Container-based cloud native capacity management method, system, electronic device and storage medium

Abstract

The present application provides a container-based cloud native capacity management method, system, electronic device and storage medium. When an application feasibility study demand of an application system is detected, feasibility study information of the application feasibility study demand is obtained, and whether the application feasibility study demand meets the immediate allocation condition is determined based on the feasibility study information; if the application feasibility study demand meets the immediate allocation condition, the application feasibility study demand is determined as a feasibility study demand to be allocated; based on the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, it is determined whether the target container resource pool meets the capacity allocation condition; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs; if the feasibility study demand to be allocated does not meet the capacity allocation condition, the target container resource pool is expanded; and capacity is allocated for the application system based on the feasibility study information of the feasibility study demand to be allocated and the expanded target container resource pool.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and more specifically, to a container-based cloud native capacity management method, system, electronic device, and storage medium. Background Art

[0002] In recent years, cloud native technologies represented by containers and Kubernetes have developed rapidly, and cloud native technologies as the underlying cloud resources are also emerging. Cloud resources provide large-scale computing power and on-demand services, which improves resource utilization. However, given the continuous expansion of business systems, the cloud infrastructure and platform construction cycle of data centers is long. Therefore, how to coordinate the growth of container cloud resources and business and shorten the cloud infrastructure and platform construction cycle of data centers is a key issue that capacity management needs to solve. Among them, the capacity management of cloud containers involves business needs, feasibility study and evaluation of application systems, cloud resource capacity information (including total capacity, capacity utilization rate, capacity allocation rate, etc.), and cloud resource delivery information. Doing a good job in capacity management of the entire chain from demand to construction and then to delivery is an important guarantee for the stable growth of cloud resources in line with business.

[0003] Most of the existing capacity management technologies and methods are based on resource utilization for management and evaluation. Specifically, by dynamically acquiring resource utilization and using K8S's scheduling and orchestration capabilities, resources can be quickly expanded and contracted horizontally and vertically, thereby achieving elastic scaling. However, resources are not infinite. When resources are relatively scarce or temporarily scarce, monitoring only the single indicator of resource utilization cannot meet application needs, that is, effective capacity management cannot be achieved. Summary of the invention

[0004] In view of this, the present application provides a container-based cloud native capacity management method, system, electronic device and storage medium to achieve efficient use of resources when resources are insufficient and solve the problem in the prior art that monitoring of a single indicator, resource utilization, cannot meet application needs.

[0005] A first aspect of the present application provides a container-based cloud native capacity management method, the method comprising:

[0006] When an application feasibility study requirement of an application system is detected, feasibility study information of the application feasibility study requirement is obtained, and whether the application feasibility study requirement meets an immediate allocation condition is determined according to the feasibility study information;

[0007] If the application feasibility study requirement meets the immediate allocation condition, the application feasibility study requirement is determined as a feasibility study requirement to be allocated;

[0008] According to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, it is judged whether the target container resource pool meets the capacity allocation condition; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs;

[0009] If the feasibility study demand to be allocated does not meet the capacity allocation condition, the target container resource pool is expanded;

[0010] Capacity is allocated for the application system according to the feasibility study information of the feasibility study demand to be allocated and the target container resource pool after expansion.

[0011] Optionally, the method further includes:

[0012] If the application feasibility study requirement does not meet the immediate allocation condition, the application feasibility study requirement is stored in a local cache, and the cache time of the application feasibility study requirement is accumulated;

[0013] When it is detected that the cache time of the application feasibility study requirement reaches a preset time, the application feasibility study requirement is determined as a feasibility study requirement to be allocated.

[0014] Optionally, the feasibility study information of the feasibility study demand to be allocated includes a resource requirement of the feasibility study demand to be allocated, and the resource requirement is the sum of the capacity requirements of multiple container bases;

[0015] The determining, based on the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, whether the target container resource pool meets the capacity allocation condition includes:

[0016] Obtaining available resource information of the target container resource pool, wherein the available resource information includes available resources of the target container resource pool and a container base capacity of each available container base in the target container resource pool; the available resources are the sum of the container base capacities of each available container base;

[0017] Determine target available resources according to the available resources and the preset ratio, and judge whether the target available resources are less than the resource demand; wherein the target available resources are less than the available resources;

[0018] If the target available resources are not less than the resource requirements, determining whether there is a target container base capacity requirement among the container base capacity requirements;

[0019] If so, determining whether each of the target container base capacity requirements has a matching container base capacity;

[0020] If both exist, determining that the target container resource pool meets the capacity allocation condition;

[0021] If the target available resources are less than the resource requirements, or any of the target container base capacity requirements does not have a matching container base capacity, it is determined that the target container resource pool does not meet the capacity allocation condition.

[0022] Optionally, the method further includes:

[0023] Real-time detection of whether there is a target demand for the application system; the target demand is a demand related to the special matters of the application system;

[0024] When the target demand is detected, the target demand is determined as a feasibility study demand to be allocated.

[0025] Optionally, if the feasibility study demand to be allocated does not meet the capacity allocation condition, the target container resource pool is expanded, including:

[0026] If the feasibility study demand to be allocated does not meet the capacity allocation condition, obtaining the detection time of the feasibility study demand to be allocated, and determining the target time period to which the detection time belongs from various pre-set time periods;

[0027] Input the capacity growth rate corresponding to the target time period into the pre-trained container base capacity prediction model, so that the container base capacity prediction model predicts the growth rate to obtain the corresponding expansion step; wherein the expansion step includes the number of expansion container clusters, the number of expansion container bases of each expansion container cluster, and the container base capacity of each expansion container base;

[0028] The target container resource pool is expanded according to the expansion step.

[0029] Optionally, after allocating capacity for the application system, the method further includes:

[0030] Generating a capacity expansion record of the target container resource pool after the capacity expansion operation according to the capacity expansion step;

[0031] The resource pool information of the target container resource pool after the capacity expansion operation is updated according to the resource demand indicated in the feasibility study information.

[0032] A second aspect of the present application provides a container-based cloud native capacity management system, the system comprising:

[0033] A first judgment unit is used to, when detecting an application feasibility study requirement of an application system, obtain feasibility study information of the application feasibility study requirement, and judge whether the application feasibility study requirement meets an immediate allocation condition according to the feasibility study information;

[0034] A first determining unit is configured to determine the application feasibility study requirement as a feasibility study requirement to be allocated if the application feasibility study requirement meets the immediate allocation condition;

[0035] A second judgment unit is used to judge whether the target container resource pool meets the capacity allocation condition according to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs;

[0036] An expansion operation is used to expand the target container resource pool if the feasibility study demand to be allocated does not meet the capacity allocation condition;

[0037] The capacity allocation unit is used to allocate capacity for the application system according to the feasibility study information of the feasibility study demand to be allocated and the target container resource pool after expansion.

[0038] Optionally, the system further includes:

[0039] A storage unit, configured to store the application feasibility study requirement in a local cache and accumulate a cache time of the application feasibility study requirement if the application feasibility study requirement does not meet an immediate allocation condition;

[0040] The second determining unit is configured to determine the application feasibility study requirement as a feasibility study requirement to be allocated when it is detected that the cache time of the application feasibility study requirement reaches a preset time.

[0041] The third aspect of the present application provides an electronic device, comprising: a processor and a memory, wherein the processor and the memory are connected via a communication bus; wherein the processor is used to call and execute a program stored in the memory; and the memory is used to store a program, wherein the program is used to implement a container-based cloud native capacity management method as provided in the first aspect of the present application.

[0042] The fourth aspect of the present application provides a storage medium, in which computer-executable instructions are stored. The computer-executable instructions are used to execute a container-based cloud-native capacity management method as provided in the first aspect of the present application.

[0043] Therefore, the present application provides a container-based cloud native capacity management method, system, electronic device and storage medium. When an application feasibility study demand of an application system is detected, the feasibility study information of the application feasibility study demand is obtained, and whether the application feasibility study demand meets the immediate allocation condition is judged according to the feasibility study information; if the application feasibility study demand meets the immediate allocation condition, the application feasibility study demand is determined as a feasibility study demand to be allocated; according to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, it is judged whether the target container resource pool meets the capacity allocation condition; wherein, the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs; if the feasibility study demand to be allocated does not meet the capacity allocation condition, the target container resource pool is expanded; capacity is allocated for the application system according to the feasibility study information of the feasibility study demand to be allocated and the target container resource pool after expansion. It can be seen that the technical solution provided by the present application accurately evaluates whether the target container resource pool can currently allocate capacity for the application system by utilizing the received feasibility study information of the application feasibility study requirements and the available resource information of the target container resource pool to which it belongs; and when it is determined that capacity cannot be allocated for the application system, the target container resource pool is expanded to realize capacity allocation for the application system. This can not only achieve efficient utilization of resources when resources are insufficient, but also solve the problem in the prior art that when resources are relatively scarce or temporarily scarce, the monitoring of a single indicator of resource utilization cannot meet application needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0045] Figure 1 A flowchart of a container-based cloud native capacity management method provided in an embodiment of the present application;

[0046] Figure 2 An example diagram of capacity management of a container resource pool provided in an embodiment of the present application;

[0047] Figure 3 A schematic diagram of the structure of a container-based cloud native capacity management system provided in an embodiment of the present application;

[0048] Figure 4 A schematic diagram of the structure of a container-based cloud native capacity management provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0050] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0051] From the above background technology, it can be seen that the existing capacity management technologies and means are mostly based on resource utilization for management and evaluation, but for capacity management, it is necessary to process multi-source data. Taking container cloud native resources as an example, the container base resources are the total resources for capacity management, and the resources required for feasibility study are demand resources. Simply put, capacity evaluation is to see whether the existing resource volume meets the feasibility study requirements of the application system, but the actual situation is much more complicated. For example: In the face of insufficient container cloud native and the rapid development of application containerization, it is necessary to conduct application feasibility study under the construction of container base at the same time. However, the capacity evaluation of feasibility study is only a promised resource volume, not the actual divided capacity, so it cannot be evaluated only with existing resources, and the promised resource volume also needs to be recorded. Therefore, the target capacity Tuanxi technical scenarios are all discussed under the condition of sufficient resources. When resources are relatively scarce or temporarily scarce, the monitoring of a single indicator such as resource utilization cannot meet the application requirements, that is, effective capacity management cannot be achieved.

[0052] Therefore, the present application provides a container-based cloud native capacity management method, system, electronic device and storage medium, which accurately evaluates whether the target container resource pool can currently allocate capacity for the application system by utilizing the received feasibility information of the application feasibility study requirements and the available resource information of the target container resource pool to which it belongs; and when it is determined that capacity cannot be allocated for the application system, the target container resource pool is expanded to realize capacity allocation for the application system. This can not only achieve efficient utilization of resources when resources are insufficient, but also solve the problem in the prior art that when resources are relatively scarce or temporarily scarce, the monitoring of a single indicator, namely resource utilization, cannot meet application needs.

[0053] See also Figure 1 , shows a flow chart of a container-based cloud native capacity management method provided in an embodiment of the present application, and the container-based cloud native capacity management method specifically includes the following steps:

[0054] S101: When an application feasibility study requirement of an application system is detected, feasibility study information of the application feasibility study requirement is obtained, and whether the application feasibility study requirement meets an immediate allocation condition is determined according to the feasibility study information.

[0055] In the embodiment of the present application, when the application system has a demand for cloud computing, it is necessary to apply for a feasibility study, referred to as a feasibility study. That is to say, when the application system has an application feasibility study demand, it is necessary to apply for a corresponding feasibility study; after the feasibility study is passed, the application system can be put into production and provide services. The feasibility study includes the review of the application system solution. For a data center with cloud native resources (multiple container resource pools), an important part of the feasibility study is the evaluation of the resources required by the application system (the resource requirements indicated in the application feasibility study requirements). This involves capacity management, that is, evaluating the resource requirements indicated by the application feasibility study requirements, and feedback on the resource satisfaction. For existing resources that do not meet the needs, cloud native resources need to be built, that is, the existing capacity resource pool does not meet the resource requirements indicated by the application feasibility study requirements, and corresponding capacity expansion processing (cloud native resource construction) is required; after the construction delivery is completed, the capacity management information of the container resource pool needs to be updated synchronously, so as to realize capacity management as the center, connect the application feasibility study requirements with the construction delivery, and help the application container cloud native process.

[0056] Therefore, in the actual application process, it is possible to detect in real time whether there is an application feasibility study demand for the application system; when the application feasibility study demand for the application system is detected, the feasibility study information of the application feasibility study demand can be obtained, wherein the feasibility study information of the application feasibility study demand may include the feasibility study order number, feasibility study level, application system to which it belongs, resource requirements, feasibility study progress, delivery progress, implementer and container resource pool number, etc., as shown in Table 1. Determine whether the feasibility study level in the feasibility study information of the application feasibility study demand belongs to a high level; if not, determine that the application feasibility study demand does not meet the immediate allocation condition, and then execute step S102; if it does, determine that the application feasibility study demand meets the immediate allocation condition, and then immediately enter the corresponding feasibility study process, and then execute step S104. Among them, the immediate allocation condition indicates that the high-level application feasibility study demand needs to enter the feasibility study process immediately to make corresponding capacity allocation for the application feasibility study demand.

[0057] Table 1:

[0058]

[0059] It should be noted that the resource requirement of the application feasibility study is the sum of the capacity requirements of multiple container bases; for example, the resource requirement is 20C, including 4 5C container base capacity requirements; or, the capacity requirement of a 10C container base is 10C and 2 5C container base capacity requirements.

[0060] Furthermore, in an embodiment of the present application, it is also possible to detect in real time whether the current application system meets the target requirement; wherein the target requirement is a requirement related to a special matter of the application system; when the target requirement is detected, the target requirement can be directly confirmed as a feasibility study requirement to be allocated, and then step S104 can be performed.

[0061] It should be noted that the demands related to special matters may be the demands related to major transformation matters. For example, the target demands may be the demands for information technology transformation, etc., which are not limited in the embodiments of this application.

[0062] S102: Storing the application feasibility study requirements in a local cache, and accumulating the cache time of the application feasibility study requirements.

[0063] In the process of specifically executing step S102, when it is determined that the feasibility level of the application feasibility study requirement is not a high level, it can be considered that the application feasibility study requirement does not need to be processed immediately; in order to ensure that high-level application feasibility study requirements or target requirements can be processed first, the application feasibility study requirement can be stored in the local cache first; when storing the application feasibility study requirement in the local cache, the cache time of the application feasibility study requirement can also be accumulated.

[0064] S103: Determine whether the cache time of the application feasibility study requirement reaches the preset time; if so, execute step S104.

[0065] In the specific process of executing step S104, in order to ensure the validity of the application feasibility study requirements, a corresponding preset time can be set in advance, and the cache time of the application feasibility study requirements can be detected in real time. When the cache time of the application feasibility study requirements reaches the preset time, the corresponding feasibility study process is entered, and then step S104 can be executed. If the cache time of the application feasibility study requirements has not reached the preset time, the cache time of the application feasibility study requirements continues to be accumulated, and step S103 is executed.

[0066] It should be noted that the corresponding preset time can be set according to the actual application. For example, the preset time can be 1 day, 2 days, 5 days, etc., which is not limited in the embodiment of the present application.

[0067] S104: Determine the application feasibility study requirements as the feasibility study requirements to be allocated.

[0068] In the specific process of executing step S104, when it is determined that the application feasibility study demand meets the immediate allocation condition, or the cache time of the application feasibility study demand reaches the preset time, or the target demand of the application system is detected, the application feasibility study demand or the target demand can be determined as the feasibility study demand to be allocated, so as to perform corresponding feasibility study process and capacity management on the application feasibility study demand, that is, execute step S105.

[0069] S105: According to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, determine whether the target container resource pool meets the capacity allocation condition; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs. If the target container resource pool meets the capacity allocation condition, execute step S106.

[0070] In the specific execution of step S105, when there is a feasibility study demand to be allocated, the container resource pool corresponding to the container resource pool number indicated in the feasibility study information of the feasibility study demand to be allocated in each container resource pool in the data center can be determined as the target container resource pool, and the available resource information of the target container resource pool is obtained, wherein the available resource information includes the available resources of the target container resource pool and the container base capacity of each available container base in the target container resource pool; the available resources are the sum of the container base capacities of each available container base; based on the resource requirements of the feasibility study demand to be allocated, the capacity requirements of each container base, the available resources and the container base capacity of each available container base, it is determined whether the target container resources meet the capacity allocation conditions; if not, step S106 can be executed; if satisfied, corresponding capacity allocation can be made for the application system based on the feasibility study information of the feasibility study demand to be allocated and the target container resource pool.

[0071] In some embodiments, the resource pool information of the target container resource pool can be directly obtained, wherein the resource pool information may include the container cluster, total capacity, allocated capacity, capacity allocation rate, available resources, total feasibility study demand (committed resources), number of divisible pods (number of allocatable container bases), etc. of the target container resource pool, as shown in Table 2.

[0072] Table 2:

[0073]

[0074] Among them, it can be seen from Table 2 that the target container resource pool can have at least one container cluster, and each container cluster is composed of multiple container bases (i.e., machines, which can be virtual machines or physical machines); and the container base capacity of the container base is the resource capacity of the container when it is first built. The sum of the capacities of each container base can be regarded as the initialization of the total capacity of the cloud native resource pool, that is, the total capacity at the beginning of the target container resource pool; when the target container resource pool does not meet the capacity allocation conditions, that is, it cannot meet the feasibility study requirements to be allocated, it is necessary to expand the target container resource pool, that is, execute step S106; it can be seen that capacity management can have two sources, one is the capacity of each container base, and the other is the expanded capacity obtained after expansion, such as Figure 2 shown.

[0075] It should be noted that the sum of the capacities of each container base is the total capacity of the container resource pool; as can be seen from Table 2, the total capacity of the container resource pool is also equal to the sum of the allocated capacity, available resources and total feasibility study requirements.

[0076] In some embodiments, corresponding capacity allocation conditions can be set in advance, wherein the capacity allocation conditions can indicate that the target available resources of the target container resource pool are not less than the resource requirements of the feasibility study requirements to be allocated, and each target container base capacity requirement constituting the resource requirement has a matching container base capacity.

[0077] It should be noted that a container base capacity requirement greater than a preset capacity may be determined as a target container base capacity requirement; for example, the preset capacity may be 8C, and then a container base capacity requirement greater than 8C may be determined as a target container base capacity requirement.

[0078] Optionally, the process of judging whether the target container resource pool meets the capacity allocation conditions according to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool can be specifically as follows: obtaining the available resource information of the target container resource pool; determining the target available resources according to the available resources and the preset ratio, and judging whether the target available resources are less than the resource requirements, wherein the target available resources are less than the available resources; if the target available resources are not less than the resource requirements, judging whether there is a target container base capacity requirement in each container base capacity requirement; if so, judging whether each target container base capacity requirement has a matching container base capacity; if so, judging whether the target container base capacity requirement has a matching container base capacity; if so, judging that the target container resource pool meets the capacity allocation conditions, and capacity allocation can be performed for the application system according to the resource requirements of the feasibility study demand to be allocated and the available resources of the target container resource pool; if the target available resources are less than the resource requirements, or any target container base capacity requirement does not have a matching container base capacity, judging that the target container resource pool does not meet the capacity allocation conditions, and then executing step S106.

[0079] In some embodiments, a container base capacity that is not less than a target container base capacity requirement may be determined as a container base capacity that matches the target container base capacity requirement.

[0080] In an embodiment of the present application, the process of allocating capacity for an application system based on the resource requirements of the feasibility study requirements to be allocated and the available resources of the target container resource pool can be: determining the container base capacity that matches each container base capacity requirement from the container base capacities of each available container base in the target container resource pool, and putting into production the corresponding container base capacity requirement on the available container base corresponding to the container base capacity that matches each container base capacity requirement, so as to complete the capacity allocation for the application system.

[0081] Furthermore, in an embodiment of the present application, the available resources of the target container resource pool are subtracted from the resource requirements of the feasibility study requirements to be allocated to complete the update of the available resources of the target container resource pool; it is detected whether there are resources that have been put into production in the committed resources of the target resource pool. If so, the committed resources of the target resource pool can be updated; finally, the allocated capacity and capacity allocation rate of the target resource pool are updated.

[0082] In actual application, in order to ensure the stable application of the target container resource pool, the capacity of the target container resource pool cannot be fully allocated. Therefore, a corresponding preset ratio can be set. After determining the available resources of the target resource pool, the product of the available resources and the preset ratio can be calculated to obtain the target available resources. For example, the preset ratio can be 90%. If the available resources are 100C, the target available resources can be 90%.

[0083] Further, in the embodiment of the present application, the applicant has found through research that if the capacity allocation rate of the target container resource pool reaches a certain value, capacity allocation will no longer be performed, and resource expansion will be performed directly, that is, step S106 will be directly executed. Therefore, the corresponding capacity allocation rate threshold can be pre-set. When there is a feasibility study demand to be allocated, the resource pool information of the target container resource pool can be obtained, and it can be determined whether the capacity allocation rate in the resource pool information is less than the capacity allocation rate threshold. If it is less than, step S105 is executed to further determine whether the target container resource pool meets the capacity allocation conditions; if it is not less than, step S106 can be directly executed to perform the corresponding resource expansion operation.

[0084] For example, the preset ratio is 90%, the capacity allocation rate threshold is 80%, and the preset capacity is 8C; when there is a feasibility study demand to be allocated, the target container resource pool to which the feasibility study demand to be allocated belongs can be determined according to the container resource pool number in the feasibility study information of the feasibility study demand to be allocated; the resource pool information of the target container resource pool is obtained, wherein the capacity allocation rate in the resource pool information is 75%, the available resources are 30C, and the container base capacities of each available container base are 10C, 5C, 5C, 5C and 5C respectively; since the capacity allocation rate of the target container resource pool (75%) is not greater than the capacity allocation rate threshold (80%), the product of the available resources and the preset ratio can be calculated, and the target available resources are 24; if the resource demand of the feasibility study demand to be allocated is 20 C, it can be determined that the target available resources are greater than the resource demand; if the container base capacity demands that constitute the resource demand are 10C, 5C and 5C respectively, it can be determined that there is a target container base capacity demand (10C) in each container base capacity demand, and the target container base capacity demand has a matching container base capacity demand (10C), therefore, it can be determined that the target container resource pool meets the capacity allocation conditions; if the container base capacity demands that constitute the resource demand are allocated 10C and 10C, it can be determined that there are two target container base capacity demands in each container base capacity demand, and only one target container base capacity demand has a matching container base capacity, therefore, it can be determined that the target container resource pool does not meet the capacity allocation conditions.

[0085] S106: Expand the target container resource pool.

[0086] In the process of specifically executing step S106, when it is determined that the target container resource pool does not meet the capacity allocation conditions, the target container resource pool can be further expanded. At the same time, in order to adapt to the rapid development of containerization and cloud nativeization and ensure the efficiency of resource application on demand, when expanding the target container resource pool, the target container resource pool can be expanded according to the corresponding capacity growth rate, rather than only expanding the target container resource pool according to resource demand. This ensures that not only frequent expansion operations for the container resource pool can be avoided, but also the availability and efficiency of the container resource pool can be guaranteed.

[0087] In the embodiment of the present application, the applicant has discovered through research that there is a certain capacity growth law in the container resource pool, and the corresponding time period and capacity growth rate can be set according to the corresponding growth law; at the same time, the corresponding historical capacity growth rate information can also be obtained, wherein the historical capacity growth rate information includes the historical capacity growth rate and the target expansion step; the historical capacity growth rate information is input into the container base capacity prediction model to be trained, so that the container base capacity prediction model to be trained makes a prediction based on the historical capacity growth rate to obtain the predicted expansion step, and the parameters of the container base capacity prediction model to be trained are adjusted with the predicted expansion step approaching the target expansion step as the training goal, until the container base capacity prediction model to be trained converges to obtain the container base capacity prediction model.

[0088] Optionally, the process of expanding the capacity of the target container resource pool may specifically be: obtaining the detection time of the feasibility study demand to be allocated, and determining the target time period to which the detection time belongs from various pre-set time periods; inputting the capacity growth rate corresponding to the target time period into a pre-trained container base capacity prediction model, so that the container base capacity prediction model predicts the growth rate and obtains a corresponding expansion step; and expanding the target container resource pool according to the expansion step.

[0089] It should be noted that the expansion step includes the number of expansion container clusters, the number of expansion container bases of each expansion container cluster, and the container base capacity of each expansion container base.

[0090] In some embodiments, the process of expanding the target container resource pool according to the expansion step may be as follows: according to the expansion step, constructing a number of expansion container clusters in the target container resource pool (for ease of distinction, the expanded container clusters are referred to as expansion container clusters); according to the number of expansion container bases in each expansion container cluster indicated in the expansion step and the container base capacity of each expansion container base, constructing a corresponding number of container bases in each expansion container cluster and the container base capacity corresponding to each container base.

[0091] It should be noted that the container base constructed during the expansion of the target container resource pool may be an available container base.

[0092] S107: Allocate capacity for the application system according to the feasibility study information of the feasibility study demand to be allocated and the target container resource pool after expansion.

[0093] In the process of specifically executing step S107, after the target container resource pool is expanded, the container base capacity that matches each container base capacity requirement can be determined from the container base capacities of each available container base in the expanded target container resource pool, and the corresponding container base capacity requirement can be put into production on the available container base corresponding to the container base capacity that matches each container base capacity requirement to complete the capacity allocation for the application system.

[0094] Furthermore, in an embodiment of the present application, after capacity is allocated to the application system, an expansion record of the target container resource pool after the expansion operation can be further generated according to the obtained expansion step; at the same time, the resource pool information of the target container resource pool after the expansion operation can be updated according to the resource requirements indicated in the feasibility study information.

[0095] The expansion record may include the number of container clusters of the target container resource pool after the expansion operation, the number of container bases of each container cluster (number of cluster nodes), the container base capacity of each container base (cluster node specification), the increased capacity (the sum of the container base capacities of each expanded container base), and the construction / expansion time of each expanded container cluster, as shown in Table 3;

[0096] Table 3:

[0097]

[0098] In some embodiments, the total capacity of the target resource pool after the expansion operation is detected can be updated; the available resources of the target container resource pool after the expansion operation are subtracted from the resource requirements of the feasibility study requirements to be allocated to complete the update of the available resources of the target container resource pool after the expansion operation; it is detected whether there are resources that have been put into production in the committed resources of the target resource pool after the expansion operation. If so, the committed resources of the target resource pool after the expansion operation can be updated; finally, the allocated capacity and capacity allocation rate of the target resource pool after the expansion operation are updated.

[0099] The present application provides a container-based cloud native capacity management method. When an application feasibility study demand of an application system is detected, feasibility study information of the application feasibility study demand is obtained, and whether the application feasibility study demand meets the immediate allocation condition is determined according to the feasibility study information; if the application feasibility study demand meets the immediate allocation condition, the application feasibility study demand is determined as a feasibility study demand to be allocated; according to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, whether the target container resource pool meets the capacity allocation condition; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs; if the feasibility study demand to be allocated does not meet the capacity allocation condition, the target container resource pool is expanded; and capacity is allocated for the application system according to the feasibility study information of the feasibility study demand to be allocated and the target container resource pool after expansion. It can be seen that the technical solution provided by the present application accurately evaluates whether the target container resource pool can currently allocate capacity for the application system by utilizing the received feasibility study information of the application feasibility study requirements and the available resource information of the target container resource pool to which it belongs; and when it is determined that capacity cannot be allocated for the application system, the target container resource pool is expanded to realize capacity allocation for the application system. This can not only achieve efficient utilization of resources when resources are insufficient, but also solve the problem in the prior art that when resources are relatively scarce or temporarily scarce, the monitoring of a single indicator of resource utilization cannot meet application needs.

[0100] Based on the container-based cloud native capacity management method provided in the above-mentioned embodiment of the present application, correspondingly, the embodiment of the present application also provides a container-based cloud native capacity management system, such as Figure 3 As shown in the figure, the container-based cloud native capacity management system includes:

[0101] The first judgment unit 31 is used to obtain feasibility study information of the application feasibility study demand when the application system's application feasibility study demand is detected, and judge whether the application feasibility study demand meets the immediate allocation condition according to the feasibility study information;

[0102] The first determining unit 32 is configured to determine the application feasibility study requirement as a feasibility study requirement to be allocated if the application feasibility study requirement meets the immediate allocation condition;

[0103] The second judgment unit 33 is used to judge whether the target container resource pool meets the capacity allocation condition according to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs;

[0104] The capacity expansion operation 34 is used to expand the target container resource pool if the feasibility study demand to be allocated does not meet the capacity allocation conditions;

[0105] The capacity allocation unit 35 is used to allocate capacity for the application system according to the feasibility study information of the feasibility study demand to be allocated and the target container resource pool after expansion.

[0106] The specific principles and execution processes of each unit in the container-based cloud native capacity management system disclosed in the above-mentioned embodiment of the present application are the same as the container-based cloud native capacity management method disclosed in the above-mentioned embodiment of the present application. Please refer to the corresponding parts of the container-based cloud native capacity management method disclosed in the above-mentioned embodiment of the present application, and no further details will be given here.

[0107] The present application provides a container-based cloud native capacity management system. When an application feasibility study demand of an application system is detected, the feasibility study information of the application feasibility study demand is obtained, and whether the application feasibility study demand meets the immediate allocation condition is determined based on the feasibility study information; if the application feasibility study demand meets the immediate allocation condition, the application feasibility study demand is determined as a feasibility study demand to be allocated; based on the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, it is determined whether the target container resource pool meets the capacity allocation condition; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs; if the feasibility study demand to be allocated does not meet the capacity allocation condition, the target container resource pool is expanded; and capacity is allocated to the application system based on the feasibility study information of the feasibility study demand to be allocated and the expanded target container resource pool. It can be seen that the technical solution provided by the present application accurately evaluates whether the target container resource pool can currently allocate capacity for the application system by utilizing the received feasibility study information of the application feasibility study requirements and the available resource information of the target container resource pool to which it belongs; and when it is determined that capacity cannot be allocated for the application system, the target container resource pool is expanded to realize capacity allocation for the application system. This can not only achieve efficient utilization of resources when resources are insufficient, but also solve the problem in the prior art that when resources are relatively scarce or temporarily scarce, the monitoring of a single indicator of resource utilization cannot meet application needs.

[0108] Optionally, the container-based cloud native capacity management system provided in the embodiment of the present application further includes:

[0109] A storage unit, used for storing the application feasibility study requirement in a local cache if the application feasibility study requirement does not meet the immediate allocation condition, and accumulating the cache time of the application feasibility study requirement;

[0110] The second determining unit is configured to determine the application feasibility study requirement as the feasibility study requirement to be allocated when it is detected that the cache time of the application feasibility study requirement of the application system reaches a preset time.

[0111] Optionally, the feasibility study information of the feasibility study demand to be allocated includes a resource requirement of the feasibility study demand to be allocated, and the resource requirement is the sum of the capacity requirements of multiple container bases; the second judgment unit includes:

[0112] An available resource information acquisition unit is used to acquire available resource information of a target container resource pool if the feasibility study demand to be allocated does not meet the capacity allocation condition, wherein the available resource information includes available resources of the target container resource pool and the container base capacity of each available container base in the target container resource pool; the available resources are the sum of the container base capacities of each available container base;

[0113] A third judgment unit is used to determine the target available resources according to the available resources and the preset ratio, and to judge whether the target available resources are less than the resource demand; wherein the target available resources are less than the available resources;

[0114] A fourth judgment unit, configured to judge whether there is a target container base capacity requirement among the container base capacity requirements if the target available resources are not less than the resource requirement;

[0115] A fifth judgment unit, used for judging whether there is a matching container base capacity for each target container base capacity requirement, if any;

[0116] A third determining unit is used to determine that the target container resource pool meets the capacity allocation condition if both exist;

[0117] The fourth determining unit is used to determine that the target container resource pool does not meet the capacity allocation condition if the target available resources are less than the resource requirements, or there is no matching container base capacity for any target container base capacity requirement.

[0118] Optionally, the container-based cloud native capacity management system provided in the embodiment of the present application further includes:

[0119] A real-time detection unit is used to detect in real time whether there is a target demand of the application system at present; wherein the target demand is a demand related to a special matter of the application system;

[0120] The fifth determining unit is used to determine the target demand as the feasibility study demand to be allocated when the target demand is detected.

[0121] Optional expansion unit, including:

[0122] A sixth determining unit, configured to obtain the detection time of the feasibility study requirement to be allocated, and determine the target time period to which the detection time belongs from various pre-set time periods;

[0123] A prediction unit is used to input the capacity growth rate corresponding to the target time period into a pre-trained container base capacity prediction model, so that the container base capacity prediction model predicts the growth rate to obtain a corresponding expansion step; wherein the expansion step includes the number of expansion container clusters, the number of expansion container bases of each expansion container cluster, and the container base capacity of each expansion container base;

[0124] The expansion subunit is used to expand the target container resource pool according to the expansion step.

[0125] Optionally, the container-based cloud native capacity management system provided in the embodiment of the present application further includes:

[0126] An expansion record generating unit, used to generate an expansion record of a target container resource pool after the expansion operation according to the expansion step;

[0127] The updating unit is used to update the resource pool information of the target container resource pool after the capacity expansion operation according to the resource demand indicated in the feasibility study information.

[0128] The present application also provides a storage medium, which stores computer-executable instructions. When the computer-readable instructions are loaded and executed by a processor, any of the above-mentioned container-based cloud native capacity management method embodiments is implemented.

[0129] The present application also provides an electronic device, such as Figure 4 As shown, the electronic device includes a processor 401 and a memory 402; a program is stored in the memory; the processor calls the program in the memory to execute any one of the above-mentioned container-based cloud native capacity management method embodiments.

[0130] The processor in the present application may be a CPU of a terminal, or an MCU integrated in the terminal, or a combination of a CPU and an MCU. Moreover, the processor includes a kernel, which retrieves a corresponding program from a memory, and one or more kernels may be provided.

[0131] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0132] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, in which the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0133] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0134] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0135] The above are only preferred implementations of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A container-based cloud native capacity management method, characterized in that: The method comprises: When an application feasibility study requirement of an application system is detected, feasibility study information of the application feasibility study requirement is obtained, and whether the application feasibility study requirement meets an immediate allocation condition is determined according to the feasibility study information; If the application feasibility study requirement meets the immediate allocation condition, the application feasibility study requirement is determined as a feasibility study requirement to be allocated; According to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, it is judged whether the target container resource pool meets the capacity allocation condition; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs; If the feasibility study demand to be allocated does not meet the capacity allocation condition, the target container resource pool is expanded; Capacity is allocated for the application system according to the feasibility study information of the feasibility study demand to be allocated and the target container resource pool after expansion.

2. The method according to claim 1, characterized in that The method further comprises: If the application feasibility study requirement does not meet the immediate allocation condition, the application feasibility study requirement is stored in a local cache, and the cache time of the application feasibility study requirement is accumulated; When it is detected that the cache time of the application feasibility study requirement reaches a preset time, the application feasibility study requirement is determined as a feasibility study requirement to be allocated.

3. The method according to claim 1, characterized in that The feasibility study information of the feasibility study demand to be allocated includes the resource requirement of the feasibility study demand to be allocated, and the resource requirement is the sum of the capacity requirements of multiple container bases; The determining, based on the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool, whether the target container resource pool meets the capacity allocation condition includes: Obtaining available resource information of the target container resource pool, wherein the available resource information includes available resources of the target container resource pool and a container base capacity of each available container base in the target container resource pool; the available resources are the sum of the container base capacities of each available container base; Determine target available resources according to the available resources and the preset ratio, and judge whether the target available resources are less than the resource demand; wherein the target available resources are less than the available resources; If the target available resources are not less than the resource requirements, determining whether there is a target container base capacity requirement among the container base capacity requirements; If so, determining whether each of the target container base capacity requirements has a matching container base capacity; If both exist, it is determined that the target container resource pool meets the capacity allocation condition; If the target available resources are less than the resource requirements, or any of the target container base capacity requirements does not have a matching container base capacity, it is determined that the target container resource pool does not meet the capacity allocation condition.

4. The method according to claim 1, characterized in that: The method further comprises: Real-time detection of whether there is a target demand for the application system; the target demand is a demand related to the special matters of the application system; When the target demand is detected, the target demand is determined as a feasibility study demand to be allocated.

5. The method according to claim 1, characterized in that If the feasibility study demand to be allocated does not meet the capacity allocation condition, the target container resource pool is expanded, including: If the feasibility study demand to be allocated does not meet the capacity allocation condition, obtaining the detection time of the feasibility study demand to be allocated, and determining the target time period to which the detection time belongs from various pre-set time periods; Input the capacity growth rate corresponding to the target time period into the pre-trained container base capacity prediction model, so that the container base capacity prediction model predicts the growth rate to obtain the corresponding expansion step; wherein the expansion step includes the number of expansion container clusters, the number of expansion container bases of each expansion container cluster, and the container base capacity of each expansion container base; The target container resource pool is expanded according to the expansion step.

6. The method according to claim 5, characterized in that After allocating capacity for the application system, the method further includes: Generating a capacity expansion record of the target container resource pool after the capacity expansion operation according to the capacity expansion step; The resource pool information of the target container resource pool after the capacity expansion operation is updated according to the resource demand indicated in the feasibility study information.

7. A container-based cloud native capacity management system, characterized in that: The system comprises: A first judgment unit is used to, when detecting an application feasibility study requirement of an application system, obtain feasibility study information of the application feasibility study requirement, and judge whether the application feasibility study requirement meets an immediate allocation condition according to the feasibility study information; A first determining unit is configured to determine the application feasibility study requirement as a feasibility study requirement to be allocated if the application feasibility study requirement meets the immediate allocation condition; A second judgment unit is used to judge whether the target container resource pool meets the capacity allocation condition according to the feasibility study information of the feasibility study demand to be allocated and the available resource information of the target container resource pool; wherein the target container resource pool is the container resource pool to which the feasibility study demand to be allocated belongs; An expansion operation is used to expand the target container resource pool if the feasibility study demand to be allocated does not meet the capacity allocation condition; The capacity allocation unit is used to allocate capacity for the application system according to the feasibility study information of the feasibility study demand to be allocated and the target container resource pool after expansion.

8. The system according to claim 7, characterized in that The system further comprises: A storage unit, configured to store the application feasibility study requirement in a local cache and accumulate a cache time of the application feasibility study requirement if the application feasibility study requirement does not meet an immediate allocation condition; The second determining unit is configured to determine the application feasibility study requirement as a feasibility study requirement to be allocated when it is detected that the cache time of the application feasibility study requirement reaches a preset time.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the processor and the memory are connected via a communication bus; wherein the processor is used to call and execute a program stored in the memory; The memory is used to store a program, and the program is used to implement a container-based cloud native capacity management method as described in any one of claims 1-6.

10. A storage medium, characterized in that: The storage medium stores computer-executable instructions, and the computer-executable instructions are used to execute a container-based cloud-native capacity management method as described in any one of claims 1-6.

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