CN116599968A - Expansion and contraction method and device, electronic equipment and readable storage medium - Google Patents

Expansion and contraction method and device, electronic equipment and readable storage medium Download PDF

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Publication number
CN116599968A
CN116599968A CN202310876794.7A CN202310876794A CN116599968A CN 116599968 A CN116599968 A CN 116599968A CN 202310876794 A CN202310876794 A CN 202310876794A CN 116599968 A CN116599968 A CN 116599968A
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China
Prior art keywords
target
copy number
server cluster
information
time
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CN202310876794.7A
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CN116599968B (en
Inventor
李剑锋
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China Mobile Communications Group Co Ltd
China Mobile Suzhou Software Technology Co Ltd
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China Mobile Communications Group Co Ltd
China Mobile Suzhou Software Technology Co Ltd
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    • 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
    • H04L67/1031—Controlling of the operation of servers by a load balancer, e.g. adding or removing servers that serve requests
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/5044—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering hardware capabilities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G06F9/5072—Grid computing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
    • H04L43/0817—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2209/00—Indexing scheme relating to G06F9/00
    • G06F2209/50—Indexing scheme relating to G06F9/50
    • G06F2209/505—Clust
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2209/00—Indexing scheme relating to G06F9/00
    • G06F2209/50—Indexing scheme relating to G06F9/50
    • G06F2209/508—Monitor
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Environmental & Geological Engineering (AREA)
  • Mathematical Physics (AREA)
  • Computer And Data Communications (AREA)

Abstract

The disclosure provides a capacity expansion and contraction method, a device, electronic equipment and a readable storage medium, and relates to the technical field of communication, wherein the method comprises the following steps: monitoring annotation information of a target application, wherein the annotation information comprises configuration information for controlling a copy expansion and contraction strategy; and expanding and shrinking the copy of the server cluster based on the configuration information, wherein the target application is deployed in the server cluster. According to the method and the system, the annotation information of the target application is monitored, the annotation information comprises the configuration information for controlling the copy expansion and contraction strategy, and the copy of the server cluster for deploying the target application is expanded and contracted based on the configuration information, so that the copy number of the server cluster is adapted to the running state of the target application, the HPA strategy is not required to be created manually, and the efficiency of creating the strategy for controlling the copy number of the server cluster is improved.

Description

Expansion and contraction method and device, electronic equipment and readable storage medium
Technical Field
The disclosure relates to the technical field of communication, and in particular relates to a capacity expansion and contraction method, a capacity expansion and contraction device, electronic equipment and a readable storage medium.
Background
In the related art, a server cluster is generally adopted to provide cloud service for an internet enterprise, so that physical resources are saved, and cost is reduced. In particular, kubernetes clusters are typically deployed at the cloud to provide corresponding services. In the related art, to improve the capacity of concurrent access traffic corresponding to an application program, a horizontal automatic capacity expansion and contraction (Horizontal Pod Autoscaler, HPA) policy is created manually, and the number of copies is controlled by monitoring the traffic load of the application program. In the related art, more human resources are required to be consumed to create the HPA policy, so that the efficiency is low, and the requirement that a large number of application programs need to establish the HPA policy cannot be met.
It can be seen that the prior art has a problem of low policy efficiency in creating the number of copies of the control server cluster.
Disclosure of Invention
The embodiment of the disclosure provides a capacity expansion and contraction method, a capacity expansion and contraction device, electronic equipment and a readable storage medium, and aims to solve the problem that in the prior art, the efficiency of creating a strategy for controlling the number of container cluster copies is low.
To solve the above problems, the present disclosure is implemented as follows:
in a first aspect, an embodiment of the present disclosure provides a method for expanding and contracting a volume, including:
monitoring annotation information of a target application, wherein the annotation information comprises configuration information for controlling a copy expansion and contraction strategy;
and expanding and shrinking the copy of the server cluster based on the configuration information, wherein the target application is deployed in the server cluster.
In one embodiment, the configuration information includes at least one of time task information and horizontal auto-scaling HPA information, the time task information includes a time task policy for controlling the copy of the server cluster to scale according to the time information, and the HPA information includes a policy for controlling the copy of the server cluster to scale according to the resource occupation information of the target application.
In one embodiment, the configuration information includes time task information, and the expanding and contracting the copy of the server cluster based on the configuration information includes:
creating a work task based on the time task information, wherein the work task comprises a plurality of continuous time periods and a first target copy number corresponding to each time period in the plurality of continuous time periods;
acquiring the number of real-time copies at the current moment in a target time period, wherein the target time period is any one of the plurality of continuous time periods;
and calling an application programming (Application Programming Interface, API) interface to update the copy number of the server cluster to the first target copy number corresponding to the target time period under the condition that the real-time copy number is not matched with the first target copy number corresponding to the target time period.
In one embodiment, after the calling application programming API interface updates the number of copies of the server cluster to the first target number of copies corresponding to the target time period, the method further includes:
monitoring target events, wherein the target events are used for requesting events for updating the number of copies of the server cluster into the second target number of copies based on a preset strategy, and the preset strategy is other expansion and contraction strategies outside the time task strategy;
When the target event is monitored and the second target copy number is larger than the first target copy number, calling the API interface to update the copy number of the server cluster to the second target copy number corresponding to the target time period;
and if the target event is monitored and the second target copy number is smaller than or equal to the first target copy number, keeping the copy number of the server cluster to be the first target copy number.
In one embodiment, the configuration information includes HPA information, where the HPA information includes a plurality of consecutive subintervals in a target interval, and a third target copy number corresponding to each subinterval, where the target interval is a value interval of a resource occupancy rate of the server cluster;
the expanding and shrinking the copy of the server cluster based on the configuration information comprises the following steps:
creating an HPA object based on the HPA information calling API interface, wherein the HPA object comprises a plurality of continuous subintervals in the target interval and a third target copy number corresponding to each subinterval;
acquiring the real-time resource occupancy rate and the real-time copy number of the resource occupancy of the target application;
Determining a corresponding target subinterval of the real-time resource occupancy rate in the HPA object, wherein the target subinterval is a subinterval comprising the real-time resource occupancy rate in a plurality of continuous subintervals in the target interval;
and under the condition that the real-time copy number is not matched with the third target copy number corresponding to the target subinterval, updating the copy number of the server cluster to the third target copy number corresponding to the target subinterval.
In one embodiment, the method further comprises:
and updating an interval or a third target copy number in the HPA information in the HPA object based on the updating information when the updating information of the annotation information is monitored, wherein the updating information is used for updating the interval and/or the third target copy number in the HPA information.
In one embodiment, the method further comprises:
and deleting the HPA object from the server cluster in the condition that the HPA information of the annotation information is deleted.
In one embodiment, the obtaining the real-time resource occupancy and the real-time copy number of the resource occupancy of the target application includes:
And acquiring the real-time resource occupancy rate and the real-time copy number of the target application from the index server meta-server and/or the Prometaheus.
In a second aspect, an embodiment of the present disclosure further provides a device for expanding and contracting a volume, including:
the monitoring module is used for monitoring annotation information of the target application, wherein the annotation information comprises configuration information for controlling copy expansion and contraction strategies;
and the processing module is used for expanding and shrinking the copy of the server cluster based on the configuration information, wherein the target application is deployed in the server cluster.
In one embodiment, the configuration information includes at least one of time task information and horizontal auto-scaling HPA information, the time task information includes a time task policy for controlling the copy of the server cluster to scale according to the time information, and the HPA information includes a policy for controlling the copy of the server cluster to scale according to the resource occupation information of the target application.
In one embodiment, the configuration information includes time task information, and the processing module includes:
a first processing unit, configured to create a work task based on the time task information, where the work task includes a plurality of consecutive time periods and a first target copy number corresponding to each time period in the plurality of consecutive time periods;
The second processing unit is used for acquiring the real-time copy number of the current moment in a target time period, wherein the target time period is any one of the plurality of continuous time periods;
and the third processing unit is used for calling an application programming API interface to update the copy number of the server cluster to the first target copy number corresponding to the target time period under the condition that the real-time copy number is not matched with the first target copy number corresponding to the target time period.
In one embodiment, after the third processing unit, the apparatus comprises:
the first monitoring unit is used for monitoring target events, wherein the target events are used for requesting events for updating the number of copies of the server cluster into the second target number of copies based on a preset strategy, and the preset strategy is other expansion and contraction strategies outside the time task strategy;
the fourth processing unit is used for calling the API interface to update the copy number of the server cluster to the second target copy number corresponding to the target time period under the condition that the target event is monitored and the second target copy number is larger than the first target copy number;
And the fifth processing unit is used for keeping the number of copies of the server cluster to be the first target number of copies when the target event is monitored and the second target number of copies is smaller than or equal to the first target number of copies.
In one embodiment, the configuration information includes HPA information, where the HPA information includes a plurality of consecutive subintervals in a target interval, and a third target copy number corresponding to each subinterval, where the target interval is a value interval of a resource occupancy rate of the server cluster;
the processing module comprises:
a sixth processing unit, configured to call an API interface to create an HPA object based on the HPA information, where the HPA object includes a plurality of consecutive subintervals in the target interval, and a third target copy number corresponding to each subinterval;
the acquisition unit is used for acquiring the real-time resource occupancy rate and the real-time copy number of the resource occupancy of the target application;
a seventh processing unit, configured to determine a target subinterval corresponding to the real-time resource occupancy rate in the HPA object, where the target subinterval is a subinterval including the real-time resource occupancy rate in a plurality of continuous subintervals in the target interval;
And the eighth processing unit is used for updating the copy number of the server cluster to the third target copy number corresponding to the target subinterval under the condition that the real-time copy number is not matched with the third target copy number corresponding to the target subinterval.
In one embodiment, the apparatus further comprises:
and the updating module is used for updating the subarea or the third target copy number in the HPA information in the HPA object based on the updating information under the condition that the updating information of the annotation information is monitored, wherein the updating information is used for updating the subarea and/or the third target copy number in the HPA information.
In one embodiment, the apparatus further comprises:
and the deleting module is used for deleting the HPA object from the server cluster under the condition that the HPA information of the annotation information is deleted.
In one embodiment, the acquisition unit includes:
and the acquisition subunit is used for acquiring the real-time resource occupancy rate and the real-time copy number of the target application from the metric server and/or the Prometaheus.
In a third aspect, an embodiment of the disclosure further provides an electronic device, including a processor, a memory, and a computer program stored on the memory and executable on the processor, where the computer program is executed by the processor to implement the steps in the method for expanding and contracting as described in the first aspect.
In a fourth aspect, an embodiment of the present disclosure further provides a readable storage medium, where a computer program is stored, where the computer program is executed by a processor to implement the steps of the method for expanding and contracting a volume according to the first aspect.
In the embodiment of the disclosure, by monitoring the annotation information of the target application, the annotation information comprises the configuration information for controlling the copy expansion and contraction strategy, and expanding and contracting the copies of the server cluster for deploying the target application based on the configuration information, so that the copy number of the server cluster is adapted to the running state of the target application, and the HPA strategy is not required to be created manually, thereby improving the efficiency of creating the strategy for controlling the copy number of the server cluster.
Drawings
For a clearer description of the technical solutions of the embodiments of the present disclosure, the drawings that are needed in the description of the embodiments of the present disclosure will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.
Fig. 1 is a flowchart of a method for expanding and contracting capacity according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of copy scaling of a server cluster based on configuration information provided by an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of copy scaling of a server cluster based on temporal task information provided by an embodiment of the present disclosure;
fig. 4 is a schematic diagram of copy scaling of a server cluster based on HPA information provided by an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a capacity expansion device according to an embodiment of the disclosure;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
The following description of the technical solutions in the embodiments of the present disclosure will be made clearly and completely with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are some embodiments of the present disclosure, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without inventive effort, based on the embodiments in this disclosure are intended to be within the scope of this disclosure.
Referring to fig. 1, fig. 1 is a flowchart of a method for expanding and contracting capacity according to an embodiment of the disclosure, as shown in fig. 1, including the following steps:
and 101, monitoring annotation information of a target application, wherein the annotation information comprises configuration information for controlling a copy expansion and contraction strategy.
The annotation information (advertisement) is information describing the target application, and is not typically monitored or processed in the server cluster. In the method, configuration information for controlling copy expansion and contraction strategies is added in annotation information of a target application, and then the annotation information of the target application is monitored, so that the configuration information in the annotation information is obtained.
Wherein, since annotation information is not monitored or processed in the server cluster, the present disclosure adds an auto-scaler (auto-scaler-controller) in the server cluster, and monitors the annotation information of the target application through the auto-scaler.
It should be understood that the scaling of the application in the Kubernetes cluster is implemented by modifying the number of copies controlled by a controller (e.g. a duplicate or statefulset) that manages the multi-copy application, and after adding the auto-scaling controller, the auto-scaling controller listens to resource events of all controllers that manage the multi-copy application in the Kubernetes cluster through an asynchronous message processing mechanism (e.g. list-watch mechanism) in the Kubernetes cluster, thereby implementing the monitoring of annotation information of the target application.
And 102, expanding and shrinking the copy of the server cluster based on the configuration information, wherein the target application is deployed in the server cluster.
The target application is deployed in the server cluster, and the copy number of the server cluster is adapted to the running state of the target application by expanding and shrinking the copy number of the server cluster based on the configuration information, so that an HPA policy is not required to be created artificially, and the efficiency of creating the policy for controlling the copy number of the server cluster is improved.
For example, the configuration information is a strategy of expanding and shrinking according to the hardware resource occupation state of the target application, and the automatic expanding and shrinking controller expands and contracts the copies of the server cluster according to the hardware resource occupation state of the target application after monitoring the annotation information of the target application to obtain the configuration information.
In the embodiment of the disclosure, by monitoring the annotation information of the target application, the annotation information comprises the configuration information for controlling the copy expansion and contraction strategy, and expanding and contracting the copies of the server cluster for deploying the target application based on the configuration information, so that the copy number of the server cluster is adapted to the running state of the target application, and the HPA strategy is not required to be created manually, thereby improving the efficiency of creating the strategy for controlling the copy number of the server cluster.
In one embodiment, the configuration information includes at least one of time task information and horizontal auto-scaling HPA information, the time task information includes a time task policy for controlling the copy of the server cluster to scale according to the time information, and the HPA information includes a policy for controlling the copy of the server cluster to scale according to the resource occupation information of the target application.
The time task strategy included in the time task information can enable the server cluster to control the number of copies of the server cluster according to preset time variation. It should be understood that the concurrent access flow of the target application shows obvious time change, the concurrent access flow of the target application is higher in working time, the concurrent access flow of the target application is lower in rest time at night, and the number of copies of the server cluster at different times is controlled through time task information, so that the condition of changing the number of copies of the target application is adapted to the condition of changing the concurrent access flow of the target application along with the time.
The policy included in the HPA information may be that the server cluster controls the number of copies of the server cluster according to the occupancy state of the real-time hardware resource of the target application. It should be understood that, in the case of higher concurrent access traffic, the target application occupies more hardware resources; under the condition of low concurrent access flow, occupied hardware resources are fewer, the number of copies of the target application requirement can be predicted through the occupied state of the real-time hardware resources of the target application, and the number of copies of the server cluster is controlled to be the number of copies of the target application requirement, so that the change condition of the number of copies of the server cluster is adapted to the hardware occupation condition of the target application.
In the case that the automatic capacity expansion and contraction controller monitors that the configuration information includes time task information, as shown in fig. 2, the number of copies of the server cluster is controlled through a time period character string (e.g., cron expression); under the condition that the automatic capacity expansion and contraction controller monitors that the configuration information comprises HPA information, the number of copies of the server cluster is controlled through the HPA controller, and the specific process is described in the following embodiments.
In the embodiment of the disclosure, the configuration information includes at least one of time task information and horizontal automatic capacity expansion and contraction HPA information, where the time task information includes a time task policy for controlling copies of the server cluster to expand and contract according to the time task information, and the HPA information includes a policy for controlling copies of the server cluster to expand and contract according to resource occupation information of the target application, based on the time task information, the adaptation of the number of copies of the server cluster to the number of concurrent access traffic of the target application to the number of copies of the target application may be controlled, and based on the HPA information, the adaptation of the number of copies of the server cluster to the hardware occupation of the target application may be controlled.
In one embodiment, the configuration information includes time task information, and the expanding and contracting the copy of the server cluster based on the configuration information includes:
Creating a work task based on the time task information, wherein the work task comprises a plurality of continuous time periods and a first target copy number corresponding to each time period in the plurality of continuous time periods;
acquiring the number of real-time copies at the current moment in a target time period, wherein the target time period is any one of the plurality of continuous time periods;
and calling an application programming (Application Programming Interface, API) interface to update the copy number of the server cluster to the first target copy number corresponding to the target time period under the condition that the real-time copy number is not matched with the first target copy number corresponding to the target time period.
It should be appreciated that the time task information includes a time task policy that controls copies of the server cluster to scale according to the time information, a work task is created based on the time task information, and a plurality of consecutive time periods in the work task and a first target number of copies corresponding to each of the plurality of consecutive time periods are determined based on the time task information. And determining the first target copy number corresponding to the current moment through a plurality of time periods and the first target copy number corresponding to each time period, and further controlling the copy number of the server cluster to be updated to the corresponding first target copy number, so that the change condition of the copy number of the server cluster is adapted to the change condition of the concurrent access flow of the target application along with the time.
The time task information is a user-defined time period task (cronjob).
Illustratively, as shown in fig. 3, in the case where the automatic expansion and contraction controller listens for annotation information from a resource event (replyment or statefulset), the time task information in the annotation information, which conforms to the format specification, is passed to a job processing component (Jobhandler). After receiving the time task information, the work processing component creates a corresponding work task, stores the corresponding work task in a local cache, and simultaneously adds an identifier corresponding to the work task into a work queue (work queue). Under the condition that a Job engine (Job-engine) acquires an identifier corresponding to a Job task from a Job queue, the Job engine acquires the Job task from a local cache, and a preset cron component executes the Job task. In executing a work task, a cron time expression and a task (job) object need to be specified, and the job object includes a task execution method (e.g., execution function) that implements the task. When the time defined by the cron component arrives, the method is automatically operated to perform task processing work, and the control of the copy number of the server cluster is realized.
When the task runs, the method of the expansion and contraction capacity library is called by calling the API interface of the server cluster, and the first target copy number set by the task is used as the copy number corresponding to the new target application and is updated into the application. The server cluster can ensure that the target application expands to the first target copy number, so that the timed expansion of the application is realized. And simultaneously, a timing task is started, delay is carried out according to a preset window (predictionWindow) value set by the task, and when the application is operated to the time corresponding to the predictionWindow value, the API interface of the server cluster is also called to adjust the number of the working copies of the application, and the state is adjusted to be in idle time.
Specifically, annotation information of the target application is described by defining a depth, the content is as follows:
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx
annotations:
autoscaling.io/type: "cron"
scaleup.autoscaling.io/cron: "0 8/17 * * *"
scaleup.autoscaling.io/targetReplicas: "50"
scaleup.autoscaling.io/predictionWindow: "3600"
scaledown.autoscaling.io/cron: "0 22 * * *"
scaledown.autoscaling.io/targetReplicas: "2"
spec:
selector:
matchLabels:
app: nginx
replicas: 2
template:
metadata:
spec:
containers:
# omitted here
When the file of the target application is submitted to the server cluster and created, the content of the annotation information (time task information at this time) can be monitored by the automatic expansion and contraction controller as follows:
a time period type work task can meet incoming flow peaks at 8 points and 17 points every day, the peak flow can last for one hour, and the time of the work task at the 8 points and the 17 points is configured to perform copy expansion of target applications to 50, and the duration is 1 hour. The application is in a low traffic trough after 22 points per day, and is configured to perform copy capacity reduction of the target application after 22 points, wherein the number of copies after capacity reduction is 2.
After monitoring that the annotation information is time task information, the time task information is sent to a work processing component, the work processing component creates a work task through a built-in data interface (e.g. CroneJob HPA), the work task is kept in a local cache, and an identification corresponding to the work task is added to a work queue. The work engine will continually obtain an identification of the work task from the work queue and based on the identification, obtain the work task. An engine for processing the work task is built in the work engine, and a cron library which is open at present can be adopted. In the present system, taking the go-cron framework as an example, we need to add a cron time expression to the go-cron engine, such as "0 8/17" for each job task in the system.
The method comprises the steps that a job task is executed at a time designated by a cron time expression in a go-cron framework, and an API interface of a server cluster is called in the process of executing the job task, so that the regulation of the copy number of the server cluster is realized. Executing the work task through the API interface of the server cluster includes the following:
(1) Acquiring a target application to which the work task belongs through an API (application program interface) of a server cluster;
(2) Acquiring the number of copies at the current moment through an API (application program interface) of a server cluster;
(3) Updating the copy number of the server cluster to be the first target copy number through an API (application program interface) of the server cluster;
(4) And after the preset predictionWindow time is passed, the number of copies of the server cluster is adjusted to be a default number.
The work processing component, the work queue and the work engine are components built in the server cluster, and the automatic expansion and contraction controller is also a component built in the server cluster.
In the embodiment of the disclosure, a work task is created based on time task information, the real-time copy number at the current moment is obtained in a target time period, and when the real-time copy number is not matched with the first target copy number corresponding to the target time period, an application programming API interface is called to update the copy number of a server cluster to the first target copy number corresponding to the target time period, so that the condition of the change of the copy number of the server cluster and the condition of the concurrent access flow of a target application along with the time change are controlled through time task information.
In one embodiment, after the calling application programming API interface updates the number of copies of the server cluster to the first target number of copies corresponding to the target time period, the method further includes:
Monitoring target events, wherein the target events are used for requesting events for updating the number of copies of the server cluster into the second target number of copies based on a preset strategy, and the preset strategy is other expansion and contraction strategies outside the time task strategy;
when the target event is monitored and the second target copy number is larger than the first target copy number, calling the API interface to update the copy number of the server cluster to the second target copy number corresponding to the target time period;
and if the target event is monitored and the second target copy number is smaller than or equal to the first target copy number, keeping the copy number of the server cluster to be the first target copy number.
It should be appreciated that there may be other scaling policies in the server cluster beyond the temporal task policy, and that other scaling policies may scale the number of copies of the server cluster as well. If the time task policy and other capacity expansion policies conflict at the same time (for example, one needs capacity expansion and the other needs capacity expansion, or one capacity expansion copy number is smaller and the other capacity expansion copy number is larger), the server cluster cannot accurately judge which policy needs to be executed in this case, so that the server cluster needs to be designed for, and can perform capacity expansion and contraction correctly.
The target event is an event that the number of copies of the server cluster needs to be adjusted again by other expansion and contraction strategies in the target time period. After the target event is monitored, the second target copy number and the first target copy number in the target event need to be compared to determine whether to adjust the copy number of the server cluster. The copy number control of the server cluster is performed under the condition that the second target copy number needs to be larger than the first target copy number no matter whether other capacity expansion strategies are capacity expansion or capacity reduction. If the number of the second target copies is smaller than or equal to the number of the first target copies, if the number of the copies of the server cluster is adjusted, the adjusted number of the copies of the server cluster cannot meet the requirement of the time period, and the possibility that the target application concurrent access flow of the time period cannot be met exists, so that the number of the copies of the server cluster is kept to be the first target number of copies under the condition.
Specifically, in the process of executing the work task by the go-cron, an API interface of the server cluster is called, and the regulation of the copy number of the server cluster is realized. Executing the work task through the API interface of the server cluster further includes:
And checking whether other expansion and contraction strategies exist in the application, and if so, adjusting the lowest value of the number of copies of the server cluster to be the first target number of copies, so as to prevent the number of copies of the server cluster from being lower than the first target number of copies in the predictive window time period.
In the embodiment of the disclosure, by monitoring a target event, when the target event is monitored and the number of second target copies is greater than that of first target copies, an API (application program interface) is called to update the number of copies of the server cluster to the number of second target copies corresponding to the target time period; and under the condition that the number of the second target copies is smaller than or equal to the number of the first target copies, keeping the number of the copies of the server cluster as the number of the first target copies, controlling the number of the copies of the server cluster through two control strategies simultaneously, and further improving the flexibility of controlling the number of the copies of the server cluster.
In one embodiment, the configuration information includes HPA information, where the HPA information includes a plurality of consecutive subintervals in a target interval, and a third target copy number corresponding to each subinterval, where the target interval is a value interval of a resource occupancy rate of the server cluster;
The expanding and shrinking the copy of the server cluster based on the configuration information comprises the following steps:
creating an HPA object based on the HPA information calling API interface, wherein the HPA object comprises a plurality of continuous subintervals in the target interval and a third target copy number corresponding to each subinterval;
acquiring the real-time resource occupancy rate and the real-time copy number of the resource occupancy of the target application;
determining a corresponding target subinterval of the real-time resource occupancy rate in the HPA object, wherein the target subinterval is a subinterval comprising the real-time resource occupancy rate in a plurality of continuous subintervals in the target interval;
and under the condition that the real-time copy number is not matched with the third target copy number corresponding to the target subinterval, updating the copy number of the server cluster to the third target copy number corresponding to the target subinterval.
The HPA information comprises a strategy for controlling the copy of the server cluster to expand and contract according to the resource occupation information of the target application, and an HPA object is created based on the HPA information, so that the server cluster can control the number of the copies through the HPA object, and the adaptation of the copy number change condition of the server cluster and the hardware occupation condition of the target application is realized.
Illustratively, as shown in fig. 4, in the case that the automatic expansion and contraction controller monitors the annotation information, the HPA information conforming to the format specification in the annotation information is transferred to an HPA processing component (HPA handler), and the HPA processing component calls an API interface to create an HPA object; and an HPA Controller (HPA Controller) acquires the real-time resource occupancy rate and the real-time copy number of the resource occupancy of the target application, and expands and contracts the copy number of the server cluster according to the HPA object, the real-time resource occupancy rate and the real-time copy number.
The real-time resource occupancy rate of the resource occupancy of the target application may be the occupancy rate of hardware resources such as the memory occupancy rate, the occupancy rate of a central processing unit (Central Processing Unit, CPU), and the like, and the hardware resources are hardware resources of the server cluster.
Specifically, annotation information of the target application is described by defining a depth, the content is as follows:
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx
annotations:
autoscaling.io/type: "hpa"
autoscaling.io/minReplicas: "2"
autoscaling.io/maxReplicas: "30"
cpu.autoscaling.io/targetAverageUtilization: "70"
mem.autoscaling.io/targetAverageUtilization: "70"
spec:
selector:
matchLabels:
app: nginx
replicas: 2
template:
metadata:
spec:
containers:
# omitted here
When the file of the target application is submitted to the server cluster and created, the content of the annotation information (HPA information at this time) can be monitored by the auto-scaling controller as follows:
and an HPA type expansion and contraction rule is used for monitoring the expansion and contraction capacity of the resource occupancy rate of the CPU and the memory of the application to the number of copies of the server cluster. When the resource occupancy rate of the CPU or the memory corresponding to the target application exceeds 70%, carrying out capacity expansion on the number of copies of the server cluster, wherein the maximum number is 30; and when the resource occupancy rate of the CPU and the memory corresponding to the target application is reduced to be within 70%, the capacity reduction of the number of copies of the server cluster is carried out, and the minimum number is 2.
After monitoring that the annotation information is HPA information, an HPA object is created based on the HPA information, for example, in the golang language, as follows:
hpa :=&v2beta2.HorizontalPodAutoscaler{
# omitted here
},
Spec: v2beta2.HorizontalPodAutoscalerSpec{
ScaleTargetRef: v2beta2.CrossVersionObjectReference{
APIVersion: apps/v1,
Kind: Deployment,
Name: nginx,
},
MinReplicas: 30,
MaxReplicas: 2,
Metric：
Threshold value of #cpu 70
Memory threshold 70 #
},
}
And the HPA controller controls the number of copies of the server cluster based on the HPA object, so that the number of copies of the server cluster is expanded when the resource occupancy rate of the CPU or the memory exceeds 70%, or the number of copies of the server cluster is contracted when the resource occupancy rate of the CPU or the memory is lower than 70%.
The resource occupancy rates corresponding to different hardware can be set to be different, and the number of copies of the server cluster is set to be the maximum number of copies corresponding to the plurality of hardware under the condition that the expansion and contraction strategies corresponding to the plurality of hardware are contradictory.
It should be understood that a plurality of subintervals may be set, where each subinterval corresponds to a different number of copies, for example, the number of copies is 2 when the resource occupancy rate is less than 30%, the resource occupancy rate is greater than 70% and is 30, and the number of copies changes linearly between 30% and 70%.
In the embodiment of the disclosure, the configuration information includes HPA information, an API interface is called based on the HPA information to create an HPA object, a real-time resource occupancy rate and a real-time copy number of a resource occupancy of a target application are obtained, a target subinterval corresponding to the real-time resource occupancy rate in the HPA object is determined, and the copy number of the server cluster is updated to a third target copy number corresponding to the target subinterval under the condition that the real-time copy number is not matched with the third target copy number corresponding to the target subinterval, so that the adaptation of the copy number change condition of the server cluster to the hardware occupancy condition of the target application is realized.
In one embodiment, the method further comprises:
and updating an interval or a third target copy number in the HPA information in the HPA object based on the updating information when the updating information of the annotation information is monitored, wherein the updating information is used for updating the interval and/or the third target copy number in the HPA information.
It should be appreciated that the target application, after being put into use, may change its peak or valley of concurrent access traffic, where the sub-area or the third target copy number in the original HPA information no longer adapts to the new situation, and the HPA information in the HPA object needs to be updated.
In the embodiment of the disclosure, by adding update information including subintervals and/or the third target copy number in the annotation information, and updating the subintervals or the third target copy number in the HPA information in the HPA object based on the update information, the subintervals and the third target copy number in the HPA object are the latest data, so that the copy number change of the server cluster is controlled by the latest HPA object.
Further, in the case that the HPA information of the annotation information is deleted, the HPA object is deleted from the server cluster.
In the related art, the control of the number of copies of the server cluster requires manual creation of an HPA object, and when the server cluster is no longer deploying the target application, the HPA object still exists in the server cluster and needs to be manually deleted, otherwise, the HPA object becomes dirty data in the server cluster, and the operation of the server cluster is affected. In the present disclosure, when the HPA information of the annotation information is deleted, the HPA object is deleted from the server cluster, and manual deletion is not required, so that the maintenance efficiency of the server can be further improved.
In one embodiment, the obtaining the real-time resource occupancy and the real-time copy number of the resource occupancy of the target application includes:
and acquiring the real-time resource occupancy rate and the real-time copy number of the target application from the index server meta-server and/or the Prometaheus.
In the related art, acquiring the real-time resource occupancy rate depends on monitoring of the server cluster, i.e., judgment is performed by periodically acquiring monitoring data. The method is limited by the monitoring capability of the server cluster, the period interval is longer, the interval is usually more than 1 minute, the overall load of the target application is suddenly increased in a short time, the server cluster cannot timely acquire the increase of the resource occupancy rate, the copy number of the server cluster cannot be timely expanded, and the situation that part of terminals fail to access the target application easily occurs.
In the embodiment of the disclosure, the real-time resource occupancy rate and the real-time copy number of the target application are obtained from the metric servers meta-server and/or Prometheus, so that the real-time resource occupancy rate and the real-time copy number of the target application can be obtained more quickly relative to the monitoring of the server cluster, and the capacity expansion and contraction speed of the server cluster is improved.
Referring to fig. 5, fig. 5 is a structural diagram of a capacity expansion device according to an embodiment of the disclosure, and as shown in fig. 5, a capacity expansion device 500 includes:
a monitoring module 501, configured to monitor annotation information of a target application, where the annotation information includes configuration information for controlling a copy expansion and contraction policy;
and the processing module 502 is configured to scale up and scale down a copy of the server cluster based on the configuration information, where the target application is deployed on the server cluster.
In one embodiment, the configuration information includes at least one of time task information and horizontal auto-scaling HPA information, the time task information includes a time task policy for controlling the copy of the server cluster to scale according to the time information, and the HPA information includes a policy for controlling the copy of the server cluster to scale according to the resource occupation information of the target application.
In one embodiment, the configuration information includes time task information, and the processing module 502 includes:
a first processing unit, configured to create a work task based on the time task information, where the work task includes a plurality of consecutive time periods and a first target copy number corresponding to each time period in the plurality of consecutive time periods;
the second processing unit is used for acquiring the real-time copy number of the current moment in a target time period, wherein the target time period is any one of the plurality of continuous time periods;
and the third processing unit is used for calling an application programming API interface to update the copy number of the server cluster to the first target copy number corresponding to the target time period under the condition that the real-time copy number is not matched with the first target copy number corresponding to the target time period.
In one embodiment, after the third processing unit, the apparatus comprises:
the first monitoring unit is used for monitoring target events, wherein the target events are used for requesting events for updating the number of copies of the server cluster into the second target number of copies based on a preset strategy, and the preset strategy is other expansion and contraction strategies outside the time task strategy;
The fourth processing unit is used for calling the API interface to update the copy number of the server cluster to the second target copy number corresponding to the target time period under the condition that the target event is monitored and the second target copy number is larger than the first target copy number;
and the fifth processing unit is used for keeping the number of copies of the server cluster to be the first target number of copies when the target event is monitored and the second target number of copies is smaller than or equal to the first target number of copies.
In one embodiment, the configuration information includes HPA information, where the HPA information includes a plurality of consecutive subintervals in a target interval, and a third target copy number corresponding to each subinterval, where the target interval is a value interval of a resource occupancy rate of the server cluster;
the processing module 502 includes:
a sixth processing unit, configured to call an API interface to create an HPA object based on the HPA information, where the HPA object includes a plurality of consecutive subintervals in the target interval, and a third target copy number corresponding to each subinterval;
The acquisition unit is used for acquiring the real-time resource occupancy rate and the real-time copy number of the resource occupancy of the target application;
a seventh processing unit, configured to determine a target subinterval corresponding to the real-time resource occupancy rate in the HPA object, where the target subinterval is a subinterval including the real-time resource occupancy rate in a plurality of continuous subintervals in the target interval;
and the eighth processing unit is used for updating the copy number of the server cluster to the third target copy number corresponding to the target subinterval under the condition that the real-time copy number is not matched with the third target copy number corresponding to the target subinterval.
In one embodiment, the apparatus further comprises:
and the updating module is used for updating the subarea or the third target copy number in the HPA information in the HPA object based on the updating information under the condition that the updating information of the annotation information is monitored, wherein the updating information is used for updating the subarea and/or the third target copy number in the HPA information.
In one embodiment, the apparatus further comprises:
and the deleting module is used for deleting the HPA object from the server cluster under the condition that the HPA information of the annotation information is deleted.
In one embodiment, the acquisition unit includes:
and the acquisition subunit is used for acquiring the real-time resource occupancy rate and the real-time copy number of the target application from the metric server and/or the Prometaheus.
The capacity expansion and contraction device 500 provided in the embodiments of the present disclosure can implement each process of each embodiment of the capacity expansion and contraction method, technical features are in one-to-one correspondence, and can achieve the same technical effects, and for avoiding repetition, a detailed description is omitted here.
It should be noted that, the expansion and contraction device in the embodiments of the present disclosure may be a device, or may be a component, an integrated circuit, or a chip in an electronic device.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure, and as shown in fig. 6, the electronic device includes: may include a processor 601, a memory 602, and a program 6021 stored on the memory 602 and executable on the processor 601.
The program 6021, when executed by the processor 601, may implement any steps and achieve the same advantageous effects in the method embodiment corresponding to fig. 1, and will not be described herein. Those of ordinary skill in the art will appreciate that all or a portion of the steps of implementing the methods of the embodiments described above may be implemented by hardware associated with program instructions, where the program may be stored on a readable medium.
The embodiment of the present disclosure further provides a readable storage medium, where a computer program is stored, where the computer program when executed by a processor may implement any step in the method embodiment corresponding to fig. 1, and may achieve the same technical effect, so that repetition is avoided, and no further description is provided herein.
The computer-readable storage media of the embodiments of the present disclosure may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or terminal. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
While the foregoing is directed to the preferred implementation of the disclosed embodiments, it should be noted that numerous modifications and adaptations to those skilled in the art may be made without departing from the principles of the disclosure, and such modifications and adaptations are intended to be within the scope of the disclosure.

Claims (10)

1. A method of expanding and contracting, comprising:
monitoring annotation information of a target application, wherein the annotation information comprises configuration information for controlling a copy expansion and contraction strategy;
and expanding and shrinking the copy of the server cluster based on the configuration information, wherein the target application is deployed in the server cluster.
2. The method of claim 1, wherein the configuration information comprises at least one of time-task information and horizontal auto-scaling HPA information, the time-task information comprising a time-task policy that controls scaling of the copies of the server cluster according to time information, the HPA information comprising a policy that controls scaling of the copies of the server cluster according to resource occupancy information of the target application.
3. The method of claim 2, wherein the configuration information includes time task information, and wherein scaling the copy of the server cluster based on the configuration information comprises:
Creating a work task based on the time task information, wherein the work task comprises a plurality of continuous time periods and a first target copy number corresponding to each time period in the plurality of continuous time periods;
acquiring the number of real-time copies at the current moment in a target time period, wherein the target time period is any one of the plurality of continuous time periods;
and under the condition that the real-time copy number is not matched with the first target copy number corresponding to the target time period, calling an application programming API interface to update the copy number of the server cluster to the first target copy number corresponding to the target time period.
4. The method of claim 3, wherein after the calling application programming API interface updates the number of copies of the server cluster to the first target number of copies corresponding to the target time period, the method further comprises:
monitoring target events, wherein the target events are used for requesting events for updating the number of copies of the server cluster into the second target number of copies based on a preset strategy, and the preset strategy is other expansion and contraction strategies outside the time task strategy;
When the target event is monitored and the second target copy number is larger than the first target copy number, calling the API interface to update the copy number of the server cluster to the second target copy number corresponding to the target time period;
and if the target event is monitored and the second target copy number is smaller than or equal to the first target copy number, keeping the copy number of the server cluster to be the first target copy number.
5. The method according to claim 2, wherein the configuration information includes HPA information, the HPA information includes a plurality of consecutive subintervals in a target interval, and a third target copy number corresponding to each subinterval, the target interval is a value interval of a resource occupancy of the server cluster;
the expanding and shrinking the copy of the server cluster based on the configuration information comprises the following steps:
creating an HPA object based on the HPA information calling API interface, wherein the HPA object comprises a plurality of continuous subintervals in the target interval and a third target copy number corresponding to each subinterval;
Acquiring the real-time resource occupancy rate and the real-time copy number of the resource occupancy of the target application;
determining a corresponding target subinterval of the real-time resource occupancy rate in the HPA object, wherein the target subinterval is a subinterval comprising the real-time resource occupancy rate in a plurality of continuous subintervals in the target interval;
and under the condition that the real-time copy number is not matched with the third target copy number corresponding to the target subinterval, updating the copy number of the server cluster to the third target copy number corresponding to the target subinterval.
6. The method of claim 5, wherein the method further comprises:
and updating an interval or a third target copy number in the HPA information in the HPA object based on the updating information when the updating information of the annotation information is monitored, wherein the updating information is used for updating the interval and/or the third target copy number in the HPA information.
7. The method of claim 5, wherein the obtaining the real-time resource occupancy and the real-time copy number of the resource occupancy of the target application comprises:
And acquiring the real-time resource occupancy rate and the real-time copy number of the target application from the index server meta-server and/or the Prometaheus.
8. A capacity expansion device, comprising:
the monitoring module is used for monitoring annotation information of the target application, wherein the annotation information comprises configuration information for controlling copy expansion and contraction strategies;
and the processing module is used for expanding and shrinking the copy of the server cluster based on the configuration information, wherein the target application is deployed in the server cluster.
9. An electronic device, comprising: a processor, a memory and a program stored on the memory and executable on the processor, which when executed by the processor performs the steps of the method according to any one of claims 1 to 7.
10. A readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, implements the steps of the method according to any of claims 1 to 7.
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