CN110677459A - Resource adjusting method and device, computer equipment and computer storage medium - Google Patents
Resource adjusting method and device, computer equipment and computer storage medium Download PDFInfo
- Publication number
- CN110677459A CN110677459A CN201910824481.0A CN201910824481A CN110677459A CN 110677459 A CN110677459 A CN 110677459A CN 201910824481 A CN201910824481 A CN 201910824481A CN 110677459 A CN110677459 A CN 110677459A
- Authority
- CN
- China
- Prior art keywords
- resource
- service nodes
- preset
- node
- index value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1004—Server selection for load balancing
- H04L67/1012—Server selection for load balancing based on compliance of requirements or conditions with available server resources
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1029—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers using data related to the state of servers by a load balancer
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Debugging And Monitoring (AREA)
Abstract
The application relates to a resource adjusting method, a resource adjusting device, computer equipment and a computer storage medium. The method comprises the following steps: acquiring resource use data of each service node in at least two service nodes; processing the resource use data of each service node to obtain resource index values corresponding to the at least two service nodes; and when the resource index value meets the corresponding preset condition, adjusting the number of the service nodes according to a preset node adjustment rule. By adopting the scheme of the application, the resource adjustment efficiency can be improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a resource adjustment method, an apparatus, a computer device, and a computer storage medium.
Background
Services may be deployed and hosted in virtual machines or containers, and the like. In a distributed system environment, there are a large number of service nodes, and a server needs to monitor the resource usage of each service node. When the system load is high, a new service node is needed to meet the calculation requirement. When the system load is reduced, service resources need to be recovered, and waste is avoided. However, the conventional resource adjusting method has a problem of low resource adjusting efficiency.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a resource adjustment method, device, computer device, and computer storage medium, which can improve resource adjustment efficiency.
A method of resource adjustment, the method comprising:
acquiring resource use data of each service node in at least two service nodes;
processing the resource use data of each service node to obtain resource index values corresponding to the at least two service nodes;
and when the resource index value meets the corresponding preset condition, adjusting the number of the service nodes according to a preset node adjustment rule.
In one embodiment, the resource usage data includes at least one of central processor usage, memory usage, number of used thread pools, and response time; each resource usage data corresponds to a resource indicator value.
When the resource index value meets the corresponding preset condition, adjusting the number of service nodes according to a preset node adjustment rule, including:
and when at least one resource index value meets the corresponding preset condition, adjusting the number of service nodes according to a preset node adjustment rule.
In one embodiment, the obtaining the resource index values corresponding to the at least two service nodes by processing the resource usage data of each service node includes:
processing the resource use data of each service node according to the priority of the resource use data to obtain resource index values corresponding to the at least two service nodes, wherein each resource use data corresponds to one resource index value;
when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to a preset node adjustment rule, and the method comprises the following steps:
and when a target resource index value meeting the corresponding preset condition is detected according to the priority, adjusting the number of service nodes according to a preset node rule corresponding to the target resource index value.
In one embodiment, the resource adjusting method further includes:
acquiring a resource index value corresponding to each period in continuous preset number periods;
when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to a preset node adjustment rule, and the method comprises the following steps:
and when the resource index value corresponding to each period meets the corresponding preset condition, adjusting the number of service nodes according to a preset node adjustment rule.
In one embodiment, the preset node adjustment rule includes a preset capacity expansion rule and a preset capacity reduction rule;
when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to a preset node adjustment rule, and the method comprises the following steps:
when the resource index value is greater than or equal to the corresponding index upper limit threshold value, increasing the number of service nodes according to the preset capacity expansion rule;
and when the resource index value is smaller than the corresponding index lower limit threshold, reducing the number of service nodes according to the preset capacity reduction rule.
In one embodiment, the obtaining the resource index values corresponding to the at least two service nodes by processing the resource usage data of each service node includes:
and carrying out weighted average processing on the resource utilization data of each service node to obtain resource index values corresponding to the at least two service nodes.
In one embodiment, the resource adjusting method further includes:
and when the timing is started after the number of the service nodes is adjusted, the preset time is reached, and the resource index value meets the corresponding preset condition, continuing to execute the step of adjusting the number of the service nodes according to the node adjustment rule.
An apparatus for resource adjustment, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring resource use data of each service node in at least two service nodes;
the processing module is used for processing the resource use data of each service node to obtain resource index values corresponding to the at least two service nodes;
and the adjusting module is used for adjusting the number of the service nodes according to a preset node adjusting rule when the resource index value meets the corresponding preset condition.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring resource use data of each service node in at least two service nodes;
processing the resource use data of each service node to obtain resource index values corresponding to the at least two service nodes;
and when the resource index value meets the corresponding preset condition, adjusting the number of the service nodes according to a preset node adjustment rule.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring resource use data of each service node in at least two service nodes;
processing the resource use data of each service node to obtain resource index values corresponding to the at least two service nodes;
and when the resource index value meets the corresponding preset condition, adjusting the number of the service nodes according to a preset node adjustment rule.
The resource adjusting method, the resource adjusting device, the computer equipment and the storage medium acquire the resource use data of each service node in at least two service nodes, process the resource use data of each service node to obtain the resource index values corresponding to the at least two service nodes, not only consider the resource use data of a single node, but also obtain one resource index value corresponding to all the service nodes; when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjustment rule, the number of the service nodes can be quickly and automatically adjusted according to the requirement and the preset node adjustment rule, management personnel are not required to intervene, and the resource adjustment efficiency can be improved.
Drawings
FIG. 1 is a diagram of an application environment of a resource adjustment method in one embodiment;
FIG. 2 is a flow diagram illustrating a resource adjustment method according to an embodiment;
FIG. 3 is a flowchart illustrating a resource adjustment method according to another embodiment;
FIG. 4 is a flowchart illustrating a resource adjustment method according to another embodiment;
FIG. 5 is a block diagram of an apparatus for resource adjustment according to an embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The resource adjustment method provided in the embodiment of the present application may be applied to an application environment shown in fig. 1. The server 102 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.
In one embodiment, as shown in fig. 2, a resource adjustment method is provided, which is described by taking the method as an example applied to the server 102 in fig. 1, and includes the following steps:
Wherein the service node may be a data distribution point. The service node may be a microservice node. The microservice architecture can be used to deploy applications and services in the cloud. The microservice node is a node in the microservice architecture. The service node may specifically be a virtual machine or a container. A virtual machine refers to a complete computer system with complete hardware system functionality, which is emulated by software and runs in a completely isolated environment. The container can provide a resource independent running environment for the application software and the dependent components thereof. A server may contain multiple service nodes. The at least two service nodes may be all service nodes on the server, or all service nodes in the server cluster. The resource usage data may be load data of the server. For example, the resource usage data may be at least one of central processor usage, memory usage, number of idle thread pools, number of used thread pools, and response time.
Specifically, the server monitors the resource usage of each service node in real time. The server acquires resource use data of each service node in all service nodes under the same server cluster, wherein the number of the service nodes is at least two.
In this embodiment, the server obtains resource usage data of each service node in all service nodes in the same server cluster at the same time.
In this embodiment, the server obtains resource usage data of each service node in all service nodes in the same server cluster in the same time period.
And step 204, processing the resource use data of each service node to obtain resource index values corresponding to at least two service nodes.
The resource index value refers to a value corresponding to a certain resource index. Each resource usage data corresponds to a resource indicator value. For example, the resource usage data is memory usage. Then, the memory usage rate of each service node in the at least two service nodes is obtained, the resource usage rate of each service node is processed, and the memory usage rate index values corresponding to the at least two service nodes are obtained.
Specifically, the server performs data weighting processing on each service node resource to obtain resource index values corresponding to all service nodes in the same server cluster. Wherein, the weight of each server node may be the same or different.
In this embodiment, the server may each obtain a difference value between the service node resource usage data and the reference usage data, and use a ratio of the difference value to the current number of service nodes as a resource index value corresponding to the service node. The difference value between the service node resource usage data and the reference usage data may be a value obtained by subtracting the service node resource usage data from the reference usage data, or a square of a subtraction value of the service node resource usage data and the reference usage data, or the like.
And step 206, when the resource index value meets the corresponding preset condition, adjusting the number of the service nodes according to a preset node adjustment rule.
Each resource index value has a corresponding preset condition. And each preset condition has a corresponding preset node adjustment rule. The preset node adjustment rules corresponding to the preset conditions may be the same. The preset node adjustment rule refers to a node adjustment rule already stored in the server. The node adjustment rule may include a preset capacity expansion rule and a preset capacity reduction rule. This preset condition may also be referred to as a first preset condition in the embodiments of the present application.
Specifically, when the resource index value meets a preset condition corresponding to the resource index value, the number of service nodes is adjusted according to a preset node adjustment rule corresponding to the preset condition.
In this embodiment, for example, the resource index value is related to the cpu utilization, and the predetermined condition of the cpu utilization is that the utilization is greater than 70% or less than 20%. The preset node adjustment rule with the utilization rate of more than 70% is adjusted to be 1.3 times of the current node number. The preset node adjustment rule with the utilization rate less than 20% is adjusted to be 0.7 times of the current node number. Then, when the resource index value is 80%, that is, the condition that the utilization rate is greater than 70% is satisfied, the number of service nodes is adjusted according to the rule that the number of service nodes is 1.3 times of the current number of nodes.
In this embodiment, when the number of service nodes obtained according to the node adjustment rule is a decimal, the decimal is rounded to obtain the number of target service nodes. The rounding of the decimal may be performed by rounding, or only the integer part of the decimal may be taken as the number of the target service nodes.
In this embodiment, when the node adjustment number obtained according to the node adjustment rule is smaller than 1, 1 is used as the adjustment number. For example, the node adjustment rule is a service node increased by 0.3 times, the current number of nodes is 2, and then 2 × 0.3 is 0.6. The server treats 1 as the number of increased service nodes.
In the resource adjustment method, the resource use data of each service node in at least two service nodes is obtained, the resource use data of each service node is processed, and the resource index values corresponding to the at least two service nodes are obtained, wherein the resource use data of a single node is not considered, but one resource index value corresponding to all the service nodes is obtained; when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjustment rule, the number of the service nodes can be quickly and automatically adjusted according to the requirement and the preset node adjustment rule, management personnel are not required to intervene, the logic is simple, and the resource adjustment efficiency can be improved; and the calculation requirements of the service nodes are met, the calculation efficiency is improved, the response speed is improved, or the service resources are recycled, so that the waste is avoided.
In one embodiment, the resource usage data includes at least one of central processor usage, memory usage, number of used thread pools, response time; each kind of resource use data corresponds to a resource index value;
when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjustment rule, and the method comprises the following steps: and when at least one resource index value meets the corresponding preset condition, adjusting the number of the service nodes according to a preset node adjustment rule.
The Central Processing Unit (CPU) is an operation and control core of a computer system, and is a final execution Unit for information Processing and program operation. The central processing unit utilization rate refers to the CPU resources occupied by the running program. Indicating the situation of the service node running the program at a certain point in time. The memory usage rate may include a usage rate of the JAVA heap memory and the non-heap memory. JAVA is an object-oriented programming language. The response time refers to a time when the service node responds to the request. The unit of the response time may be milliseconds, etc., but is not limited thereto. The utilization rate of the central processing unit and the utilization rate of the memory can be regarded as relative indexes and expressed by percentage or decimal, fraction and the like. The number of used thread pools and the response time are absolute indicators and are represented by fixed values.
Specifically, the server may obtain at least one of the cpu utilization, the memory utilization, the number of used thread pools, and the response time when monitoring the resource usage data of the service node. And the server processes the resource use data of each service node to obtain a resource index value corresponding to each resource use data. For example, the utilization rate of the central processing unit of each service node is processed to obtain an index value of the central processing unit corresponding to all the service nodes. And processing the memory utilization rate of each service node to obtain the memory utilization rate index values corresponding to all the service nodes.
And when at least one resource index value meets the preset condition corresponding to the resource index value, adjusting the number of the service nodes according to the node adjustment rule corresponding to the preset condition. For example, the index value of the central processing unit satisfies a preset condition higher than 70%, and the number of the service nodes is adjusted according to 1.3 times of the number of the nodes. The index value of the central processing unit meets 70% of preset conditions, the index value of the memory utilization rate meets 95% of the preset conditions, and the number of the service nodes is adjusted according to 1.3 times of the number of the nodes.
In this embodiment, when the node adjustment rules corresponding to the preset conditions are different, the number of service nodes is adjusted according to the rule with the larger value in the node adjustment rules. If the index value of the utilization rate of the central processing unit meets 70% of the preset condition, the corresponding rule is adjusted according to the multiple amount of 1.3; the index value of the memory utilization rate meets the preset condition of 95%, the corresponding rule is that the adjustment is carried out according to the multiple quantity of 1.2, and then the server adjusts the number of the service nodes according to the 1.3 multiple quantity with larger numerical value.
In the resource adjustment method, only one resource use data can be acquired, and multiple resource use data can be acquired, each resource use data only corresponds to one resource index value, when at least one resource index value meets the preset condition corresponding to the resource index value, that is, only the preset condition corresponding to one resource index value can be met, the number of service nodes is adjusted according to the preset node adjustment rule, the same index value corresponding to all the service nodes can be fully considered, instead of only one service node, the contingency is reduced, and the accuracy of resource adjustment is improved.
In one embodiment, when at least one resource index value satisfies a preset condition corresponding to the resource index value, the number of service nodes is adjusted according to a node adjustment rule corresponding to the number of resource index values satisfying the preset condition. Specifically, the number of resource values that satisfy the preset condition corresponds to a node adjustment rule. The node adjustment rules corresponding to different quantities are different. For example, the number is 1 to 1.1 times, the number is 2 to 1.2 times …, or the number is 1 to 0.9 times, the number is 2 to 0.8 times, etc., but is not limited thereto. For example, if two resource index values are greater than or equal to the corresponding upper limit values, the number of serving nodes is adjusted to 1.2 times the number of current nodes according to the adjustment rule corresponding to 2. The resource adjusting method can adjust the number of the nodes according to the number of the resource index values meeting the conditions, and improve the accuracy of resource adjustment.
In one embodiment, the obtaining resource index values corresponding to at least two service nodes by processing the resource usage data of each service node includes: and processing the resource use data of each service node according to the priority of the resource use data to obtain resource index values corresponding to at least two service nodes, wherein each resource use data corresponds to one resource index value.
When the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjustment rule, and the method comprises the following steps: and when the target resource index value meeting the corresponding preset condition is detected according to the priority, adjusting the number of the service nodes according to the preset node rule corresponding to the target resource index value.
Wherein the resource usage data has a priority. For example, resource usage data includes central processor usage, memory usage, number of thread pools used, and response time. Then the prioritization order is: the utilization rate of a central processing unit > the utilization rate of a memory > the number of used thread pools > the response time.
Specifically, the server processes the resource use data of each service node at the same time according to the priority of the resource use data to obtain resource index values corresponding to at least two service nodes. When a target resource index value meeting the corresponding preset condition is detected according to the priority, the number of the service nodes is adjusted according to a preset node adjustment rule corresponding to the target resource index value without processing the other resource use data at the moment.
For example, the server obtains the central processing unit usage, the memory usage, the number of used thread pools, and the response time at a certain time. The server firstly processes the utilization rate of the central processing unit at the moment to obtain the index values of the utilization rates of the central processing units corresponding to the at least two service nodes. When the CPU utilization rate index value meeting the corresponding preset condition is detected to exist at the moment, the memory utilization rate, the number of idle thread pools and the response time at the moment are not processed, and the number of the service nodes is adjusted according to the preset node adjustment rule corresponding to the CPU utilization rate index value.
In this embodiment, the server processes the resource usage data of each service node in the same period according to the priority of the resource usage data, and obtains resource index values corresponding to at least two service nodes. And when the target resource index value meeting the corresponding preset condition in the period is detected according to the priority, the data of other resource usage in the period are not processed, and the number of the service nodes is adjusted according to the preset node adjustment rule corresponding to the target resource index value.
According to the resource adjustment method, the resource use data of each service node is processed according to the priority of the resource use data, so that resource index values corresponding to at least two service nodes are obtained, wherein each resource use data corresponds to one resource index value, when a target resource index value meeting a corresponding preset condition is detected according to the priority, the number of the service nodes is adjusted according to a preset node rule corresponding to the target resource index value, the remaining other resource use data can not be processed, the processing time is saved, and the resource adjustment efficiency is improved.
In one embodiment, the resource adjusting method further includes: and acquiring resource use data corresponding to each period in the continuous preset period. When the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjustment rule, and the method comprises the following steps: and when the resource index value corresponding to each period meets the corresponding preset condition, adjusting the number of the service nodes according to a preset node adjustment rule.
Wherein a cycle refers to a time period. The preset number of cycles is a number of cycles previously configured at the server. For example, the period may be 1, 2, 3 …, etc., but is not limited thereto. The consecutive preset number of cycles refers to at least two time periods consecutively. For example, each period is 2 minutes, and the preset number is 3, the server obtains a resource index value corresponding to each period in 3 consecutive periods.
Specifically, the server integrates and processes the resource usage data of each service node at each time to obtain the resource usage data of each service node in the period. And the server performs weighting processing on the resource use data of each service node in the period to obtain resource index values corresponding to at least two service nodes in the period.
The preset node adjustment rule comprises a preset capacity expansion rule and a preset capacity reduction rule. The server obtains a resource index value corresponding to each period in the continuous preset number of periods. And when the resource index value corresponding to each period is greater than or equal to the corresponding index upper limit threshold value, increasing the number of the service nodes according to a preset capacity expansion rule. And when the resource index value corresponding to each period is smaller than the corresponding index lower limit threshold, reducing the number of service nodes according to a preset capacity reduction rule.
In the resource adjustment method, the resource index value corresponding to each period in the continuous preset number of periods is obtained, when the resource index value corresponding to each period meets the corresponding preset condition, namely the resource index values corresponding to several continuous periods meet the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjustment rule, and the resource index values corresponding to a plurality of periods are taken, so that the contingency can be reduced, and the accuracy of resource adjustment is improved.
In one embodiment, the resource adjusting method includes: and acquiring the resource use data of each service node in at least two service nodes in the same period. And processing the resource use data of each service node in the same period to obtain resource index values corresponding to at least two service nodes. And acquiring a resource index value corresponding to each period in the continuous preset number of periods. And performing weighting processing on the resource index value corresponding to each period to obtain the resource index values corresponding to at least two service nodes in the continuous preset number of periods. And when the resource index values corresponding to at least two service nodes in the continuous preset number period meet the corresponding preset conditions, adjusting the number of the service nodes. According to the resource adjusting method, the contingency can be reduced, and the accuracy of resource adjustment is improved.
In one embodiment, the resource adjusting method further includes: and acquiring resource use data corresponding to each period in the continuous preset period. And carrying out weighting processing on the resource use data corresponding to each period to obtain resource index values corresponding to at least two micro service nodes. And when the resource index value meets the corresponding preset condition, adjusting the number of the service nodes. In the resource adjusting method, the resource use data of a plurality of periods are acquired, weighted processing is carried out, the number of the service nodes is adjusted, the contingency can be reduced, and the accuracy of resource adjustment is improved.
In one embodiment, the preset node adjustment rule includes a preset capacity expansion rule and a preset capacity reduction rule.
When the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjustment rule, and the method comprises the following steps: when the resource index value is greater than or equal to the corresponding index upper limit threshold value, increasing the number of service nodes according to a preset capacity expansion rule; and when the resource index value is smaller than the corresponding index lower limit threshold, reducing the number of service nodes according to a preset capacity reduction rule.
The preset capacity expansion rule may include a service node addition rule. At least one of the number upper limit value of the service nodes and the called interface may be included. The preset capacity reduction rules may include service node reduction rules. At least one of the number lower limit value of the service nodes and the called interface may be included. The upper limit value of the number of the service nodes and the lower limit value of the number of the service nodes can be configured according to requirements. Thus avoiding unlimited capacity expansion or capacity reduction.
The index upper limit threshold is an upper limit value of the index value. The index lower limit threshold is a lower limit value of the index. The index upper limit threshold and the index lower limit threshold can be configured according to requirements. The preset conditions include being greater than or equal to the corresponding index upper threshold value and being less than the corresponding index lower threshold value. As in table 1 below:
the number of idle thread pools can be obtained by subtracting the number of used thread pools from the number of total thread pools. For example, if the total number of thread pools is 1000, the upper limit is greater than 990 according to the priority 3, and the lower limit is less than 100. The lower limit of the average response time may be set to 0, and the corresponding contraction and capacity rule is not operated. The capacity expansion rules corresponding to the upper limit values in table one may be the same. For example, the number of service nodes is adjusted according to the number of nodes which is 1.3 times of the current number of nodes. The capacity reduction rules corresponding to the lower limit values in table one may also be the same. For example, the number of serving nodes is adjusted to be 0.7 times the number of current nodes.
Specifically, when the server detects that the resource index value is greater than or equal to the corresponding index upper limit threshold value, the number of service nodes is increased according to the same preset capacity expansion rule; and when the server detects that the resource index value is smaller than the corresponding index lower limit threshold, reducing the number of service nodes according to the same preset capacity reduction rule.
In this embodiment, the server may create a new service node or delete a service node by calling a virtualization Interface, a docker or Kubernetes container Programming API (Application Programming Interface). Among them, Kubernetes, abbreviated as K8s, is an abbreviation in which 8 characters "ubernet" are replaced with 8. It is an application for managing containerization on multiple hosts in a cloud platform.
In this embodiment, for example, the capacity expansion rule may be: the number of target nodes is equal to the number of existing nodes 1.3, and the maximum number of service nodes does not exceed: XX with a minimum time interval of 10 minutes. The capacity reduction rule may be: the number of target nodes is 0.7 of the number of existing nodes, and the minimum number of service nodes is not lower than: YY, minimum time interval 10 minutes.
In this embodiment, when the resource index value satisfies the second preset condition, an alarm signal is sent. The resource index upper limit threshold of the second preset condition is smaller than the index upper limit threshold of the first preset condition, and the index lower limit threshold of the second preset condition is larger than the index lower limit threshold of the first preset condition. For example, in the CPU usage ratio of table 1, the index upper limit threshold is 70% and the index lower limit threshold is 20%. The index upper limit threshold value of the second preset condition may be 60%, the index lower limit threshold value may be 25%, and the like are not limited thereto.
In the resource adjustment method, when the resource index value is greater than or equal to the corresponding index upper limit threshold value, the number of the service nodes is increased according to the preset capacity expansion rule, the calculation requirement of the service nodes can be met under the condition of overhigh load, the calculation efficiency is improved, and the response speed is improved; when the resource index value is smaller than the corresponding index lower limit threshold, the number of the service nodes is reduced according to the preset capacity reduction rule, the service node resource can be recovered under the condition of too low load, the resource is saved, the waste is avoided, the number of the service nodes can be increased or reduced according to the resource index value obtained by the plurality of service nodes, the contingency is reduced, and the accuracy of resource adjustment is improved.
In one embodiment, the obtaining resource index values corresponding to at least two service nodes by processing the resource usage data of each service node includes: and carrying out weighted average processing on the resource utilization data of each service node to obtain resource index values corresponding to at least two service nodes.
Specifically, the server performs weighted average processing according to the resource usage data of each service node and the number of the current service nodes to obtain resource index values corresponding to all the service nodes. Wherein, the weight of each service node can be the same or different.
In the resource adjustment method, the resource use data of each service node are weighted and averaged to obtain the resource index values corresponding to at least two service nodes, one resource index value corresponding to a plurality of service nodes can be obtained, and the resource index value corresponding to the plurality of service nodes is used as a judgment condition, so that the number of the service nodes is adjusted, and the accuracy of resource adjustment is improved.
In one embodiment, the resource adjusting method further includes: and when the timing is started after the number of the service nodes is adjusted, the preset time length is reached, and the resource index value meets the preset condition, continuing to execute the step of adjusting the number of the service nodes according to the node adjustment rule.
The preset duration refers to a duration set in the server. The preset duration can be configured according to the requirement. For example, the preset time period may be 5 minutes, 10 minutes, etc., but is not limited thereto.
Specifically, after the server node is adjusted, the server needs a certain time to allocate resources. Then, starting timing after adjusting the number of the service nodes, and detecting whether the resource index value meets the corresponding preset condition when the timing reaches a preset duration. And when the resource index value meets the corresponding preset condition, the server adjusts the number of the service nodes according to the node adjustment rule.
In this embodiment, when the resource index value does not satisfy the preset condition, the server stops executing the step of adjusting the number of the service nodes according to the node adjustment rule.
In the resource adjustment method, when the number of the service nodes is adjusted and then timing is started, the preset time length is reached, and the resource index value meets the preset condition, that is, the number of the adjusted nodes is still too much or too little in the preset time length, the number of the service nodes needs to be continuously adjusted according to the node adjustment rule, continuous adjustment can be performed, and the accuracy of resource adjustment is improved.
In one embodiment, as shown in fig. 3, a flowchart of a resource adjustment method in another embodiment is shown. As shown, the server may obtain resource usage data from the infrastructure. For example, data is obtained from at least one of a virtual machine, a Docker, an IO port, and a network. The server can perform application monitoring on the micro service node, the service method, the database and the Redis storage, and acquire resource use data. And the server processes the resource use data of each service node to obtain resource index values corresponding to all the nodes. The server may statistically summarize resource indicator values. And when the resource index value meets a second preset condition, the server sends out an alarm signal and informs maintenance personnel. And when the resource index value meets the second preset condition and the corresponding preset condition, adjusting the number of the service nodes according to the node adjustment rule. The server can adjust the number of the service nodes through elastic expansion or secondary expansion. For example, capacity expansion or capacity reduction is performed on a virtual machine, capacity expansion or capacity reduction is performed on a Docker, and capacity expansion or capacity reduction is performed on a Redis cache. The resource adjusting method can quickly and automatically adjust the number of the service nodes according to the requirements and the preset node adjusting rule without the intervention of management personnel, and the resource adjusting efficiency is improved; and the calculation requirements of the service nodes are met, the calculation efficiency is improved, the response speed is improved, or the service resources are recycled, so that the waste is avoided.
In one embodiment, fig. 4 is a flowchart illustrating a resource adjustment method in another embodiment. As shown in fig. 4, a resource adjustment method includes:
And step 404, performing weighted average processing on the resource use data of each service node in the same period according to the priority of the resource use data to obtain resource index values corresponding to at least two service nodes in the same period. Wherein each resource usage data corresponds to a resource index value.
And step 410, when a target resource index value meeting the corresponding preset condition is detected according to the priority, and when the resource index value is smaller than the corresponding index lower limit threshold, reducing the number of service nodes according to a preset capacity reduction rule.
In step 412, when the timing is started after the number of the service nodes is adjusted, the preset time length is reached, and the resource index value meets the corresponding preset condition, the number of the service nodes continues to be increased or decreased.
And step 414, when the resource index value does not meet the preset condition, the server stops executing the step of adjusting the number of the service nodes according to the node adjustment rule.
In the resource adjustment method, resource use data of each service node in at least two service nodes in a period is obtained, the resource use data of each service node is processed according to priority, and resource index values corresponding to the at least two service nodes are obtained, wherein the resource use data of a single node is not considered, but one resource index value corresponding to all the service nodes is obtained; when a target resource index value meeting the corresponding preset condition is detected according to the priority, the number of the service nodes is adjusted according to the preset node rule corresponding to the target resource index value, the data processing on the rest other resources can be avoided, the processing time is saved, the number of the service nodes can be quickly and automatically adjusted according to the requirement and the preset node adjustment rule, the intervention of managers is not needed, and the resource adjustment efficiency is improved; and the calculation requirements of the service nodes are met, the calculation efficiency is improved, the response speed is improved, or the service resources are recycled, so that the waste is avoided.
It should be understood that although the steps in the flowcharts of fig. 2 and 4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2 and 4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performing the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 5, there is provided a resource adjusting apparatus, including: an obtaining module 502, a processing module 504, and an adjusting module 506, wherein:
an obtaining module 502 is configured to obtain resource usage data of each of at least two service nodes.
The processing module 504 is configured to process the resource usage data of each service node to obtain resource index values corresponding to at least two service nodes.
An adjusting module 506, configured to adjust the number of the service nodes according to a preset node adjusting rule when the resource index value satisfies the corresponding preset condition.
In the resource adjusting device, resource use data of each service node in at least two service nodes is acquired, the resource use data of each service node is processed, and resource index values corresponding to the at least two service nodes are obtained, wherein one resource index value corresponding to all the service nodes is obtained by not only considering the resource use data of a single node; when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjustment rule, the number of the service nodes can be quickly and automatically adjusted according to the requirement and the preset node adjustment rule, management personnel are not required to intervene, and the resource adjustment efficiency is improved; and the calculation requirements of the service nodes are met, the calculation efficiency is improved, the response speed is improved, or the service resources are recycled, so that the waste is avoided.
In one embodiment, the resource usage data includes at least one of central processor usage, memory usage, number of used thread pools, response time; each resource usage data corresponds to a resource indicator value.
The adjusting module 506 is configured to adjust the number of the service nodes according to a preset node adjusting rule when at least one resource index value satisfies a corresponding preset condition.
In the resource adjusting device, only one resource use data or multiple resource use data can be acquired, each resource use data only corresponds to one resource index value, when at least one resource index value meets the preset condition corresponding to the resource index value, that is, only the preset condition corresponding to one resource index value can be met, the number of service nodes is adjusted according to the preset node adjusting rule, the same index value corresponding to all the service nodes can be fully considered, instead of only one service node, the contingency is reduced, and the accuracy of resource adjustment is improved.
In an embodiment, the adjusting module 506 is configured to, when at least one resource index value satisfies a preset condition corresponding to the resource index value, adjust the number of service nodes according to a node adjusting rule corresponding to the number of resource index values satisfying the preset condition. The resource adjusting device can adjust the number of the nodes according to the number of the resource index values meeting the conditions, and the accuracy of resource adjustment is improved.
In an embodiment, the processing module 504 is configured to process the resource usage data of each service node according to the priority of the resource usage data, and obtain resource index values corresponding to at least two service nodes, where each resource usage data corresponds to one resource index value. The adjusting module 506 is configured to, when a target resource index value meeting a corresponding preset condition is detected according to the priority, adjust the number of service nodes according to a preset node rule corresponding to the target resource index value.
In the resource adjusting device, the resource use data of each service node is processed according to the priority of the resource use data to obtain resource index values corresponding to at least two service nodes, wherein each resource use data corresponds to one resource index value, and when a target resource index value meeting a corresponding preset condition is detected according to the priority, the number of the service nodes is adjusted according to a preset node rule corresponding to the target resource index value, so that the remaining other resource use data can not be processed, the processing time is saved, and the resource adjusting efficiency is improved.
In one embodiment, the obtaining module 502 is configured to obtain resource usage data corresponding to each period in consecutive preset periods. The adjusting module 506 is configured to adjust the number of the service nodes according to a preset node adjusting rule when the resource index value corresponding to each period meets the corresponding preset condition.
In the resource adjusting device, the resource index value corresponding to each period in the continuous preset number of periods is obtained, when the resource index value corresponding to each period meets the corresponding preset condition, namely the resource index values corresponding to several continuous periods meet the corresponding preset condition, the number of the service nodes is adjusted according to the preset node adjusting rule, and the resource index values corresponding to a plurality of periods are obtained, so that the contingency can be reduced, and the accuracy of resource adjustment is improved.
In one embodiment, the obtaining module 502 is configured to obtain resource usage data corresponding to each period in consecutive preset periods. The processing module 504 is configured to perform weighting processing on the resource usage data corresponding to each period to obtain resource index values corresponding to at least two microservice nodes. The adjusting module 506 is configured to adjust the number of the service nodes when the resource index value satisfies the corresponding preset condition. In the resource adjusting device, the resource use data of a plurality of periods is acquired, weighted processing is performed, the number of service nodes is adjusted, contingency can be reduced, and accuracy of resource adjustment is improved.
In one embodiment, the preset node adjustment rule includes a preset capacity expansion rule and a preset capacity reduction rule.
The adjusting module 506 is configured to increase the number of service nodes according to a preset capacity expansion rule when the resource index value is greater than or equal to the corresponding index upper limit threshold; and when the resource index value is smaller than the corresponding index lower limit threshold, reducing the number of service nodes according to a preset capacity reduction rule.
In the resource adjusting device, when the resource index value is greater than or equal to the corresponding index upper limit threshold, the number of the service nodes is increased according to the preset capacity expansion rule, so that the calculation requirement of the service nodes can be met under the condition of overhigh load, the calculation efficiency is improved, and the response speed is improved; when the resource index value is smaller than the corresponding index lower limit threshold, the number of the service nodes is reduced according to the preset capacity reduction rule, the service node resource can be recovered under the condition of too low load, the resource is saved, the waste is avoided, the number of the service nodes can be increased or reduced according to the resource index value obtained by the plurality of service nodes, the contingency is reduced, and the accuracy of resource adjustment is improved.
In an embodiment, the processing module 504 is configured to perform weighted average processing on the resource usage data of each service node to obtain resource index values corresponding to at least two service nodes.
In the resource adjusting device, the resource use data of each service node is weighted and averaged to obtain the resource index value corresponding to at least two service nodes, and one resource index value corresponding to a plurality of service nodes can be obtained.
In one embodiment, the resource adjusting apparatus further includes a timing module. The timing module is used for starting timing after the number of the service nodes is adjusted. The adjusting module 506 is configured to adjust the number of the service nodes according to the node adjusting rule when the preset duration is reached and the resource index value meets the preset condition.
In the resource adjusting device, when the number of the service nodes is adjusted and then timing is started, the preset time length is reached, and the resource index value meets the preset condition, that is, the number of the adjusted nodes is still too much or too little in the preset time length, the number of the service nodes needs to be continuously adjusted according to the node adjusting rule, continuous adjustment can be performed, and the accuracy of resource adjustment is improved.
For the specific limitation of the resource adjusting apparatus, reference may be made to the above limitation of the resource adjusting method, which is not described herein again. The modules in the resource adjusting device can be wholly or partially implemented by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing resource usage data and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a resource adjustment method.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the respective method embodiment as described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of resource adjustment, the method comprising:
acquiring resource use data of each service node in at least two service nodes;
processing the resource use data of each service node to obtain resource index values corresponding to the at least two service nodes;
and when the resource index value meets the corresponding preset condition, adjusting the number of the service nodes according to a preset node adjustment rule.
2. The method of claim 1, wherein the resource usage data comprises at least one of central processor usage, memory usage, number of used thread pools, response time; each kind of resource use data corresponds to a resource index value;
when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to a preset node adjustment rule, and the method comprises the following steps:
and when at least one resource index value meets the corresponding preset condition, adjusting the number of service nodes according to a preset node adjustment rule.
3. The method according to claim 1, wherein the processing the resource usage data of each service node to obtain the resource index values corresponding to the at least two service nodes comprises:
processing the resource use data of each service node according to the priority of the resource use data to obtain resource index values corresponding to the at least two service nodes, wherein each resource use data corresponds to one resource index value;
when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to a preset node adjustment rule, and the method comprises the following steps:
and when a target resource index value meeting the corresponding preset condition is detected according to the priority, adjusting the number of service nodes according to a preset node rule corresponding to the target resource index value.
4. The method of claim 1, further comprising:
acquiring a resource index value corresponding to each period in continuous preset number periods;
when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to a preset node adjustment rule, and the method comprises the following steps:
and when the resource index value corresponding to each period meets the corresponding preset condition, adjusting the number of service nodes according to a preset node adjustment rule.
5. The method according to claim 1, wherein the preset node adjustment rule includes a preset capacity expansion rule and a preset capacity reduction rule;
when the resource index value meets the corresponding preset condition, the number of the service nodes is adjusted according to a preset node adjustment rule, and the method comprises the following steps:
when the resource index value is greater than or equal to the corresponding index upper limit threshold value, increasing the number of service nodes according to the preset capacity expansion rule;
and when the resource index value is smaller than the corresponding index lower limit threshold, reducing the number of service nodes according to the preset capacity reduction rule.
6. The method according to any one of claims 1 to 4, wherein the processing the resource usage data of each service node to obtain the resource index values corresponding to the at least two service nodes comprises:
and carrying out weighted average processing on the resource utilization data of each service node to obtain resource index values corresponding to the at least two service nodes.
7. The method according to any one of claims 1 to 4, further comprising:
and when the timing is started after the number of the service nodes is adjusted, the preset time is reached, and the resource index value meets the corresponding preset condition, continuing to execute the step of adjusting the number of the service nodes according to the node adjustment rule.
8. An apparatus for resource adjustment, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring resource use data of each service node in at least two service nodes;
the processing module is used for processing the resource use data of each service node to obtain resource index values corresponding to the at least two service nodes;
and the adjusting module is used for adjusting the number of the service nodes according to a preset node adjusting rule when the resource index value meets the corresponding preset condition.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910824481.0A CN110677459A (en) | 2019-09-02 | 2019-09-02 | Resource adjusting method and device, computer equipment and computer storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910824481.0A CN110677459A (en) | 2019-09-02 | 2019-09-02 | Resource adjusting method and device, computer equipment and computer storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110677459A true CN110677459A (en) | 2020-01-10 |
Family
ID=69075899
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910824481.0A Pending CN110677459A (en) | 2019-09-02 | 2019-09-02 | Resource adjusting method and device, computer equipment and computer storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110677459A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111444015A (en) * | 2020-03-24 | 2020-07-24 | 北京奇艺世纪科技有限公司 | Server control method and device, computer equipment and storage medium |
| CN111782386A (en) * | 2020-03-17 | 2020-10-16 | 新浪网技术(中国)有限公司 | Historical service flow-based database scheduling method and system |
| CN112235383A (en) * | 2020-10-09 | 2021-01-15 | 腾讯科技（深圳）有限公司 | Container service cluster node scheduling method and device, server and storage medium |
| CN112380011A (en) * | 2020-11-16 | 2021-02-19 | 中国工商银行股份有限公司 | Dynamic adjustment method and device for service capacity |
| CN112398945A (en) * | 2020-11-16 | 2021-02-23 | 中国工商银行股份有限公司 | Service processing method and device based on backpressure |
| CN114548763A (en) * | 2022-02-22 | 2022-05-27 | 深圳市商汤科技有限公司 | Conference room management method, conference room management apparatus, electronic device, storage medium, and program product |
| CN114745275A (en) * | 2020-12-24 | 2022-07-12 | 顺丰科技有限公司 | Node updating method and device in cloud service environment and computer equipment |
| CN114745278A (en) * | 2022-04-11 | 2022-07-12 | 中和农信项目管理有限公司 | Method and device for expanding and contracting capacity of business system, electronic equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170111302A1 (en) * | 2015-10-16 | 2017-04-20 | Machine Zone, Inc. | Systems and methods for transferring message data |
| CN109343965A (en) * | 2018-10-31 | 2019-02-15 | 北京金山云网络技术有限公司 | Resource adjusting method, device, cloud platform and server |
| CN109669758A (en) * | 2018-09-11 | 2019-04-23 | 深圳平安财富宝投资咨询有限公司 | Concocting method, device, equipment and the storage medium of server resource |
-
2019
- 2019-09-02 CN CN201910824481.0A patent/CN110677459A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170111302A1 (en) * | 2015-10-16 | 2017-04-20 | Machine Zone, Inc. | Systems and methods for transferring message data |
| CN109669758A (en) * | 2018-09-11 | 2019-04-23 | 深圳平安财富宝投资咨询有限公司 | Concocting method, device, equipment and the storage medium of server resource |
| CN109343965A (en) * | 2018-10-31 | 2019-02-15 | 北京金山云网络技术有限公司 | Resource adjusting method, device, cloud platform and server |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111782386A (en) * | 2020-03-17 | 2020-10-16 | 新浪网技术(中国)有限公司 | Historical service flow-based database scheduling method and system |
| CN111444015A (en) * | 2020-03-24 | 2020-07-24 | 北京奇艺世纪科技有限公司 | Server control method and device, computer equipment and storage medium |
| CN112235383A (en) * | 2020-10-09 | 2021-01-15 | 腾讯科技（深圳）有限公司 | Container service cluster node scheduling method and device, server and storage medium |
| CN112235383B (en) * | 2020-10-09 | 2024-03-22 | 腾讯科技（深圳）有限公司 | Container service cluster node scheduling method and device, server and storage medium |
| CN112380011A (en) * | 2020-11-16 | 2021-02-19 | 中国工商银行股份有限公司 | Dynamic adjustment method and device for service capacity |
| CN112398945A (en) * | 2020-11-16 | 2021-02-23 | 中国工商银行股份有限公司 | Service processing method and device based on backpressure |
| CN112398945B (en) * | 2020-11-16 | 2022-12-20 | 中国工商银行股份有限公司 | Service processing method and device based on backpressure |
| CN112380011B (en) * | 2020-11-16 | 2024-02-27 | 中国工商银行股份有限公司 | Dynamic adjustment method and device for service capacity |
| CN114745275A (en) * | 2020-12-24 | 2022-07-12 | 顺丰科技有限公司 | Node updating method and device in cloud service environment and computer equipment |
| CN114548763A (en) * | 2022-02-22 | 2022-05-27 | 深圳市商汤科技有限公司 | Conference room management method, conference room management apparatus, electronic device, storage medium, and program product |
| CN114745278A (en) * | 2022-04-11 | 2022-07-12 | 中和农信项目管理有限公司 | Method and device for expanding and contracting capacity of business system, electronic equipment and storage medium |
| CN114745278B (en) * | 2022-04-11 | 2024-05-24 | 中和农信农业集团有限公司 | Method and device for expanding and shrinking capacity of service system, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110677459A (en) | Resource adjusting method and device, computer equipment and computer storage medium | |
| CN108881495B (en) | Resource allocation method, device, computer equipment and storage medium | |
| CN111818159B (en) | Management method, device, equipment and storage medium of data processing node | |
| CN110597858A (en) | Task data processing method and device, computer equipment and storage medium | |
| CN109412852B (en) | Alarm method, alarm device, computer equipment and storage medium | |
| CN113051075B (en) | Kubernetes intelligent capacity expansion method and device | |
| CN107426274B (en) | Method and system for service application and monitoring, analyzing and scheduling based on time sequence | |
| CN110545258B (en) | Streaming media server resource allocation method and device and server | |
| CN110716808B (en) | Service processing method, device, computer equipment and storage medium | |
| CN107656807B (en) | Automatic elastic expansion method and device for virtual resources | |
| CN112689007B (en) | Resource allocation method, device, computer equipment and storage medium | |
| CN110933178B (en) | Method for adjusting node configuration in cluster system and server | |
| CN107911399B (en) | Elastic expansion method and system based on load prediction | |
| CN111881004A (en) | Hardware resource control method, device, equipment and storage medium | |
| CN111209110A (en) | Task scheduling management method, system and storage medium for realizing load balance | |
| CN112165436A (en) | Flow control method, device and system | |
| US20180309686A1 (en) | Reducing rate limits of rate limiters | |
| CN111381963A (en) | Load balancing method and device, computer readable storage medium and computer equipment | |
| CN113672345A (en) | IO prediction-based cloud virtualization engine distributed resource scheduling method | |
| CN110995617A (en) | MQTT-based data transmission method, device, computer equipment and storage medium | |
| CN110599080A (en) | Service data distribution processing method and device, computer equipment and storage medium | |
| CN114064326A (en) | Method and device for processing micro-service request, computer equipment and storage medium | |
| CN111796933A (en) | Resource scheduling method, device, storage medium and electronic equipment | |
| CN113918341A (en) | Equipment scheduling method, device, equipment and storage medium | |
| CN112416888B (en) | Dynamic load balancing method and system for distributed file system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200110 |
|
| RJ01 | Rejection of invention patent application after publication |