Method, device and computer storage medium for cloud resource deployment

Abstract

The application discloses a cloud resource deployment method, device, equipment and computer storage medium, relates to the technical field of cloud computing, and comprises the following steps: acquiring a cluster configuration file, a cluster parameter template and an application configuration file; creating a cloud resource generation instance according to the cluster configuration file and the cluster parameter template, and creating a cluster through the cloud resource generation instance; establishing a mapping relationship between the cloud resource generation instance and the cluster; determining the cloud resource generation instance of the cluster corresponding to the application configuration file according to the mapping relationship; and deploying the cloud resource of an application in the cluster through the cloud resource generation instance according to the application configuration file. According to the application, the cloud resource is automatically configured through the creation of the cloud resource generation instance, automatic application deployment and operation and maintenance management can be realized, and the efficiency of cloud resource deployment is improved.

Description

Technical Field

[0001] This application belongs to the field of cloud computing technology, and in particular relates to a method, apparatus, device and computer storage medium for cloud resource deployment. Background Technology

[0002] Against the backdrop of rapid development in cloud computing technology, widespread migration of government and enterprise business applications to cloud platforms, and increasingly fierce competition in the cloud resource service market, customers are placing higher and higher demands on the quality of cloud resource services.

[0003] Existing methods rely on developers' experience in assessing and configuring cloud resources when deploying applications. This requires developers to evaluate and configure the necessary cloud resources based on their personal experience and understanding of the business. At the same time, the initial operation and maintenance work during the cloud resource deployment process is cumbersome, involving multiple aspects such as environment configuration, security settings, and performance tuning. This requires developers to invest a lot of time and energy, resulting in low efficiency in application cloud resource deployment. Summary of the Invention

[0004] This application provides a method, apparatus, device, and computer storage medium for cloud resource deployment to address the problem of low efficiency in cloud resource deployment using existing methods.

[0005] In a first aspect, embodiments of this application provide a method for deploying cloud resources, the method comprising:

[0006] Obtain the cluster configuration file, cluster parameter template, and application configuration file;

[0007] Create cloud resource generation instances based on cluster configuration files and cluster parameter templates, and create clusters using cloud resource generation instances;

[0008] Establish a mapping relationship between cloud resource generation instances and clusters;

[0009] The cloud resource instance corresponding to the cluster is generated based on the mapping relationship;

[0010] Cloud resources are used to generate instances of the application in the cluster based on the application configuration file.

[0011] Secondly, embodiments of this application provide an apparatus for deploying cloud resources, the apparatus comprising:

[0012] The acquisition module is used to acquire cluster configuration files, cluster parameter templates, and application configuration files.

[0013] The creation module is used to create cloud resource generation instances based on cluster configuration files and cluster parameter templates, and to create clusters using cloud resource generation instances.

[0014] Establish a module to create a mapping relationship between cloud resource generation instances and clusters;

[0015] The determination module is used to determine the cloud resource generation instance of the cluster corresponding to the application configuration file based on the mapping relationship;

[0016] The deployment module is used to generate cloud resources for the application in the cluster based on the application configuration file and cloud resources.

[0017] Thirdly, embodiments of this application provide a terminal device, the device including: a processor and a memory storing computer program instructions; the processor executes the computer program instructions to implement the cloud resource deployment method as described in the first aspect.

[0018] Fourthly, embodiments of this application provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the cloud resource deployment method as described in the first aspect.

[0019] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, cause the electronic device to perform a cloud resource deployment method as described in the first aspect.

[0020] This application provides a method, apparatus, device, and computer storage medium for cloud resource deployment. The method first obtains a cluster configuration file, a cluster parameter template, and an application configuration file; this accurately understands the configuration requirements of the cluster and applications, ensuring that subsequently created cloud resources and deployed applications meet the expected configuration requirements. Cloud resource generation instances are created based on the cluster configuration file and cluster parameter template, and clusters are created using these cloud resource generation instances; these instances automate the creation of cloud resource generation instances and clusters, improving the efficiency of deploying the entire cluster system. A mapping relationship is established between cloud resource generation instances and clusters; this mapping relationship allows for monitoring and control of the cluster using cloud resource generation instances, improving overall manageability and maintainability. The cloud resource generation instance corresponding to the application configuration file is determined based on the mapping relationship, ensuring that the application is deployed to the correct cluster. Cloud resources for the application are deployed in the cluster using cloud resource generation instances based on the application configuration file; this automated deployment and configuration of applications is achieved through the application configuration file and cloud resource generation instances. This application, by automatically configuring cloud resources through the creation of cloud resource generation instances, enables automated application deployment and operation and maintenance management, improving the efficiency of cloud resource deployment. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the structure of the cloud resource deployment system provided in the embodiments of this application;

[0023] Figure 2 This is a flowchart illustrating the cloud resource deployment method provided in an embodiment of this application;

[0024] Figure 3 This is a schematic diagram of the structure of the container resource specification range provided in the embodiments of this application;

[0025] Figure 4 This is a structural schematic diagram of the container replica specification range provided in the embodiments of this application;

[0026] Figure 5 This is a flowchart illustrating the cloud resource adjustment method provided in an embodiment of this application;

[0027] Figure 6 This is a flowchart illustrating the container resource adjustment method provided in an embodiment of this application;

[0028] Figure 7 This is a flowchart illustrating the node resource adjustment method provided in an embodiment of this application;

[0029] Figure 8 This is a schematic diagram of the node partition structure provided in the embodiments of this application;

[0030] Figure 9 This is a schematic diagram of the structure of the cloud resource deployment apparatus provided in the embodiments of this application;

[0031] Figure 10 This is a schematic diagram of the structure of the terminal device provided in the embodiments of this application. Detailed Implementation

[0032] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0033] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0034] Current technologies for deploying cloud resources for applications primarily rely on developers' experience-based assessments and settings. This approach has several drawbacks, severely impacting the efficiency and quality of application cloud resource deployment. First, relying on developers' experience-based assessments and settings lacks objectivity and accuracy. Each developer's understanding of the business and personal experience differ, leading to subjectivity in their assessment and configuration of cloud resources. Therefore, different developers may configure drastically different cloud resource solutions for the same application, and these solutions may not all be optimal. This subjectivity and variability not only increase the uncertainty of cloud resource deployment but may also lead to resource waste or inadequacy. Second, the initialization and maintenance work during cloud resource deployment is tedious and complex. Environment configuration, security settings, performance tuning, and many other aspects require developers to invest significant time and effort. This work demands not only extensive technical knowledge and practical experience but also a high degree of patience and meticulousness. However, in practice, developers often struggle to meet all these requirements simultaneously, resulting in frequent oversights and errors in initialization and maintenance. These problems not only affect the progress and quality of cloud resource deployment but may also pose hidden dangers for subsequent application operation and maintenance.

[0035] Furthermore, current technologies lack automated methods for cloud resource deployment and operation management. Developers need to manually perform multiple tasks such as resource assessment, configuration, deployment, and operation, which is not only inefficient but also prone to errors. With the continuous development of cloud computing technology and the expanding scale of its applications, manual deployment and operation methods can no longer meet the demands for speed, accuracy, and reliability. In summary, existing methods for cloud resource deployment are inefficient.

[0036] To address the problems of existing technologies, this application provides a method, apparatus, device, and computer storage medium for cloud resource deployment. The method first obtains a cluster configuration file, a cluster parameter template, and an application configuration file; this accurately understands the configuration requirements of the cluster and applications, ensuring that subsequently created cloud resources and deployed applications meet the expected configuration requirements. Cloud resource generation instances are created based on the cluster configuration file and cluster parameter template, and clusters are created using these cloud resource generation instances; these instances automate the creation of cloud resource generation instances and clusters, improving the efficiency of deploying the entire cluster system. A mapping relationship is established between cloud resource generation instances and clusters; this mapping relationship allows for monitoring and control of the cluster using cloud resource generation instances, improving overall manageability and maintainability. The cloud resource generation instance corresponding to the application configuration file is determined based on the mapping relationship, ensuring that the application is deployed to the correct cluster. Cloud resources for the application are deployed in the cluster using cloud resource generation instances based on the application configuration file; this automated deployment and configuration of applications is achieved through the application configuration file and cloud resource generation instances. This application, by automatically configuring cloud resources through the creation of cloud resource generation instances, enables automated application deployment and operation and maintenance management, improving the efficiency of cloud resource deployment.

[0037] The cloud resource deployment system provided in the embodiments of this application will be introduced first below.

[0038] Figure 1 A schematic diagram of the structure of a cloud resource deployment system 100 provided in one embodiment of this application is shown. Figure 1 As shown, the system may include a configuration module 110, an operation and maintenance module 120, and a cloud environment module 130. The configuration module 110 is used for the initial configuration and parameter settings of the system. It may contain an interface or application programming interface (API) for defining configuration information such as cluster size, resource type, and resource specification range. Users or administrators can customize the behavior of the cloud resource deployment system through the configuration module to meet specific business needs. The operation and maintenance module 120 is the core part of the cloud resource deployment system, responsible for the operation and maintenance management and automated operation of cloud resources. The cloud environment module 130 is the underlying cloud environment on which the cloud resource deployment system depends, including cluster nodes and the control plane.

[0039] The operations and maintenance module 120 may include an application orchestration engine 121, an elastic cluster cloud resource operations and maintenance component 122, an elastic cluster cloud resource operations and maintenance instance 123, and a cloud infrastructure management engine 124. The application orchestration engine 121 is responsible for the lifecycle management of applications, including deployment, upgrades, and rollbacks. It can automatically complete application deployment and configuration based on user-defined application templates or configuration files. The elastic cluster cloud resource operations and maintenance component 122 is responsible for managing and maintaining the cloud resources of elastic clusters (such as Kubernetes clusters). The elastic cluster cloud resource operations and maintenance instance 123 is a concrete instance of the elastic cluster cloud resource operations and maintenance component; it performs the actual operations and maintenance, and each instance may be responsible for the operations and maintenance tasks of one or more clusters. The cloud infrastructure management engine 124 is responsible for the management and configuration of cloud infrastructure, and may include operations such as creating, deleting, and modifying cloud infrastructure resources.

[0040] The cloud environment module 130 may include cluster nodes 131 and a control plane 132 deployed on the cluster nodes. The control plane 132 may include an application orchestration engine 133, a container orchestration engine 134, a cloud infrastructure resource management engine 135, a perception control component 136, and an elastic application cloud resource operation and maintenance controller 137. The cluster nodes 131 are physical or virtual nodes managed by the cloud resource deployment system, and each node may run containers, Pods, or other workloads. The control plane 132 is responsible for managing and coordinating resources and workloads within the cluster. The application orchestration engine 133 performs application deployment and orchestration within the cluster. The container orchestration engine 134 is responsible for container creation, scheduling, updating, and deletion. The cloud infrastructure resource management engine 135 allocates and manages cloud infrastructure resources within the cluster. The perception control component 136 monitors the cluster status and resource usage, and dynamically adjusts the resource specifications or replica count of containers based on resource usage. The elastic application cloud resource operation and maintenance controller 137 is used to manage and maintain elastic application cloud resources. It may include advanced features such as automatic scaling, fault recovery, and performance optimization to ensure the stability and availability of the application.

[0041] The method for deploying cloud resources provided in the embodiments of this application is described below with reference to the accompanying drawings.

[0042] Figure 2 A flowchart illustrating a method for deploying cloud resources according to an embodiment of this application is shown. Figure 2 As shown, the method may include the following steps: S201 to S205.

[0043] S201, retrieve cluster configuration file, cluster parameter template and application configuration file.

[0044] The cluster configuration file defines the cluster creation requirements and resource configuration; the cluster parameter template provides various parameter templates required during the cluster creation process for quick cluster configuration; the application configuration file specifies the cluster name to be deployed for the application, i.e., the name of the Elastic Cluster Cloud Resource Operation and Maintenance Component instance corresponding to the cluster, as well as the application's configuration requirements.

[0045] In some embodiments, the cluster configuration file may include cloud provider type, region, cloud provider account authentication information, instance name (equivalent to cluster name), initial cluster resource value, cluster resource limit value, resource isolation space ratio, tiered resource specification distribution group and other configuration parameters, and the component type is specified as the application configuration file of the Elastic Cloud Resource Cluster Operation and Maintenance Component.

[0046] In some embodiments, cluster configuration files, cluster parameter templates, and application configuration files are manually configured according to preset specifications; configuration files and templates can be used to flexibly adjust the configuration according to different application requirements and environmental conditions, thereby improving the adaptability of the system.

[0047] By obtaining cluster configuration files, cluster parameter templates, and application configuration files, the deployment process can be standardized, the configuration requirements of the cluster and applications can be accurately understood, and the cloud resources created and applications deployed subsequently can meet the expected configuration requirements.

[0048] S202 creates cloud resource generation instances based on cluster configuration files and cluster parameter templates, and then creates clusters using these cloud resource generation instances.

[0049] Among them, cloud resource generation instances are instances created in the cloud environment based on cluster configuration files and cluster parameter templates, and are used to generate and manage clusters.

[0050] In some embodiments, cloud resource generation instances are generated using cluster configuration files and cluster parameter templates, and are created through a preset program. The preset program can be a built-in program preset in the application orchestration engine.

[0051] In some embodiments, creating a cloud resource generation instance based on a cluster configuration file and a cluster parameter template, and then creating a cluster using the cloud resource generation instance, may include:

[0052] Instances are generated using cloud resources to create cluster nodes and the corresponding control plane based on cluster configuration files;

[0053] The instance is generated using cloud resources to initialize cluster nodes and the corresponding control plane of the cluster based on the cluster parameter template.

[0054] Among them, the cloud resource generation instance controls the cloud resource facility management engine to complete the creation and initialization of cluster nodes and the corresponding control plane in the cloud environment through the built-in cloud resource cluster initialization creation program.

[0055] By creating cloud resource generator instances and then creating clusters from these instances, cluster creation is automated, improving deployment efficiency.

[0056] S203, establish the mapping relationship between cloud resource generation instances and clusters.

[0057] Among them, the cloud resource generation instance and the cluster it creates have a one-to-one companion relationship. Through the operation and maintenance of the cloud resource generation instance, the basic information mapping and lifecycle management of the created cluster can be realized.

[0058] By establishing a mapping relationship between cloud resource generation instances and clusters, the management of clusters can be achieved through cloud resource generation instances, making cluster management and control simpler and more intuitive.

[0059] S204, determine the cloud resource generation instance of the cluster corresponding to the application configuration file based on the mapping relationship.

[0060] In some embodiments, the application configuration file includes application settings specifying the name of the cluster to be deployed, and obtains the cloud resource generation instance corresponding to the cluster name through a mapping relationship, so as to use the cloud resource generation instance to deploy the corresponding cluster according to the application configuration file.

[0061] The mapping relationship can accurately determine the cloud resource generation instance of the cluster corresponding to the configuration file, ensuring that the application is deployed to the correct cluster, improving the accuracy of application deployment, and reducing deployment failures or performance issues caused by incorrect resource allocation.

[0062] S205, based on the application configuration file, generates instances of cloud resources to deploy the application in the cluster.

[0063] In some embodiments, the application configuration file also includes initial configuration parameters for application resources. After obtaining the cluster name to which the application is to be deployed, an instance is generated based on the cloud resources corresponding to the cluster name, and the cloud resources of the cluster are configured using the basic configuration information of the cluster.

[0064] Configuring cloud resources for an application using application configuration files based on cloud resource generation instances ensures that the application obtains the specific resources and configurations required to meet its operational needs. This achieves automated deployment of cloud resource configuration, simplifies the complexity of application deployment, and improves application deployment efficiency.

[0065] First, obtain the cluster configuration file, cluster parameter template, and application configuration file. This allows for an accurate understanding of the cluster and application configuration requirements, ensuring that subsequently created cloud resources and deployed applications meet the expected configuration requirements. Create cloud resource generation instances based on the cluster configuration file and cluster parameter template, and then create clusters using these cloud resource generation instances. Instance creation of cloud resource generation instances and clusters can be automated, improving the efficiency of deploying the entire cluster system. Establish a mapping relationship between cloud resource generation instances and clusters. This mapping relationship allows for monitoring and control of the cluster using cloud resource generation instances, improving overall manageability and maintainability. Determine the cloud resource generation instance for the cluster corresponding to the application configuration file based on the mapping relationship, ensuring that the application is deployed to the correct cluster. Deploy the application's cloud resources in the cluster using cloud resource generation instances based on the application configuration file. Deploying application cloud resources in the cluster using application configuration files and cloud resource generation instances enables automated application deployment and configuration. Automated configuration of cloud resources through the creation of cloud resource generation instances enables automated application deployment and operation and maintenance management, improving the efficiency of cloud resource deployment.

[0066] In some embodiments, cloud resources include container resources and node resources. Cloud resources used to generate instances of applications for deployment in the cluster based on application configuration files may include:

[0067] Based on the preset cloud resource requirements in the application configuration file, the cloud resource generation instance deploys container resources and the target number of node resources corresponding to the application in the cluster. The target resource specification range is the minimum resource specification range that enables the application to run.

[0068] Among them, the preset cloud resource requirements are the initial configuration parameters of application resources, which describe in detail the minimum resources required for the application to run. That is, the minimum resource configuration required for the application to start and run normally, which may include the specifications of container resources such as central processing unit (CPU), memory, storage, and network, as well as the number of node resources. The target resource specification range is the resource specification range for the application's application container to run.

[0069] By matching the minimum application requirements, the system ensures that the application receives sufficient resources to meet performance requirements, while avoiding the waste of cloud resources and improving resource utilization.

[0070] In some embodiments, the resource specification range can be input via a cluster parameter template during cluster initialization. The resource specification ranges are distributed in a tiered manner; for each cluster resource isolation space, a corresponding resource specification range can be configured to control the automatic scaling of container resources. The resource specification range can include container resource specification ranges and container replica specification ranges, such as... Figure 3As shown, this represents the container resource specification range, with the vertical axis representing the container resource specification and the horizontal axis representing the number of application containers of that specification. For example... Figure 4 As shown, the container replica size range is represented by the vertical axis, which represents the size of the container replica, and the horizontal axis represents the number of applications.

[0071] In some embodiments, deploying container resources within the target resource specification range corresponding to the application in the cluster may include:

[0072] When the application is deployed for the first time, the largest available resource specification range in the resource specification range is used as the target resource specification range of the container resource; the lower bound of the target resource specification range is used as the requested resource value of the container resource, and the upper bound of the target resource specification range is used as the limited resource value of the container resource.

[0073] If the application can start normally, it matches the next smaller resource specification range. If the match is successful, the next smaller resource specification range is updated to the target resource specification range. This continues until the application cannot start due to insufficient resources. The final target resource specification range is then used as the matching range for the application resources, which is the minimum resource specification range for the application to run. At the same time, the requested resource value and the limited resource value of the container resources are updated.

[0074] Matching starts from the maximum resource specification range, allowing you to select the minimum resource specification range that enables the application to run normally, thus ensuring stable application operation.

[0075] In some embodiments, deploying container resources within the target resource specification range corresponding to the application in the cluster may further include:

[0076] When the application is deployed for the first time, the smallest resource specification range in the resource specification range is used as the target resource specification range for the container resources.

[0077] If the application fails to start normally, update the next higher-order resource specification range to the target resource specification range until the application can start normally within the target resource specification range. The final target resource specification range is then used as the matching range for the application resources, which is the minimum resource specification range required for the application to run.

[0078] Matching from the minimum resource specification range allows for a gradual increase in the cloud resources used by the application, avoiding the waste of resources caused by allocating too many resources to the application at the beginning.

[0079] In some embodiments, such as Figure 5 As shown, after generating cloud resources for deploying the application in the cluster based on the application configuration file and using cloud resources, the method may further include: S501 to S504.

[0080] S501, Get the container resource usage of the application;

[0081] S502, Update the application target resource specification range and the container resources within the target resource specification range according to the container resource usage;

[0082] S503, when the container resources in the target resource specification range are updated, obtain the node resource usage of the node. The node resource usage is the total container resource usage of the node, including the containers.

[0083] S504, adjust node resources based on the difference between node resource usage and preset node resource usage.

[0084] By updating the application's target resource specification range and the corresponding container resources based on container resource usage, and adjusting node resources based on node resource usage, resources can be dynamically adjusted according to actual usage, allowing for resource expansion or contraction, achieving optimal resource allocation, and thus improving resource management efficiency.

[0085] In some embodiments, such as Figure 6 As shown, the container specification includes the container resource specification and the container replica specification. Updating the application target resource specification range and the container resources within the target resource specification range according to the container resource usage can include: S601 to S603.

[0086] S601, when the container resource usage exceeds the first container set threshold, obtain the container resource limit value of the application container and the first resource specification range and the second resource specification range corresponding to the container resource usage.

[0087] S602, determine the expansion direction coefficients of container resource specifications and container replica specifications according to the first resource specification range and the second resource specification range respectively, and obtain the first expansion direction coefficient and the second expansion direction coefficient.

[0088] S603, select the target container specification corresponding to the smaller expansion direction coefficient among the first expansion direction coefficient and the second expansion direction coefficient, update the target resource specification range corresponding to the target container specification to a higher-order resource specification range, and update the container resources corresponding to the target resource specification range.

[0089] Determining the expansion direction coefficient based on the first and second resource specification ranges allows for dynamic assessment of expansion needs and directions. Selecting the target container specification corresponding to the smaller expansion direction coefficient for expansion ensures that application requirements are met while minimizing resource waste.

[0090] In some embodiments, determining the expansion direction coefficients of container resource specifications and container replica specifications based on the first resource specification range and the second resource specification range respectively may include: the ratio of the difference in step levels between the specification range item where the resource limit value is located and the specification range item where the resource request value is located to the step density as the expansion direction coefficient.

[0091] In some embodiments, updating the application target resource specification range and the container resources within the target resource specification range based on container resource usage may include:

[0092] If the resource usage is lower than the threshold set by the second container, the target resource specification range is updated to the lower-level resource specification range, and the container resources corresponding to the target resource specification range are updated.

[0093] By updating the target resource specification range to a higher level, the resources allocated to the application can be reduced, making more efficient use of resources in the cluster and improving resource utilization.

[0094] In some embodiments, adjusting node resources based on the difference between node resource usage and a preset node resource amount may include:

[0095] If the difference between the node resource usage and the preset node resource amount exceeds the threshold set by the first node, a cloud resource generation instance is used to create node resources.

[0096] By increasing node resources to meet resource demands, performance degradation or service interruptions due to insufficient resources can be avoided; new nodes are only created when resource demands increase, avoiding excessive pre-allocation and waste of resources.

[0097] In some embodiments, such as Figure 7 As shown, adjusting node resources based on the difference between node resource usage and preset node resource usage can include steps S701 to S704.

[0098] S701, when the difference between the node resource usage and the preset node resource usage is lower than the threshold set by the second node, the nodes and the application containers corresponding to the nodes are sorted according to the node resource usage and the container resource usage, respectively, to obtain the container stability sequence and the node stability sequence.

[0099] S702, based on the node stability sequence, sets a threshold to divide the nodes into steady-state nodes and dynamic nodes;

[0100] S703, schedule the first target container of the steady-state node to the dynamic zone node, schedule the second target container of the dynamic zone node to the steady-state node, until the container stability ranking of the containers in the steady-state node is lower than that of the containers in the dynamic zone node. Here, the first target container is the container with the largest ranking in the container stability sequence, and the second target container is the container with the smallest ranking in the container stability sequence.

[0101] S704: When the container resources of a dynamic zone node exceed the node's preset threshold, create a target node, schedule the container to the target node, divide the target node into a steady-state zone node, and delete idle nodes.

[0102] By scheduling the first target container (with the highest resource usage) of the steady-state zone node to the dynamic zone node, and scheduling the second target container (with the lowest resource usage) of the dynamic zone node back to the steady-state zone node, containers with high resource usage are scheduled to nodes with relatively abundant resources, and containers with low resource usage are scheduled to nodes with high resource usage. This allows for dynamic adjustments based on actual resource usage and preset thresholds.

[0103] In some embodiments, sorting the application containers corresponding to nodes according to their resource usage to obtain a container stability sequence may include:

[0104] Based on the preset importance sequence of various resource types, such as sorting resources from high to low according to their occupancy rate in the total resource quantity of a node;

[0105] Calculate the standard deviation of resource usage for different resource types in all application containers over a specified time period; the smaller the standard deviation, the better the stability of resource usage in the container.

[0106] The container stability sequence is obtained by sorting containers from highest to lowest runtime, then by the order of importance of resource type, and finally by the standard deviation of resource usage data for each resource type from lowest to highest.

[0107] In some embodiments, sorting nodes according to their resource usage to obtain a node stability sequence may include:

[0108] The runtime of all containers on each node and the standard deviation of each resource type are summed over each dimension. The sum is the stability index value of that dimension for that node. The containers are then sorted according to the stability ranking rules to obtain the node stability sequence.

[0109] In some embodiments, when the total resources of containers running in the dynamic region exceed the standard node specification, a new standard-specification node is created and placed in the merge region. The running containers in the dynamic region are then scheduled to the merge node, and the merge node is placed in the steady-state region. When the total resources of the running containers in the dynamic region do not meet the merging conditions, the sum of the current container resource requests and the maximum resource limit is calculated. Nodes in the dynamic region whose resources fall between this sum are matched. If no match is found, a new node is created as the sole reserved node. Other idle nodes are deleted.

[0110] In some embodiments, nodes in the steady-state zone can be matched with the optimal specifications in the cloud provider's resource pool according to the actual resource usage and the nodes can be replaced. The new nodes are assigned to the optimal allocation zone, and after the replacement and migration are completed, the new nodes are assigned to the steady-state zone.

[0111] In one example, the dynamic region can have more than one node, and the remaining nodes are all assigned to the steady-state region, which can have zero nodes. The optimized region and the merged region are temporary; after resource scheduling is complete, they will be moved to the steady-state region. For example... Figure 8 As shown, the node partitions include a preferred partition, a stable partition, a merge partition, and a dynamic partition. Application containers 1, 2, 6, 3, 7, 9, and 4, 5, 8 are application containers within three nodes in the stable partition. Application container 12 is scheduled from a node in the stable partition to a node in the dynamic partition, and application container 10 is scheduled from a node in the dynamic partition to a node in the stable partition. Application containers 11 and 13 in the dynamic partition are scheduled to newly generated nodes in the merge partition, and their original nodes are deleted.

[0112] Figure 9 An apparatus 900 for cloud resource deployment according to an embodiment of this application is shown. The apparatus may include:

[0113] Module 901 is used to obtain cluster configuration files, cluster parameter templates, and application configuration files.

[0114] Module 902 is used to create cloud resource generation instances based on cluster configuration files and cluster parameter templates, and to create clusters using cloud resource generation instances.

[0115] Establish module 903 to create a mapping relationship between cloud resource generation instances and clusters;

[0116] Module 904 is used to determine the cloud resource generation instance of the cluster corresponding to the application configuration file based on the mapping relationship;

[0117] Deployment module 905 is used to generate cloud resources for applications in the cluster based on application configuration files and cloud resources to deploy the application instance.

[0118] In some embodiments, the cloud resource deployment apparatus 900 may further include:

[0119] Module 902 is also used to generate instances from cloud resources, creating cluster nodes and the corresponding control plane of the cluster based on the cluster configuration file.

[0120] The initialization module is used to generate instances from cloud resources and initialize cluster nodes and the corresponding control plane of the cluster based on cluster parameter templates.

[0121] In some embodiments, the deployment module 905 is further configured to deploy container resources and a target number of node resources corresponding to the application in the cluster by generating an instance of cloud resources according to the preset cloud resource requirements in the application configuration file, wherein the target resource specification range is the minimum resource specification range for the application to run.

[0122] In some embodiments, the cloud resource deployment apparatus 900 may further include:

[0123] The acquisition module 901 is also used to acquire the resource usage of the container running the application;

[0124] The update module is used to update the application's target resource specification range and the container resources within the target resource specification range based on container resource usage.

[0125] The acquisition module 901 is also used to acquire the node resource usage of a node when the container resources in the target resource specification range are updated. The node resource usage is the total container resource usage of the node, including the container.

[0126] The adjustment module is used to adjust node resources based on the difference between the node resource usage and the preset node resource amount.

[0127] In some embodiments, the acquisition module 901 is further configured to acquire, respectively, the container resource limit value of the application container and the first resource specification range and the second resource specification range corresponding to the container resource usage when the container resource usage exceeds the first container set threshold.

[0128] The determination module 904 is further configured to determine the expansion direction coefficients of the container resource specification and the container replica specification according to the first resource specification range and the second resource specification range, respectively, to obtain the first expansion direction coefficient and the second expansion direction coefficient.

[0129] The update module is also used to select the target container specification corresponding to the smaller expansion direction coefficient among the first expansion direction coefficient and the second expansion direction coefficient, update the target resource specification range corresponding to the target container specification to a higher-order resource specification range, and update the container resources corresponding to the target resource specification range.

[0130] In some embodiments, the updating module is further configured to update the target resource specification range to a lower-order resource specification range and update the container resources corresponding to the target resource specification range when the resource usage is lower than the second container set threshold.

[0131] In some embodiments, the creation module 902 is further configured to create node resources using cloud resource generation instances when the difference between the node resource usage and the preset node resource amount exceeds a threshold set by the first node.

[0132] In some embodiments, the cloud resource deployment apparatus 900 may further include:

[0133] The sorting module is used to sort the nodes and their corresponding application containers according to the node resource usage and container resource usage when the difference between the node resource usage and the preset node resource usage is lower than the threshold set by the second node, so as to obtain the container stability sequence and the node stability sequence.

[0134] The partitioning module is used to divide nodes into steady-state nodes and dynamic nodes based on a threshold set according to the node stability sequence.

[0135] The scheduling module is used to schedule the first target container in the steady-state zone node to the dynamic zone node, and the second target container in the dynamic zone node to the steady-state zone node, until the container stability ranking of the containers in the steady-state zone node is lower than that of the containers in the dynamic zone node. The first target container is the container with the highest ranking in the container stability sequence, and the second target container is the container with the lowest ranking in the container stability sequence.

[0136] The creation module 902 is also used to create a target node when the container resources of the container in the dynamic zone node are greater than the node's preset threshold, schedule the container to the target node, divide the target node into a steady-state zone node, and delete idle nodes.

[0137] Figure 9 The various modules in the device shown can achieve Figure 2 The various steps involved, and the corresponding technical effects achieved, will not be elaborated upon here for the sake of brevity.

[0138] Figure 10 A schematic diagram of the hardware structure of the terminal device provided in an embodiment of this application is shown.

[0139] The terminal device may include a processor 1001 and a memory 1002 storing computer program instructions.

[0140] Specifically, the processor 1001 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0141] Memory 1002 may include mass storage for data or instructions. For example, and not limitingly, memory 1002 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 1002 may include removable or non-removable (or fixed) media, or memory 1002 may be non-volatile solid-state memory. Memory 1002 may be internal or external to the integrated gateway disaster recovery device.

[0142] In one instance, memory 1002 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the cloud resource deployment method according to this disclosure.

[0143] The processor 1001 reads and executes computer program instructions stored in the memory 1002 to achieve... Figure 2 The cloud resource deployment method in the illustrated embodiment.

[0144] In one example, the terminal device may further include a communication interface 1003 and a bus 1004. For example, Figure 10 As shown, the processor 1001, memory 1002, and communication interface 1003 are connected through bus 1004 and complete communication with each other.

[0145] The communication interface 1003 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0146] Bus 1004 includes hardware, software, or both, that couples components of an end device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 1004 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0147] Furthermore, in conjunction with the cloud resource deployment methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the cloud resource deployment methods in the above embodiments.

[0148] This application also provides a computer program product, including a computer program, which, when executed, implements any of the cloud resource deployment methods described in the above embodiments.

[0149] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0150] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or text segments used to perform the required tasks. Programs or text segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Text segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0151] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0152] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0153] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method of cloud resource deployment, characterized by, include: Obtain the cluster configuration file, cluster parameter template, and application configuration file; A cloud resource generation instance is created based on the cluster configuration file and cluster parameter template, and a cluster is created using the cloud resource generation instance. Establish a mapping relationship between the cloud resource generation instance and the cluster; The cloud resource generation instance of the cluster corresponding to the application configuration file is determined based on the mapping relationship; The cloud resources are used to generate instances of the application in the cluster based on the application configuration file and the cloud resources.

2. The method of cloud resource deployment of claim 1, wherein, The step of creating a cloud resource generation instance based on the cluster configuration file and cluster parameter template, and creating a cluster using the cloud resource generation instance, includes: Instances are generated using cloud resources to create cluster nodes and the corresponding control plane based on cluster configuration files; The cloud resource generation instance initializes the cluster nodes and the corresponding control plane of the cluster based on the cluster parameter template.

3. The method of cloud resource deployment of claim 1, wherein, The cloud resources include container resources and node resources. The step of generating instances of the application and deploying them in the cluster using the cloud resources according to the application configuration file includes: Based on the preset cloud resource requirements in the application configuration file, the application's corresponding target resource specification range of container resources and target number of node resources are deployed in the cluster through cloud resource generation instances. The target resource specification range is the minimum resource specification range for the application to run.

4. The method of cloud resource deployment of claim 3, wherein, After generating an instance of the application using the cloud resources in the cluster according to the application configuration file, the method further includes: Get the container resource usage of the application; Update the application's target resource specification range and the container resources within the target resource specification range based on the container resource usage; When the container resources within the target resource specification range are updated, the node resource usage of the node is obtained, where the node resource usage is the total container resource usage of the node, including the containers. The node resources are adjusted based on the difference between the node resource usage and the preset node resource amount.

5. The method of cloud resource deployment of claim 4, wherein, The container resources include container resource specifications and container replica specifications. Updating the application's target resource specification range and the container resources within that range based on the container resource usage includes: When the container resource usage exceeds the first container set threshold, the container resource limit value of the application container and the first resource specification range and the second resource specification range corresponding to the container resource usage are obtained respectively. Based on the first resource specification range and the second resource specification range, the expansion direction coefficients of the container resource specification and the container replica specification are determined respectively, thus obtaining the first expansion direction coefficient and the second expansion direction coefficient. Select the target container specification corresponding to the smaller expansion direction coefficient between the first expansion direction coefficient and the second expansion direction coefficient, update the target resource specification range corresponding to the target container specification to a higher-order resource specification range, and update the container resources corresponding to the target resource specification range.

6. The method of cloud resource deployment of claim 4, wherein, The step of updating the application's target resource specification range and the container resources within the target resource specification range based on the container resource usage includes: If the resource usage is lower than the second container's set threshold, the target resource specification range is updated to a lower-order resource specification range, and the container resources corresponding to the target resource specification range are updated.

7. The method of cloud resource deployment of claim 4, wherein, The step of adjusting node resources based on the difference between the node resource usage and the preset node resource amount includes: If the difference between the node resource usage and the preset node resource amount exceeds the threshold set by the first node, a cloud resource generation instance is used to create node resources.

8. The method of cloud resource deployment of claim 4, wherein, The step of adjusting node resources based on the difference between the node resource usage and the preset node resource amount includes: When the difference between the node resource usage and the preset node resource usage is lower than the second node set threshold, the nodes and the application containers corresponding to the nodes are sorted according to the node resource usage and the container resource usage, respectively, to obtain the container stability sequence and the node stability sequence. Based on a threshold set according to the node stability sequence, nodes are divided into steady-state nodes and dynamic nodes. The first target container in the steady-state node is scheduled to the dynamic zone node, and the second target container in the dynamic zone node is scheduled to the steady-state node, until the container stability ranking of the containers in the steady-state node is lower than that of the containers in the dynamic zone node. Here, the first target container is the container with the highest ranking in the container stability sequence, and the second target container is the container with the lowest ranking in the container stability sequence. When the container resources of a dynamic zone node exceed the node's preset threshold, a target node is created, the container is scheduled to the target node, the target node is divided into a steady-state zone node, and idle nodes are deleted.

9. An apparatus for cloud resource deployment, the apparatus comprising: include: The acquisition module is used to acquire cluster configuration files, cluster parameter templates, and application configuration files. A creation module is used to create cloud resource generation instances based on the cluster configuration file and cluster parameter template, and to create clusters through the cloud resource generation instances. A module is established to create a mapping relationship between the cloud resource generation instance and the cluster; The determination module is used to determine the cloud resource generation instance of the cluster corresponding to the application configuration file based on the mapping relationship; The deployment module is used to generate instances of the application in the cluster and deploy the application's cloud resources in the cluster based on the application configuration file and the cloud resources.

10. A terminal device, comprising: The device includes: a processor and a memory storing computer program instructions; the processor executes the computer program instructions to implement the cloud resource deployment method as described in any one of claims 1-8.

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