CN114928606A - Scheduling method and system of server resources - Google Patents
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- H04L67/10—Protocols in which an application is distributed across nodes in the network
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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
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- H04L67/1008—Server selection for load balancing based on parameters of servers, e.g. available memory or workload
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Abstract
The invention relates to the technical field of server operation and maintenance, in particular to a scheduling method of server resources, which specifically comprises the following steps: step S1: acquiring idle hardware resources of at least one server which executes the application instance and required hardware resources of the application instance; step S2: judging whether the idle hardware resources are larger than the required hardware resources or not; if yes, return to step S1; if not, go to step S3; step S3: an extension method is used to select a server from the server resource pool and allocate the application instance to the server, and then the process returns to step S1. The invention has the beneficial effects that: hardware resources required for maintaining normal work of the application instance in a future time period are effectively judged by acquiring the required resources of the application instance, and further, the server is effectively scheduled in a short time. The number of servers for operating a certain application example can be increased or decreased in time according to the change condition of the burst flow, and the overall utilization rate of the server system is improved.
Description
Technical Field
The invention relates to the technical field of server operation and maintenance, in particular to a scheduling method of server resources.
Background
With the gradual expansion of internet business scale and the need of actual business operation, internet enterprises often need to provide normal services for users under the conditions of high concurrency and burst traffic. Concurrency, a concept in the field of operating systems, refers to the phenomenon of alternating execution of multitask streams over a period of time. When an internet enterprise provides internet services for a large number of users in a short time based on business needs, a large number of access requests are usually borne by gateway equipment and a back-end server, so that the number of the access requests exceeds the upper bearing limit of the server under the common condition, and the normal operation of the internet business is influenced. Generally, with service expansion or specific service nodes, internet enterprises increase the number of servers adaptively to increase the upper limit of their load, thereby avoiding the impact of high concurrent or burst traffic on internet services. However, deploying too many servers at idle or in general may cause an increase in operation and maintenance costs. Therefore, the server scheduling system is set to realize dynamic regulation and control of server resources when the service runs normally, and the method has great economic value.
In the prior art, the scheduling of the server usually depends on manual operation, and the capacity expansion time is long, so that the response of the whole scheduling process is not timely enough, and the burst traffic cannot be effectively handled.
Disclosure of Invention
In view of the above problems in the prior art, a method for scheduling server resources is provided.
The specific technical scheme is as follows:
a scheduling method of server resources is applicable to a server resource pool, a plurality of servers are arranged in the server resource pool, the servers are used for executing at least one application instance, and the application instance runs on at least one server;
the scheduling method includes an allocation method for allocating the server to the running application instance, and the allocation method specifically includes:
step S1: acquiring idle hardware resources of at least one server which executes the application instance and the required hardware resources of the application instance;
step S2: judging whether the idle hardware resources are larger than the required hardware resources;
if yes, returning to the step S1;
if not, go to step S3;
step S3: selecting a server from the server resource pool by using an extension method, allocating the application instance to the server, and returning to the step S1.
Preferably, the capacity expansion method includes:
step A1: acquiring idle hardware resources of a plurality of servers in a current server resource pool;
step A2: selecting at least two servers which can be used for executing the application instance according to the idle hardware resources of the servers and the required hardware resources of the application instance;
step A3: a server scoring method is used to select the highest scoring server as the server for executing the instance.
Preferably, the step a2 further includes:
and when the number of the servers which can be used for executing the application examples is less than two, sending out early warning information to operation and maintenance personnel.
Preferably, the hardware resources include: the processor idle rate, the memory idle rate, the hard disk idle rate and the network bandwidth idle rate;
said step a3 includes:
step A31: respectively calculating and generating a processor resource score, a memory resource score, a hard disk resource score and a network resource score according to the processor idle rate, the memory idle rate, the hard disk idle rate and the network bandwidth idle rate;
step A32: generating a server score of the server according to the processor resource score, the memory resource score, the hard disk resource score and the network resource score;
step A33: and sequencing the servers from high to low in sequence according to the server scores so as to output the server with the highest score.
Preferably, the scheduling method further comprises stopping the application instance from the server by using a first capacity reduction method or a second capacity reduction method
The first capacity reduction method includes:
acquiring the hardware resources occupied by a plurality of running application instances and the running time of the plurality of running application instances;
generating an instance hardware occupation score according to the application instance occupied hardware resources;
sorting the application examples according to the running time to generate an example sorting result;
generating an instance time score according to the instance sorting result;
generating an instance score according to the instance time score and the instance hardware occupancy score;
stopping the application instance on the server according to the instance score;
the second capacity reduction method comprises the following steps: and stopping the application instance from the server according to a preset instance capacity reduction rule.
A system for scheduling server resources, configured to implement the scheduling method, includes:
the acquisition module is connected with the server resource pool, acquires idle resources in the server resource pool and occupied resources of the application examples, and acquires the access amount of the application examples;
the analysis module is connected with the acquisition module and judges whether capacity expansion or capacity reduction is needed or not according to the occupied resources and the access quantity of the application example;
the scheduling module is connected with the analysis module and used for allocating the server to the application instance or stopping the application instance from the server according to the output result of the analysis module;
and the feedback module is connected with the acquisition module, the analysis module and the scheduling module and is used for displaying the idle resources, the application instances, the occupied resources and the scheduling result of the scheduling module.
Preferably, the acquisition module comprises:
the traffic monitoring submodule is connected with an external routing device and acquires the access quantity of the application example from the routing device;
the hardware statistics sub-module is connected with the server resource pool and acquires hardware resources of the server from the server resource pool;
and the instance counting submodule is connected with the server resource pool and collects occupied resources of the application instance from the server resource pool.
Preferably, the analysis module comprises:
the rule configuration sub-module is internally preset with at least one early warning rule;
and the matching sub-module is connected with the acquisition module and the rule configuration sub-module, judges whether the access amount, the occupied resources and the idle resources meet the early warning rule or not, and generates a matching result.
Preferably, the scheduling module includes:
the capacity expansion submodule is connected with the server resource pool and the analysis module and distributes the application examples to the server according to a preset capacity expansion rule;
the capacity reduction sub-module is connected with the server resource pool and the analysis module and stops the application example from the server according to a preset capacity reduction rule;
the first notification sub-module is connected with the capacity expansion sub-module and the capacity reduction sub-module and generates the scheduling result according to the output result of the capacity expansion sub-module or the output result of the capacity reduction sub-module.
Preferably, the feedback module comprises:
the display sub-module is connected with an external display screen, and the display screen is used for displaying the idle resources, the application examples, the occupied resources and the scheduling results of the scheduling module;
and the notification submodule is connected with the scheduling module and external terminal equipment and is used for sending notification information to the terminal equipment according to the scheduling result of the scheduling module.
The technical scheme has the following advantages or beneficial effects: hardware resources required for maintaining normal work of the application instance in a future time period are effectively judged by acquiring the required resources of the application instance, and further, the server is effectively scheduled in a short time. The number of servers for operating a certain application instance can be increased or decreased in time according to the change condition of the burst flow, and the overall utilization rate of the server system is improved.
Drawings
Embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings. The drawings are, however, to be regarded as illustrative and explanatory only and are not restrictive of the scope of the invention.
FIG. 1 is a schematic diagram of an allocation method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating a capacity expansion method according to an embodiment of the invention;
FIG. 3 is a schematic diagram illustrating the substep of step A3 according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a first capacity reduction method according to an embodiment of the present invention;
FIG. 5 is a schematic block diagram of a system of an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive efforts based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
The invention comprises the following steps:
a scheduling method of server resources is applicable to a server resource pool, a plurality of servers are arranged in the server resource pool, the servers are used for executing at least one application instance, and the application instance runs on at least one server;
the scheduling method includes an allocation method for allocating a server to the running application instance, as shown in fig. 1, the allocation method specifically includes:
step S1: acquiring idle hardware resources of at least one server executing the application instance and required hardware resources of the application instance;
step S2: judging whether the idle hardware resources are larger than the required hardware resources or not;
if yes, return to step S1;
if not, go to step S3;
step S3: an extension method is used to select a server from the server resource pool and allocate the application instance to the server, and then the step S1 is returned.
Specifically, the present application provides a scheduling method for solving the problem in the prior art that the response speed is low and the burst traffic cannot be responded well when a manual capacity expansion method is used for an application instance. The method is specifically implemented by deploying the application instance as a software embodiment in a server or other computer equipment, acquiring an access request for accessing the corresponding application instance through a connection gateway, a routing or load balancing device and the like, further presuming the required resources of the application instance in a certain period of time in the future, and expanding or shrinking the capacity of the server for executing the application instance according to a prediction result. An application instance typically represents a process, service, or other computer program in a server operating system that is used by an internet enterprise to provide internet services to users during implementation. The occupied resources of the application instance refer to hardware resources required for normal operation of the application instance, and include processor idle rate, memory idle rate, hard disk idle rate, network bandwidth idle rate and the like. The server resource pool may be represented as a server cluster provided by a cloud service provider or a private cloud constructed by a user. The hardware of each server in the server resource pool is not necessarily the same, and the specific hardware configuration of each server and the current idle hardware resource are stored in the server resource pool in a physical machine list form, so that the scheduling method is used as a basis for judgment and scheduling.
In a preferred embodiment, as shown in fig. 2, the capacity expansion method includes:
step A1: acquiring idle hardware resources of a plurality of servers in a current server resource pool;
step A2: selecting at least two servers which can be used for executing the application instance according to the idle hardware resources of the servers and the required hardware resources of the application instance;
step A3: a server scoring method is employed to select the highest scoring server as the server for executing the instance.
In a preferred embodiment, step a2 further includes:
when the number of the servers which can be used for executing the application instances is less than two, an early warning message is sent to operation and maintenance personnel for reminding the operation and maintenance personnel to perform hardware expansion or part reduction on the server resource pool.
Specifically, the capacity expansion method includes a preselection step. When the application instance needs to be expanded, the physical machine list of the server resource pool is called to obtain the current idle hardware resource conditions of all servers in the server hardware resource pool, and the servers which can be used for executing the application instance are screened out. The screening condition is an and relationship, that is, the currently idle hardware resources of the server must satisfy the processor idle rate, the memory idle rate, the hard disk idle rate and the network bandwidth idle rate for executing the application instance at the same time. And when the number of the selected servers is less than two, the server load in the current server resource pool is close to the upper limit, a new server should be added, or a part of the application instance should be reduced to release the hardware resources of the server.
In a preferred embodiment, the hardware resources include: the processor idle rate, the memory idle rate, the hard disk idle rate and the network bandwidth idle rate;
as shown in fig. 3, step a3 includes:
step A31: respectively calculating and generating a processor resource score, a memory resource score, a hard disk resource score and a network resource score according to the processor idle rate, the memory idle rate, the hard disk idle rate and the network bandwidth idle rate;
step A32: generating a server score of the server according to the processor resource score, the memory resource score, the hard disk resource score and the network resource score;
step A33: and sequencing the servers from high to low according to the server scores to output the server with the highest score.
Specifically, in one embodiment, the method for calculating the server score includes:
when the idleness of the processor is more than 50%, the resource score of the processor is 10; when the processor idleness is less than 50% and more than 20%, the processor resource score is 5; when the processor idleness is less than 20%, the processor resource score is 0.
When the memory vacancy rate is more than 50%, the memory resource score is 10; when the memory vacancy rate is less than 50% and more than 20%, the memory resource score is 5; when the memory vacancy rate is less than 20%, the memory resource score is 0.
When the hard disk vacancy rate is more than 50%, the hard disk resource score is 10; when the hard disk vacancy rate is less than 50% and more than 20%, the hard disk resource score is 5; when the hard disk vacancy rate is less than 20%, the hard disk resource score is 0.
When the network bandwidth vacancy rate is more than 50%, the network resource score is 10; when the network bandwidth vacancy rate is less than 50% and more than 20%, the network resource score is 5; when the network bandwidth vacancy rate is less than 20%, the network resource score is 0.
In a preferred embodiment, the scheduling method further comprises stopping the application instance from the server by using a first capacity reduction method or a second capacity reduction method;
as shown in fig. 4, the first capacity reduction method includes:
acquiring hardware resources occupied by a plurality of running application instances and running time of the plurality of application instances;
generating an instance hardware occupation score according to the application instance occupying hardware resources;
sorting the application examples according to the running time to generate an example sorting result;
generating an instance time score according to the instance sorting result;
generating an instance score according to the instance time score and the instance hardware occupancy score;
stopping the application instance on the server according to the instance score;
the second capacity reduction method comprises the following steps: and stopping the application instance from the server according to a preset instance capacity reduction rule.
Specifically, in the actual implementation process, the sequence between the generation processes of the instance time score and the instance hardware occupancy score is not limited, and may be executed sequentially, in the opposite direction, or simultaneously.
As an alternative embodiment, the example time score is calculated as follows:
selecting an application example with the longest service running time, and recording the score of the example time as 1; the earliest generated application instance is selected and recorded with an instance time score of 20.
As an alternative embodiment, the example hardware occupancy score is calculated as follows;
when the memory occupancy rate of the application example exceeds 85%, recording the example score of the application example as 100; when the memory occupancy rate of the application instance is more than 70% and less than 85%, the score of the instance hardware occupancy rate is increased by 10 points; when the memory occupancy rate of the application example is larger than 50% and smaller than 70%, the score of the example hardware occupancy rate is increased by 5 points; and when the memory occupancy rate of the application instance is less than 50%, increasing the hardware occupancy rate of the application instance by 1 point.
When the processor occupancy rate of the application example exceeds 85%, recording the example score as 100; when the processor occupancy rate of the application example is more than 50% and less than 85%, the example hardware occupancy rate is increased by 10 points; when the processor occupancy rate of the application instance is less than 50%, the hardware occupancy rate of the instance is increased by 1 point.
When the occupancy rate of the hard disk of the application example exceeds 85%, recording the example score of 100; when the hard disk occupancy rate of the application example is more than 70% and less than 85%, increasing the example hardware occupancy rate by 10 points; when the hard disk occupancy rate of the application example is more than 50% and less than 70%, the hardware occupancy rate of the application example is increased by 5 points; and when the hard disk occupancy rate of the application example is less than 50%, increasing the hardware occupancy rate of the application example by 1 point.
When the network bandwidth occupancy rate of the application example exceeds 85%, recording the example score of 100; when the network bandwidth occupancy rate of the application example is more than 50% and less than 85%, the hardware occupancy rate of the application example is increased by 10 points; and when the network bandwidth occupancy rate of the application instance is less than 50%, increasing the hardware occupancy rate of the application instance by 1 point.
A scheduling system of server resources, configured to implement the scheduling method described above, as shown in fig. 5, includes:
the acquisition module 1 is connected with the server resource pool A, acquires idle resources in the server resource pool A and occupied resources of the application example, and acquires the access amount of the application example;
the analysis module 2 is connected with the acquisition module 1, and judges whether capacity expansion or capacity reduction is needed according to the occupied resources and the access amount of the application example;
the scheduling module 3 is connected with the analysis module 2, and allocates the server to the application example according to the output result of the analysis module 2, or stops the application example from the server;
and the feedback module 4 and the feedback module 3 are connected with the acquisition module 1, the analysis module 2 and the scheduling module 3 and are used for displaying idle resources, application examples, occupied resources and scheduling results of the scheduling module.
In a preferred embodiment, the acquisition module 1 comprises:
the traffic monitoring submodule 11 is connected with an external routing device B, and the visit volume of the application instance is obtained from the routing device B;
the hardware statistics submodule 12 is connected with the server resource pool A, and the hardware statistics submodule acquires hardware resources of the server from the server resource pool A;
and the instance counting submodule 13 is connected with the server resource pool A, and the instance counting submodule 13 collects the occupied resources of the application instance from the server resource pool A.
In a preferred embodiment, the analysis module 2 comprises:
the rule configuration submodule 21 is used for presetting at least one early warning rule in the rule configuration submodule 21;
and the matching submodule 22 is connected with the acquisition module 1 and the rule configuration submodule 21, judges whether the access amount, the occupied resources and the idle resources meet the early warning rules or not, and generates a matching result.
In a preferred embodiment, the scheduling module 3 comprises:
the expansion submodule 31 is connected with the server resource pool A and the analysis module 2, and the expansion submodule 31 distributes the application examples to the servers according to a preset expansion rule;
the capacity reduction submodule 32 is connected with the server resource pool A and the analysis module 2, and stops an application example from the server according to a preset capacity reduction rule;
the first notification submodule 33, the first notification submodule 33 connects the capacity expansion submodule 31 and the capacity reduction submodule 32, and the first notification submodule 33 generates a scheduling result according to an output result of the capacity expansion submodule 31 or an output result of the capacity reduction submodule 32.
In a preferred embodiment, the feedback module 4 comprises:
the display sub-module 41, the display sub-module 41 is connected to an external display screen, and the display screen is used for displaying idle resources, application instances, occupied resources and scheduling results of the scheduling module;
and a second notifying submodule 42, where the second notifying submodule 42 is connected to the scheduling module 3 and the external terminal device C, and is configured to send notification information to the terminal device according to the scheduling result of the scheduling module.
The invention has the beneficial effects that: hardware resources required for maintaining normal work of the application instance in a future time period are effectively judged by acquiring the required resources of the application instance, and further, the server is effectively scheduled in a short time. The number of servers for operating a certain application instance can be increased or decreased in time according to the change condition of the burst flow, and the overall utilization rate of the server system is improved.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (10)
1. The scheduling method of the server resource is characterized in that the scheduling method is suitable for a server resource pool, a plurality of servers are arranged in the server resource pool, the servers are used for executing at least one application instance, and the application instance runs on at least one server;
the scheduling method includes an allocation method for allocating the server to the running application instance, and the allocation method specifically includes:
step S1: acquiring idle hardware resources of at least one server which executes the application instance and the required hardware resources of the application instance;
step S2: judging whether the idle hardware resources are larger than the required hardware resources;
if yes, returning to the step S1;
if not, go to step S3;
step S3: selecting a server from the server resource pool by using an extension method, allocating the application instance to the server, and returning to the step S1.
2. The scheduling method according to claim 1, wherein the capacity expansion method comprises:
step A1: acquiring idle hardware resources of a plurality of servers in a current server resource pool;
step A2: selecting at least two servers which can be used for executing the application instance according to the idle hardware resources of the servers and the required hardware resources of the application instance;
step A3: a server scoring method is employed to select the highest scoring server as the server for executing the instance.
3. The scheduling method according to claim 2, wherein said step a2 further comprises:
and when the number of the servers which can be used for executing the application examples is less than two, sending out early warning information to operation and maintenance personnel.
4. The scheduling method of claim 2, wherein the hardware resources comprise: the processor idle rate, the memory idle rate, the hard disk idle rate and the network bandwidth idle rate;
said step a3 includes:
step A31: respectively calculating and generating a processor resource score, a memory resource score, a hard disk resource score and a network resource score according to the processor idle rate, the memory idle rate, the hard disk idle rate and the network bandwidth idle rate;
step A32: generating a server score of the server according to the processor resource score, the memory resource score, the hard disk resource score and the network resource score;
step A33: and sequencing the servers in sequence from high to low according to the server scores so as to output the server with the highest score.
5. The scheduling method of claim 1 further comprising stopping the application instance from the server using a first or second scaling method;
the first capacity reduction method comprises:
acquiring the hardware resources occupied by a plurality of running application instances and the running time of the plurality of running application instances;
generating an instance hardware occupation score according to the application instance occupied hardware resources;
sorting the application examples according to the running time to generate an example sorting result;
generating an instance time score according to the instance sorting result;
generating an instance score according to the instance time score and the instance hardware occupancy score;
stopping the application instance on the server according to the instance score;
the second capacity reduction method comprises the following steps: and stopping the application instance from the server according to a preset instance capacity reduction rule.
6. A system for scheduling server resources, configured to implement the scheduling method according to any one of claims 1 to 5, comprising:
the acquisition module is connected with the server resource pool, acquires idle resources in the server resource pool and occupied resources of the application examples, and acquires the access amount of the application examples;
the analysis module is connected with the acquisition module and judges whether capacity expansion or capacity reduction is needed or not according to the occupied resources and the access amount of the application example;
the scheduling module is connected with the analysis module and used for allocating the server to the application instance or stopping the application instance from the server according to the output result of the analysis module;
and the feedback module is connected with the acquisition module, the analysis module and the scheduling module and is used for displaying the idle resources, the application instances, the occupied resources and the scheduling result of the scheduling module.
7. The scheduling system of claim 6 wherein the acquisition module comprises:
the traffic monitoring submodule is connected with an external routing device and acquires the access quantity of the application example from the routing device;
the hardware statistics submodule is connected with the server resource pool and acquires hardware resources of the server from the server resource pool;
and the instance counting submodule is connected with the server resource pool and collects occupied resources of the application instance from the server resource pool.
8. The scheduling system of claim 6 wherein the analysis module comprises:
the rule configuration sub-module is internally preset with at least one early warning rule;
and the matching sub-module is connected with the acquisition module and the rule configuration sub-module, judges whether the access amount, the occupied resources and the idle resources meet the early warning rule or not, and generates a matching result.
9. The scheduling system of claim 6 wherein the scheduling module comprises:
the capacity expansion sub-module is connected with the server resource pool and the analysis module and distributes the application examples to the servers according to a preset capacity expansion rule;
the capacity reduction submodule is connected with the server resource pool and the analysis module and stops the application example from the server according to a preset capacity reduction rule;
the first notification submodule is connected with the capacity expansion submodule and the capacity reduction submodule and generates the scheduling result according to the output result of the capacity expansion submodule or the output result of the capacity reduction submodule.
10. The scheduling system of claim 9 wherein the feedback module comprises:
the display sub-module is connected with an external display screen, and the display screen is used for displaying the idle resources, the application examples, the occupied resources and the scheduling results of the scheduling module;
and the second notification submodule is connected with the scheduling module and external terminal equipment and is used for sending notification information to the terminal equipment according to the scheduling result of the scheduling module.
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