overview dashboard so that users can select one or more service clusters to view; Configure private partition variables in the resource overview dashboard so that users can select one or more private partitions to view.

5. The method according to claim 4, characterized in that, The method further includes: In response to the private partition selected by the user in the first panel, obtain the query statement corresponding to the first panel; Based on the query statement corresponding to the first panel, calculate the number of nodes allocated by different business clusters in the private partition.

6. The method according to claim 4, characterized in that, The method further includes: In response to the private partition selected by the user in the second panel, obtain the query statement corresponding to the second panel; Based on the query statement corresponding to the second panel, calculate the resource usage overview information corresponding to different business clusters in the private partition. The resource usage overview information includes: total CPU computing resource usage, total memory computing resource usage, number of allocated CPU computing resources, number of allocated memory computing resources, CPU computing resource allocation rate, and memory computing resource allocation rate.

7. The method according to any one of claims 4 to 6, characterized in that, The method further includes: In response to the user selecting a private partition in the third panel, obtain the query statement corresponding to the third panel; Based on the query statement corresponding to the second panel, calculate the node resource usage overview information allocated to the private partition for each of the business clusters. The node resource usage overview information includes: the total CPU computing resource usage of the node, the total memory computing resource usage of the node, the number of allocated CPU computing resources of the node, the number of allocated memory computing resources of the node, the actual utilization rate of the CPU computing resources of the node, and the actual utilization rate of the memory computing resources of the node.

8. A container platform, characterized in that, The container platform includes: Multiple service clusters are provided, each of which is equipped with a first monitoring component and a resource data acquisition component. The first monitoring component in each service cluster is used to monitor the resource data acquisition component to obtain the resource usage data of the service cluster collected by the resource data acquisition component. The resource usage data includes node resource usage data and cluster resource usage data. A management cluster is communicatively connected to each of the aforementioned business clusters. The management cluster includes a second monitoring component and a visualization component. The second monitoring component determines the resource usage information of each business cluster and the resource usage information of each node allocated to a private partition based on the node resource usage data and cluster resource usage data uploaded by the first monitoring component. The visualization component displays the resource usage information of each business cluster and the resource usage information of each node allocated to a private partition. The private partition is a set of node resources divided among multiple business clusters using tags and taints.

9. A resource monitoring device for a container platform, characterized in that, The container platform deploys multiple service clusters and one management cluster. The device includes: The monitoring module is used to monitor the resource data acquisition component in each of the business clusters using the first monitoring component in each business cluster, so as to obtain the resource usage data of the business clusters collected by the resource data acquisition component, wherein the resource usage data includes: node resource usage data and cluster resource usage data; The determination module is used to determine the resource usage information of each business cluster and the resource usage information of each node allocated to a private partition in each business cluster, based on the node resource usage data and the cluster resource usage data uploaded by the first monitoring component, using the second monitoring component in the management cluster. The second monitoring component is communicatively connected to the first monitoring component in each business cluster. The private partition is a set of node resources divided among multiple business clusters using tags and taints. The display module is used to display the resource usage information of each of the business clusters and the resource usage information of each node allocated to the private partition by each of the business clusters using the visualization display components in the management cluster.

10. An electronic device, characterized in that, include: A processor, and a memory connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 7.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 7.

12. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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