CN109918189B - Resource management method and related equipment - Google Patents
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- CN109918189B CN109918189B CN201711324381.9A CN201711324381A CN109918189B CN 109918189 B CN109918189 B CN 109918189B CN 201711324381 A CN201711324381 A CN 201711324381A CN 109918189 B CN109918189 B CN 109918189B
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Abstract
The embodiment of the invention discloses a resource management method and related equipment, which comprises the following steps: acquiring resource use information of each server in a plurality of servers and acquiring cost information of each server; determining effective resource investment rates of the servers according to the resource use information and the cost information; determining resource evaluation results of the plurality of servers according to the effective resource investment rate and other index data; and according to the resource evaluation result, performing resource management on the plurality of servers. By adopting the embodiment of the invention, the accuracy of resource management can be improved, and the resource management efficiency can be improved.
Description
Technical Field
The present invention relates to the field of servers, and in particular, to a resource management method and related devices.
Background
At present, whether the usage of the device resources is reasonable is measured according to the utilization rate of Central Processing Units (CPUs), memory, disks, intranet traffic and extranet traffic of all the device resources in the system. The resource monitoring system deploys resource monitoring agents (agents) on each server, the agents are used for reporting resource use conditions of the servers such as CPU, memory, disk, intranet and extranet flow and the like at regular time every minute, the resource monitoring system caches the data, carries out resource evaluation according to resource use peak values reported in a certain time window (usually defaults for 1 day), and judges whether a certain server is low-load equipment or not. In this way, the resource utilization rate of the servers in the system can be obtained by judging and labeling each server in the system. However, this method only considers the resource usage, and cannot reflect the effective utilization of the resource comprehensively and accurately, which affects the resource management.
Disclosure of Invention
The embodiment of the invention provides a resource management method and related equipment, which can improve the accuracy of resource management and improve the efficiency of resource management.
In a first aspect, an embodiment of the present invention provides a method for resource management, including:
acquiring resource use information of each server in a plurality of servers and acquiring cost information of each server;
determining effective resource investment rates of the servers according to the resource use information and the cost information;
determining resource evaluation results of the plurality of servers according to the effective resource input rate and other index data;
and managing the resources of the servers according to the resource evaluation result.
Wherein the determining the effective resource investment rates of the plurality of servers according to the resource usage information and the cost information comprises:
determining whether the load of each server reaches a threshold value according to the resource use information;
according to the cost information, counting a first resource cost sum of the server with the load reaching the threshold value and a second resource cost sum of the server with the load not reaching the threshold value;
and determining the effective resource input rate of the plurality of servers according to the first resource cost sum and the second resource cost sum.
Wherein determining the effective resource investment rates of the plurality of servers according to the first sum of resource costs and the second sum of resource costs comprises:
calculating a difference between the first and second resource cost sums;
and dividing the difference by the sum of the first resource cost to obtain the ratio of the effective resource investment rate.
Wherein the determining whether the load of each server reaches a threshold according to the resource usage information comprises:
determining a device type of each server;
determining whether the load of each server reaches a threshold according to the device type of each server.
Wherein the obtaining the cost information of each server comprises:
searching the configuration information of each server from a configuration information data table;
and searching the cost information of each server from a cost information data table according to the configuration information.
Before the searching the configuration information of each server from the configuration information data table, the method further includes:
when the storage time of the configuration information in the configuration information data table does not exceed a first threshold value, searching the configuration information of each server from the configuration information data table; or/and
and when the storage time of the cost information in the cost information data table does not exceed the second threshold, searching the cost information of each server from the cost information data table according to the configuration information.
Wherein the determining the resource evaluation results of the plurality of servers according to the effective resource investment rate and other index data comprises:
and calculating the product of the effective input rate of the resources and the other index data as the evaluation result of the resources.
Wherein the determining the resource evaluation results of the plurality of servers according to the effective resource investment rate and other index data comprises:
and calculating the weighted average value of the effective input rate of the resources and the other index data as the resource evaluation result.
Wherein the other index data comprises at least one of a safety protection success rate and a version iteration resource optimization rate.
In a second aspect, an embodiment of the present invention provides a resource management apparatus, including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring resource use information of each server in a plurality of servers and acquiring cost information of each server;
the processing module is used for determining the effective resource input rate of the servers according to the resource use information and the cost information;
the processing module is further used for determining resource evaluation results of the servers according to the effective resource investment rate and other index data;
and the management module is used for managing the resources of the servers according to the resource evaluation result.
Wherein the processing module is specifically configured to:
determining whether the load of each server reaches a threshold value according to the resource use information;
according to the cost information, counting a first resource cost sum of the server with the load reaching the threshold value and a second resource cost sum of the server with the load not reaching the threshold value;
and determining the effective resource input rate of the plurality of servers according to the first resource cost sum and the second resource cost sum.
Wherein the processing module is specifically configured to:
calculating a difference between the first and second resource cost sums;
and dividing the difference by the sum of the first resource cost to obtain the ratio of the effective resource investment rate.
The processing module is further configured to determine a device type of each server; determining whether the load of each server reaches a threshold according to the device type of each server.
The obtaining module is further configured to search the configuration information of each server from a configuration information data table; and searching the cost information of each server from a cost information data table according to the configuration information.
The processing module is further configured to determine whether the saving time of the configuration information data table exceeds a first threshold and/or whether the saving time of the cost information data table exceeds a second threshold; and when the storage time of the configuration information data table does not exceed the first threshold and/or the storage time of the cost information data table does not exceed the second threshold, executing the steps of acquiring the resource use information of each server in a plurality of servers and acquiring the cost information of each server.
The processing module is further configured to calculate a product of the effective resource investment rate and the other index data as the resource evaluation result.
The processing module is further configured to calculate a weighted average of the effective resource investment rate and the other index data as the resource assessment result.
Wherein the other index data comprises at least one of a safety protection success rate and a version iteration resource optimization rate.
In a third aspect, the present invention provides a resource management device, including: the resource management method comprises a processor, a memory and a communication bus, wherein the communication bus is used for realizing connection communication between the processor and the memory, and the processor executes a program stored in the memory for realizing the steps in the resource management method provided by the first aspect.
In one possible design, the resource management device provided by the present invention may include a module for performing the corresponding operations in the method. The modules may be software and/or hardware.
Yet another aspect of the present invention provides a computer-readable storage medium having stored thereon a plurality of instructions adapted to be loaded by a processor and to perform the method of the above-described aspects.
Yet another aspect of the present invention provides a computer program product containing instructions which, when run on a computer, cause the computer to perform the method of the above aspects.
The embodiment of the invention is implemented by firstly acquiring the resource use information of each server in a plurality of servers and acquiring the cost information of each server; then determining the effective resource input rate of a plurality of servers according to the resource use information and the cost information; determining resource evaluation results of the plurality of servers according to the effective resource investment rate and other index data; and finally, according to the resource evaluation result, performing resource management on the plurality of servers. The resource evaluation result is determined by referring to a plurality of factors, thereby improving the accuracy of resource management and improving the efficiency of resource management.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments or the background art of the present invention, the drawings required to be used in the embodiments or the background art of the present invention will be described below.
Fig. 1 is a schematic structural diagram of a resource management system according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a resource monitoring system according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating a resource management method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a resource assessment result provided by an embodiment of the present invention;
FIG. 5 is a flowchart illustrating a resource management method according to another embodiment of the present invention;
FIG. 6 is a schematic diagram of a server layout according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a resource management apparatus according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a resource management device according to 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 some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a resource management system according to an embodiment of the present invention, where the resource management system includes a resource monitoring system and a plurality of servers. The server may be a service server, the resource monitoring system may be deployed on a background server, and the background server may include a multi-core CPU (e.g., a 4-core CPU) and a memory (e.g., 16G). The resource monitoring system realizes the monitoring of each server by respectively deploying agents in a plurality of servers, and acquires resource use information from each server. As shown in fig. 2, the resource monitoring system includes a monitoring platform, a Configuration Management Database (CMDB), and a comprehensive budget Management system (OBS). The monitoring platform is used for acquiring resource use information from a plurality of servers, the CMDB is mainly used for storing configuration information of each server, and the OBS is mainly used for storing cost information of each server. The resource management system also comprises a server hardware pulling module, a cost and configuration information pulling module, a Cache layer, a Mysql database, a resource reasonable score calculating module, an operation cost calculating module, a front-end page and the like. Based on the resource management system, the embodiment of the invention provides the following solution.
Referring to fig. 3, fig. 3 is a schematic flowchart of a resource management method according to an embodiment of the present invention, where the method includes, but is not limited to, the following steps:
s301, acquiring resource use information of each server in a plurality of servers and acquiring cost information of each server.
On one hand, a network management agent can be deployed in each server, and each server reports resource use information and the identifier (such as IP) of the server to a monitoring platform in the resource monitoring system through the network management agent according to a preset time interval. The resource utilization information includes hardware utilization information such as a CPU, an internal memory, a network card, a disk and the like, and service characteristic information. The server hardware pull module may deploy two processes, including:
the first process calls an Application Program Interface (API) of the monitoring platform to acquire resource usage information reported by each server from the monitoring platform according to a preset time interval, and caches all the resource usage information reported within a recent period of time (for example, 7 days) in the shared memory. Wherein the predetermined time interval includes, but is not limited to, 1 minute. And then, caching the resource use information by using a structure body with a preset byte length, wherein the preset byte length comprises but is not limited to 12 bytes, and the structure body for caching the information is as follows:
typedef struct Resource{
int Ip_num；
char CPU_utilize；
char Mem_utilize；
char Block_utilize；
char eth0_utilize；
char eth1_utilize；
}Resource；
the second process may calculate the resource usage information reported in the last period of time. For example, information such as a peak value, an average value, and the like may be calculated from the resource usage information. The number of times of reporting the resource use information by the server is large, so that accidental data distortion is avoided, after the resource use information in a period of time is obtained, when the peak value of each hardware resource item is calculated, the first 5 data values with the highest peak value in the period of time can be removed, and then the data value with the highest peak value at the 6 th position is selected. In calculating the use average of each hardware resource item, the top 5 data values and the bottom 5 data values may be removed first, and then the weighted average of the remaining other data values may be calculated as the average of each hardware resource item. Meanwhile, in order to avoid memory data loss caused by machine downtime fault, the server hardware pulling module may store information such as peak values, average values and the like in the Mysql database according to preset time (e.g., 5 minutes).
On the other hand, acquiring the cost information of each server includes the following two optional ways:
in a first off-line calculation mode, the configuration information of each server can be searched from a configuration information data table; and searching the cost information of each server from a cost information data table according to the configuration information. The method specifically comprises the following steps:
the CDMB employs three levels of business modules to define server attributes. The first-level service module is used for classifying project affiliation, the second-level service module is used for classifying system affiliation, and the third-level service module is used for classifying each functional sub-module of the system. Before the server is shelved, configuration information of the server can be recorded into the CDMB, and the configuration information at least comprises: purchasing time to purchase (purchase YM), purchasing City (idc City), fixed Asset number (Svr Asset Id), intranet IP (server Lan IP), extranet IP (server Wan IP), company standard server model (device Type), server Version number (server Version) and the like. The cost and configuration information pulling module can acquire configuration information from the CDMB according to a preset time interval, and add the configuration information into a configuration information data table in the Mysql database for local storage, wherein the preset time interval includes but is not limited to 1 day, and the configuration information data table includes at least one of purchase shelf life, purchase city, fixed number, intranet IP, extranet IP, company standard server model and server version number.
Optionally, since the number of configuration information records is above the million level, in order to avoid a decrease in table lookup efficiency caused by a gradual increase in the amount of data in the configuration information data table, it may be determined whether the storage time of the configuration information in the configuration information data table exceeds the first threshold, when the storage time of the configuration information in the configuration information data table exceeds the first threshold, the configuration information whose storage time exceeds the first threshold may be deleted from the configuration information data table, and when the storage time of the configuration information in the configuration information data table does not exceed the first threshold, the configuration information of each server is looked up from the configuration information data table. Wherein the first threshold may include, but is not limited to, 3 months.
The OBS is used for storing a plurality of items of information such as server procurement yearly month (purchase YM), procurement City (idc City), company standard server Type (device Type), server Version number (server Version), current accounting yearly month (Cost YM) and the like, and the plurality of items of information respectively correspond to the unit price of the unique equipment. The information stored in the OBS can be updated according to the preset interval time, and the cost and configuration information pulling module can also acquire cost information from the OBS according to the preset interval time and add the cost information to a cost information data table in the Mysql database for local storage. The preset time interval includes but is not limited to 1 month, and the cost information data table includes a plurality of configuration information items such as a server procurement month of year, a procurement city, a company standard server type server version number, a current accounting month of year and the like, and corresponding relations between the plurality of configuration information items and the cost information items.
Optionally, since the number of the cost information records is above a million level, in order to avoid reduction of table lookup efficiency due to gradual increase of data amount in the cost information data table, it may be determined whether the storage time of the cost information in the cost information data table exceeds a second threshold, when the storage time of the cost information in the cost information data table exceeds the second threshold, the cost information whose storage time exceeds the second threshold may be deleted, and when the storage time of the cost information in the cost information data table does not exceed the second threshold, the cost information of each server is looked up from the cost information data table. Wherein the second threshold may include, but is not limited to, 3 months.
And finally, after the cost information data table and the configuration information data table are obtained, the cost information of each server can be obtained according to a preset time interval through a double-table joint check traversal matching mode. The method comprises the following steps: the method comprises the steps of firstly obtaining configuration information such as purchase shelf time, purchase city, standard server model number, server version number and the like of each server from a configuration information data table, and then obtaining cost information of each server from a cost information data table according to the configuration information. Meanwhile, the obtained cost information is inserted into a cost calculation intermediate table (t _ Device _ Account) for temporary storage, and the information field of the cost calculation intermediate table comprises: the system comprises a first-level service module, a second-level service module, a third-level service module, at least one of the year, month and day of accounting, the time of getting on shelf, the type of a purchased urban standard server, the version number of the server, the unit price of the server and the insertion updating time.
In a second online computing approach, a user may submit an IP list on a front-end page, where the IP list includes the identities of all servers that the user needs to query. After the IP list is submitted to a resource monitoring system, the IP list is spliced into json character string parameters, configuration information of each server in the IP list is obtained from the CDMB in a post pulling mode and cached in a shared memory, then matching query is carried out on a cost information data table according to the configuration information, and the queried cost information and the configuration information of each server in the IP list are combined, spliced and inserted into a cost calculation real-time table. The information field of the cost calculation real-time table is additionally and newly added with a service Identification (ID) and a user name field on the basis of the existing field of the cost calculation intermediate table so as to distinguish the query records submitted by a user for multiple times in different time periods.
S302, determining the effective resource investment rates of the servers according to the resource use information and the cost information.
In a specific implementation, whether the load of each server reaches a threshold value or not can be determined according to the resource usage information; according to the cost information, counting a first resource cost sum of the server with the load reaching the threshold value and a second resource cost sum of the server with the load not reaching the threshold value; and determining the effective resource input rate of the plurality of servers according to the first resource cost sum and the second resource cost sum.
S303, determining resource evaluation results of the servers according to the effective input rate of the resources and other index data.
In a specific implementation, a product of the effective resource investment rate and the other index data may be calculated as the resource evaluation result. The other index data comprises at least one of a safety protection success rate and a version iteration resource optimization rate. Resource assessment result Score = resource effective investment ratio safety protection success ratio version iteration resource optimization rate 100 (min).
It should be noted that, in the embodiment of the present invention, the effective resource investment rate is the most main reference factor that affects the resource evaluation result, and the success rate of security protection and the optimization rate of version iteration resources are relatively stable and close to 100%, and therefore, are not used as main reference factors when calculating the resource evaluation result. Wherein:
safety protection success rate = (1-failure rate of insufficient protection capacity) × (success rate of reverse verification and attack of 1-blue army). The failure rate of insufficient protection capacity is the number of times of the flow of the threat attack exceeding the current flow capable of being protected by the system/the total number of times of the system invoking protection, and the main reason is that the attack threat bypasses due to the insufficient protection capacity. The success rate of the reverse verification attack of the blue army = the number of rules of the successful attack breakthrough protection of the blue army/the total number of attack rules of the blue army 100%, and the main reason is that the attack threat bypasses due to the existence of defects of the programs of the protection or the attack threat bypasses due to the incomplete protection strategy rules.
Under the condition of the same attack threat flow or packet quantity test, the version iteration resource optimization rate is the ratio of the utilization rate of the CPU (Central processing Unit) of the hardware resource of the machine which is developed and consumed by the previous version program to the utilization rate of the CPU of the hardware resource of the machine which is consumed by the current version program. For example: under the 100G attack traffic threat, the utilization rate of the CPU of the protection cluster of the previous version is 80%, the current version program is optimized through algorithm adjustment, strategy simplification and the like, under the 100G attack traffic threat, the utilization rate of the CPU of the protection cluster is 60%, and the version iteration resource optimization rate is as follows: 80%/60% =1.33.
The method for obtaining the success rate of the safety protection and the optimization rate of the version iteration resources comprises the following steps: in the first offline mode, the agent deployed on each server may report the resource usage information to the server, and also support the service to report the characteristic data in a customized manner, for example, through an API interface of the monitoring platform, data such as a security protection success rate and a version iteration resource optimization rate are submitted to the resource monitoring system according to a preset period, and are cached in the shared memory. In the second online mode, the user can submit the success rate of safety protection and the optimization rate of version iteration resources to the resource monitoring system on the front-end page.
Optionally, a weighted average of the effective resource investment rate and the other index data may be calculated as the resource assessment result. The reference factors for determining the resource evaluation result can be added or deleted according to the actual security threat condition of the system, or different weight assignments can be carried out, and then the weighted average value of each reference factor is calculated as the resource scoring result.
S304, according to the resource assessment result, performing resource management on the plurality of servers.
In specific implementation, the resource evaluation results can be sequenced, a basis is provided for resource optimization of the server, and the situation that the utilization rate of the current safety equipment is too low is reduced. Meanwhile, the effective value output of the server resources can be reflected according to the resource evaluation result, so that a quantitative basis and a resource purchasing decision reference are provided for the expansion and contraction capacity of each safety system and the resource approving investment.
For example, as shown in fig. 4, fig. 4 is a schematic diagram of a resource assessment result provided by an embodiment of the present invention. Resource use information can be obtained from a server in each system (such as a DDOS protection system, an intrusion detection system, a vulnerability scanning system or a file system), then the effective resource input rate of each system is calculated according to the cost information of the server, and finally the resource evaluation result of each system is calculated according to a preset period by combining the safety protection success rate and the version iteration resource optimization rate. As can be seen from the figure, the resource assessment results of the same system at different time points may be different, and the resource assessment results of different systems at the same time point may also be different. And optimizing each system by comparing the resource evaluation results of the same system at different time points or comparing the resource evaluation results of different systems at the same time point.
In the embodiment of the invention, firstly, the resource use information of each server in a plurality of servers is obtained, and the cost information of each server is obtained; then determining the effective resource input rate of a plurality of servers according to the resource use information and the cost information; determining resource evaluation results of a plurality of servers according to the effective input rate of resources and other index data; and finally, according to the resource evaluation result, performing resource management on the plurality of servers. The resource evaluation result is determined by referring to a plurality of factors, thereby improving the accuracy of resource management and improving the efficiency of resource management.
Referring to fig. 5, fig. 5 is a schematic flowchart of a resource management method according to another embodiment of the present invention, the method includes, but is not limited to, the following steps:
s501, acquiring resource use information of each server in a plurality of servers and acquiring cost information of each server. This step is the same as the previous embodiment, and the embodiment of the present invention is not described again.
S502, determining whether the load of each server reaches a threshold value according to the resource use information.
In a specific implementation, after each server reports resource usage information, the resource monitoring information may determine whether the load of each server reaches a threshold according to a usage peak of a CPU, a memory, a disk, an intranet flow, or an extranet flow within a time window (e.g., 1 day). When the load of a certain server does not reach the threshold value, the server is determined to be a low-load device, and the load does not reach the standard. When the load of a certain server reaches a threshold value, the server is determined to be a load-qualified device.
Further, a device type of each of the servers may be determined; determining whether the load of each server reaches a threshold value according to the device type of each server. Specifically, the device type to which the server belongs may be determined according to a "company standard server model" field in the configuration information, where the device type includes an access server, a logic server, a Cache server, a storage server, a DB server, and an offline computing server. The server of each device type sets a different load determination criterion.
For example, when the CPU utilization rate is less than 20%, the memory usage ratio is less than 60%, the intranet traffic ratio is less than 16%, and the extranet traffic ratio is less than 12%, it is determined that the server load of the access class does not meet the standard. And if the CPU utilization rate is less than 25% and the intranet flow rate is less than 16%, determining that the logic server load does not reach the standard. And if the CPU utilization rate is less than 20%, the memory usage ratio is less than 60% and the intranet flow ratio is less than 16%, determining that the Cache server load does not reach the standard. The CPU utilization rate is less than 20%, the intranet flow ratio is less than 16%, the disk storage capacity ratio is less than 40%, and the disk BIO ratio is less than 40%, so that the server load of the storage class does not reach the standard. The CPU utilization rate is less than 20%, the disk storage capacity ratio is less than 40%, the disk BIO ratio is less than 40%, the server load of the DB class does not reach the standard, the CPU utilization rate is less than 20%, the disk storage capacity ratio is less than 40%, the disk BIO ratio is less than 40%, and the server load of the off-line calculation class does not reach the standard.
As shown in fig. 6, fig. 6 is a schematic structural diagram of a server layout according to an embodiment of the present invention. The equipment quantity of the access class server is 655, and 39.8% of the server load does not reach the standard. The amount of equipment 3416 for the logical class of servers, 24.8% of the server load, does not meet the standard. The equipment amount of the Cache server is 69, and 46% of server load does not reach the standard. The equipment amount of the storage class server is 436, and 37.8% of the server load does not reach the standard. The equipment amount of the server of the DB class is 365, and the load of 27.7 percent of the server does not reach the standard. The equipment amount of the server of the off-line computing class is 246,0.4 percent, and the server load does not reach the standard.
S503, according to the cost information, counting a first resource cost sum of the server with the load reaching the threshold value and a second resource cost sum of the server with the load not reaching the threshold value.
Specifically, after judging whether the load of each server reaches a threshold value, labeling each server, dividing the servers with the loads reaching the threshold value into a first class, and dividing the servers with the loads not reaching the threshold value into a second class. And respectively calculating the sum of the cost information of all the servers in the first class as a first resource cost sum and the sum of the cost information of all the servers in the second class as a second resource cost sum.
S504, determining the effective resource input rate of the plurality of servers according to the first resource cost sum and the second resource cost sum.
Specifically, a difference between the first sum of resource costs and the second sum of resource costs may be calculated; and dividing the difference by the sum of the first resource cost to obtain the ratio of the effective resource investment rate. The calculation formula is as follows: the resource effective input rate = (the sum of the first resource cost and the sum of the second resource cost)/the sum of the first resource cost.
And S505, determining resource evaluation results of the plurality of servers according to the effective input rate of the resources and other index data. This step is the same as the previous embodiment, and the embodiment of the present invention is not described again.
S506, according to the resource assessment result, resource management is carried out on the servers. This step is the same as the previous embodiment, and the embodiment of the present invention is not described again.
The method of embodiments of the present invention is set forth above in detail and the apparatus of embodiments of the present invention is provided below.
Referring to fig. 7, fig. 7 is a schematic structural diagram of a resource management device according to an embodiment of the present invention, where the resource management device may include:
an obtaining module 701, configured to obtain resource usage information of each server in a plurality of servers, and obtain cost information of each server.
On one hand, a network management agent can be deployed in each server, and each server reports resource use information and the identifier (such as IP) of the server to a monitoring platform in the resource monitoring system through the network management agent according to a preset time interval. The resource utilization information includes hardware utilization information such as a CPU, an internal memory, a network card, a disk and the like, and service characteristic information. The server hardware pull module may deploy two processes, including:
the first process calls an Application Program Interface (API) of the monitoring platform to obtain resource usage information reported by each server from the monitoring platform according to a preset time interval, and caches all the resource usage information reported within a recent period of time (e.g., 7 days) in the shared memory. Wherein the predetermined time interval includes, but is not limited to, 1 minute. And then, caching the resource use information by using a structure body with a preset byte length, wherein the preset byte length comprises but is not limited to 12 bytes, and the structure body for caching the information is as follows:
the second process may calculate the resource usage information reported in the last period of time. For example, information such as a peak value, an average value, and the like may be calculated from the resource usage information. The number of times of reporting the resource use information by the server is large, so that accidental data distortion is avoided, after the resource use information in a period of time is obtained, when the peak value of each hardware resource item is calculated, the first 5 data values with the highest peak value in the period of time can be removed, and then the data value with the highest peak value at the 6 th position is selected. In calculating the use average of each hardware resource item, the top 5 data values and the bottom 5 data values may be removed first, and then the weighted average of the remaining other data values may be calculated as the average of each hardware resource item. Meanwhile, in order to avoid memory data loss caused by machine downtime fault, the server hardware pulling module may store information such as peak values, average values and the like in the Mysql database according to preset time (e.g., 5 minutes).
On the other hand, acquiring the cost information of each server includes the following two optional ways:
in a first off-line calculation mode, the configuration information of each server can be searched from a configuration information data table; and searching the cost information of each server from a cost information data table according to the configuration information. The method specifically comprises the following steps:
the CDMB employs three levels of business modules to define server attributes. The first-level service module is used for classifying project affiliation, the second-level service module is used for classifying system affiliation, and the third-level service module is used for classifying each functional sub-module of the system. Before the server is shelved, configuration information of the server can be recorded into the CDMB, and the configuration information at least comprises: purchasing time to purchase (purchase YM), purchasing City (idc City), fixed Asset number (Svr Asset Id), intranet IP (server Lan IP), extranet IP (server Wan IP), company standard server model (device Type), server Version number (server Version) and the like. The cost and configuration information pulling module can acquire configuration information from the CDMB according to a preset time interval, and add the configuration information into a configuration information data table in the Mysql database for local storage, wherein the preset time interval includes but is not limited to 1 day, and the configuration information data table includes at least one of purchase shelf time, purchase city, fixed asset number, intranet IP, extranet IP, company standard server model and server version number.
Optionally, since the number of configuration information records is above the million level, in order to avoid a decrease in table lookup efficiency caused by a gradual increase in the amount of data in the configuration information data table, it may be determined whether the storage time of the configuration information in the configuration information data table exceeds the first threshold, when the storage time of the configuration information in the configuration information data table exceeds the first threshold, the configuration information whose storage time exceeds the first threshold may be deleted from the configuration information data table, and when the storage time of the configuration information in the configuration information data table does not exceed the first threshold, the configuration information of each server is looked up from the configuration information data table. Wherein the first threshold may include, but is not limited to, 3 months.
The OBS is used for storing a plurality of items of information such as server procurement yearly month (purchase YM), procurement City (idc City), company standard server Type (device Type), server Version number (server Version), current accounting yearly month (Cost YM) and the like, and the plurality of items of information respectively correspond to the unit price of the unique equipment. The information stored in the OBS can be updated according to the preset interval time, and the cost and configuration information pulling module can also obtain the cost information from the OBS according to the preset interval time and add the cost information to the cost information data table in the Mysql database for local storage. The preset time interval includes but is not limited to 1 month, and the cost information data table includes a plurality of configuration information such as a server procurement year month, a procurement city, a company standard server type server version number, a current accounting year month and the like, and corresponding relations between the plurality of configuration information and the cost information.
Optionally, since the number of the cost information records is over a million level, in order to avoid a decrease in table lookup efficiency due to a gradual increase in data amount in the cost information data table, it may be determined whether the storage time of the cost information in the cost information data table exceeds a second threshold, when the storage time of the cost information in the cost information data table exceeds the second threshold, the cost information whose storage time exceeds the second threshold may be deleted, and when the storage time of the cost information in the cost information data table does not exceed the second threshold, the cost information of each server is looked up from the cost information data table. Wherein the second threshold may include, but is not limited to, 3 months.
And finally, after the cost information data table and the configuration information data table are obtained, the cost information of each server can be obtained according to a preset time interval through a double-table joint check traversal matching mode. The method comprises the following steps: the method comprises the steps of firstly obtaining configuration information such as purchase shelf time, purchase city, standard server model number, server version number and the like of each server from a configuration information data table, and then obtaining cost information of each server from a cost information data table according to the configuration information. Meanwhile, the obtained cost information is inserted into a cost calculation intermediate table (t _ Device _ Account) for temporary storage, and the information field of the cost calculation intermediate table comprises: the system comprises a first-level service module, a second-level service module, a third-level service module, at least one of the year, month and day of accounting, the time of getting on shelf, the type of a purchased urban standard server, the version number of the server, the unit price of the server and the insertion updating time.
In a second online computing approach, a user may submit an IP list on a front-end page, where the IP list includes the identities of all servers that the user needs to query. After the IP list is submitted to a resource monitoring system, the IP list is spliced into json character string parameters, configuration information of each server in the IP list is obtained from the CDMB in a post pulling mode and cached in a shared memory, then a cost information data table is subjected to matching query according to the configuration information, and the queried cost information and the configuration information of each server in the IP list are combined, spliced and inserted into a cost calculation real-time table. The information field of the cost calculation real-time table is additionally and newly added with a service Identification (ID) field and a user name field on the basis of the existing field of the cost calculation intermediate table so as to distinguish query records submitted by a user for multiple times in different time periods.
A processing module 702, configured to determine effective resource investment rates of the servers according to the resource usage information and the cost information.
First, it may be determined whether the load of each server reaches a threshold value according to the resource usage information. After each server reports the resource usage information, the resource monitoring information may determine whether the load of each server reaches a threshold according to a usage peak of the CPU, the memory, the disk, the intranet or extranet traffic within a time window (e.g., 1 day). When the load of a certain server does not reach the threshold value, the server is determined to be a low-load device, and the load does not reach the standard. When the load of a certain server reaches a threshold value, the server is determined to be a load-qualified device.
Further, a device type of each of the servers may be determined; determining whether the load of each server reaches a threshold according to the device type of each server. Specifically, the device type to which the server belongs may be determined according to a "company standard server model" field in the configuration information, where the device type includes an access server, a logic server, a Cache server, a storage server, a DB server, and an offline computing server. The server of each device type sets a different load determination criterion.
For example, when the CPU utilization rate is less than 20%, the memory usage ratio is less than 60%, the intranet traffic ratio is less than 16%, and the extranet traffic ratio is less than 12%, it is determined that the server load of the access class does not meet the standard. And if the CPU utilization rate is less than 25% and the intranet flow rate is less than 16%, determining that the logic server load does not reach the standard. And if the CPU utilization rate is less than 20%, the memory usage ratio is less than 60% and the intranet flow ratio is less than 16%, determining that the Cache server load does not reach the standard. The CPU utilization rate is less than 20%, the intranet flow rate is less than 16%, the disk storage capacity rate is less than 40%, and the disk BIO rate is less than 40%, so that the server load of the storage class does not reach the standard. The CPU utilization rate is less than 20%, the disk storage capacity ratio is less than 40%, the disk BIO ratio is less than 40%, the server load of the DB class does not reach the standard, the CPU utilization rate is less than 20%, the disk storage capacity ratio is less than 40%, the disk BIO ratio is less than 40%, and the server load of the off-line calculation class does not reach the standard.
As shown in fig. 4, fig. 4 is a schematic structural diagram of a server layout according to an embodiment of the present invention. The equipment quantity of the access class server is 655, and 39.8% of the server load does not reach the standard. The amount of equipment 3416 for the logical class of servers, 24.8% of the server load, does not meet the standard. The equipment amount of the Cache server is 69, and 46% of server load does not reach the standard. The equipment amount of the storage class server is 436, and 37.8% of the server load does not reach the standard. The equipment amount of the server of the DB class is 365, and the load of 27.7 percent of the server does not reach the standard. The equipment amount of the server of the off-line computing class is 246,0.4 percent, and the server load does not reach the standard.
Then, according to the cost information, a first resource cost sum of the server with the load reaching the threshold value and a second resource cost sum of the server with the load not reaching the threshold value are counted. Specifically, after judging whether the load of each server reaches a threshold value, labeling each server, dividing the servers with the loads reaching the threshold value into a first class, and dividing the servers with the loads not reaching the threshold value into a second class. And respectively calculating the sum of the cost information of all the servers in the first class as a first resource cost sum and the sum of the cost information of all the servers in the second class as a second resource cost sum.
And finally, determining the effective resource investment rates of the plurality of servers according to the first resource cost sum and the second resource cost sum. Specifically, a difference between the first sum of resource costs and the second sum of resource costs may be calculated; and dividing the difference by the sum of the first resource cost to obtain the ratio of the effective resource investment rate. The calculation formula is as follows: resource effective input rate = (sum of first resource cost-sum of second resource cost)/sum of first resource cost.
The processing module 702 is further configured to determine resource evaluation results of the servers according to the effective resource investment rates and other index data.
In a specific implementation, a product of the effective resource investment rate and the other index data may be calculated as the resource evaluation result. The other index data comprises at least one of a safety protection success rate and a version iteration resource optimization rate. Resource assessment result Score = resource effective investment ratio safety protection success ratio version iteration resource optimization rate 100 (min).
It should be noted that in the embodiment of the present invention, the effective resource investment rate is the most important reference factor that affects the resource evaluation result, and the success rate of security protection and the optimization rate of version iteration resources are relatively stable, close to 100%, and therefore, are not used as the main reference factor when calculating the resource evaluation result. Wherein:
safety protection success rate = (1-failure rate of insufficient protection capacity) × (success rate of reverse verification and attack of 1-blue army). The failure rate of insufficient protection capacity is the number of times of the flow of the threat attack exceeding the current flow capable of being protected by the system/the total number of times of the system invoking protection, and the main reason is that the attack threat bypasses due to the insufficient protection capacity. The success rate of the reverse verification attack of the blue army = the number of rules of the successful attack breakthrough protection of the blue army/the total number of attack rules of the blue army 100%, and the main reason is that the attack threat bypasses due to the existence of defects of the programs of the protection or the attack threat bypasses due to the incomplete protection strategy rules.
Under the condition of the same attack threat flow or packet quantity test, the version iteration resource optimization rate is the ratio of the utilization rate of the hardware resource CPU of the machine which is developed and consumed by the previous version program to the utilization rate of the hardware resource CPU of the machine which is consumed by the current version program. For example: under the 100G attack traffic threat, the utilization rate of the CPU of the protection cluster of the previous version is 80%, the current version program is optimized through algorithm adjustment, strategy simplification and the like, under the 100G attack traffic threat, the utilization rate of the CPU of the protection cluster is 60%, and the version iteration resource optimization rate is as follows: 80%/60% =1.33.
The method for obtaining the safety protection success rate and the version iteration resource optimization rate comprises the following steps: in the first offline mode, the agent deployed on each server may report the resource usage information to the server, and also support the service to report the characteristic data in a customized manner, for example, through an API interface of the monitoring platform, data such as a security protection success rate and a version iteration resource optimization rate are submitted to the resource monitoring system according to a preset period, and are cached in the shared memory. In the second online mode, the user can submit the success rate of safety protection and the optimization rate of version iteration resources to the resource monitoring system on the front-end page.
Optionally, a weighted average of the effective resource investment rate and the other index data may be calculated as the resource assessment result. The reference factors for determining the resource evaluation result can be added or deleted according to the actual security threat condition of the system, or different weight assignments can be carried out, and then the weighted average value of each reference factor is calculated as the resource scoring result.
A management module 703, configured to perform resource management on the multiple servers according to the resource evaluation result.
In specific implementation, the resource evaluation results can be sequenced, a basis is provided for resource optimization of the server, and the situation that the utilization rate of the current safety equipment is too low is reduced. Meanwhile, the effective value output of the server resources can be reflected according to the resource evaluation result, so that a quantitative basis and a resource purchasing decision reference are provided for the expansion and contraction capacity of each safety system and the resource approving investment.
For example, as shown in fig. 4, fig. 4 is a schematic diagram of a resource assessment result according to an embodiment of the present invention. Resource use information can be obtained from a server in each system (such as a DDOS protection system, an intrusion detection system, a vulnerability scanning system or a file system), then the effective resource input rate of each system is calculated according to the cost information of the server, and finally the resource evaluation result of each system is calculated according to a preset period by combining the safety protection success rate and the version iteration resource optimization rate. As can be seen from the figure, the resource assessment results of the same system at different time points may be different, and the resource assessment results of different systems at the same time point may also be different. And optimizing each system by comparing the resource evaluation results of the same system at different time points or comparing the resource evaluation results of different systems at the same time point.
In the embodiment of the invention, firstly, the resource use information of each server in a plurality of servers is obtained, and the cost information of each server is obtained; then determining the effective resource input rate of a plurality of servers according to the resource use information and the cost information; determining resource evaluation results of a plurality of servers according to the effective input rate of resources and other index data; and finally, according to the resource evaluation result, performing resource management on the plurality of servers. The resource evaluation result is determined by referring to a plurality of factors, thereby improving the accuracy of resource management and improving the efficiency of resource management.
Referring to fig. 8, fig. 8 is a schematic structural diagram of a resource management device according to an embodiment of the present invention. As shown, the resource management device may include: at least one processor 801, at least one communication interface 802, at least one memory 803, and at least one communication bus 804.
The processor 801 may be, among other things, a central processing unit, a general purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, transistor logic, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor may also be a combination of computing functions, e.g., comprising one or more microprocessors in combination, a digital signal processor in combination with a microprocessor, and so forth. The communication bus 804 may be a peripheral component interconnect standard PCI bus or an extended industry standard architecture EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 8, but that does not indicate only one bus or one type of bus. A communication bus 804 is used to enable communications among the components. The communication interface 802 of the device in the embodiment of the present invention is used for performing signaling or data communication with other node devices. The Memory 803 may include a volatile Memory, such as a Nonvolatile dynamic Random Access Memory (NVRAM), a Phase Change Random Access Memory (PRAM), a Magnetoresistive Random Access Memory (MRAM), and the like, and may further include a Nonvolatile Memory, such as at least one magnetic Disk Memory device, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a flash Memory device, such as a NOR flash Memory (NOR flash Memory) or a NAND flash Memory (EEPROM), a semiconductor device, such as a Solid State Disk (SSD), and the like. The memory 803 may optionally be at least one memory device located remotely from the processor 801 as previously described. A set of program codes is stored in the memory 803 and the processor 801 executes the programs in the memory 803.
Acquiring resource use information of each server in a plurality of servers and acquiring cost information of each server;
determining effective resource investment rates of the servers according to the resource use information and the cost information;
determining resource evaluation results of the plurality of servers according to the effective resource investment rate and other index data;
and managing the resources of the servers according to the resource evaluation result.
Optionally, the processor 801 is further configured to perform the following operation steps:
determining whether the load of each server reaches a threshold value according to the resource use information;
according to the cost information, counting a first resource cost sum of the server with the load reaching the threshold value and a second resource cost sum of the server with the load not reaching the threshold value;
and determining the effective resource input rate of the plurality of servers according to the first resource cost sum and the second resource cost sum.
Optionally, the processor 801 is further configured to perform the following operation steps:
calculating a difference between the first and second resource cost sums;
and dividing the difference by the sum of the first resource cost to obtain the ratio of the effective resource investment rate.
Optionally, the processor 801 is further configured to perform the following operation steps:
determining a device type of each server;
determining whether the load of each server reaches a threshold according to the device type of each server.
Optionally, the processor 801 is further configured to perform the following operation steps:
searching the configuration information of each server from a configuration information data table;
and searching the cost information of each server from a cost information data table according to the configuration information.
Optionally, the processor 801 is further configured to perform the following operation steps:
when the storage time of the configuration information in the configuration information data table does not exceed a first threshold value, searching the configuration information of each server from the configuration information data table; or/and
and when the storage time of the cost information in the cost information data table does not exceed the second threshold, searching the cost information of each server from the cost information data table according to the configuration information.
Optionally, the processor 801 is further configured to perform the following operation steps:
and calculating the product of the effective input rate of the resources and the other index data as the evaluation result of the resources.
Optionally, the processor 801 is further configured to perform the following operation steps:
and calculating the weighted average value of the effective input rate of the resources and the other index data as the resource evaluation result.
Wherein the other index data comprises at least one of a safety protection success rate and a version iteration resource optimization rate.
Further, the processor may cooperate with the memory and the communication interface to perform the operations of the resource management apparatus in the above embodiments of the invention.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
The above-mentioned embodiments further explain the objects, technical solutions and advantages of the present invention in detail. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (11)
1. A method for resource management, the method comprising:
acquiring resource use information of each server in a plurality of servers and acquiring cost information of each server;
determining whether the load of each server reaches a threshold value according to the resource use information;
according to the cost information, counting a first resource cost sum of the server with the load reaching the threshold value and a second resource cost sum of the server with the load not reaching the threshold value;
calculating a difference between the first and second resource cost sums;
dividing the difference value by the sum of the first resource cost to obtain a ratio as the effective resource input rate of the plurality of servers;
determining resource evaluation results of the plurality of servers according to the effective resource investment rate and other index data;
and according to the resource evaluation result, performing resource management on the plurality of servers.
2. The method of claim 1, wherein said determining whether the load of said each server reaches a threshold based on said resource usage information comprises:
determining a device type of each server;
determining whether the load of each server reaches a threshold value according to the device type of each server.
3. The method of claim 1, wherein said obtaining cost information for said each server comprises:
searching the configuration information of each server from a configuration information data table;
and searching the cost information of each server from a cost information data table according to the configuration information.
4. The method of claim 3, further comprising:
when the storage time of the configuration information in the configuration information data table does not exceed a first threshold value, searching the configuration information of each server from the configuration information data table; or/and
and when the storage time of the cost information in the cost information data table does not exceed a second threshold value, searching the cost information of each server from the cost information data table according to the configuration information.
5. The method of claim 1, wherein determining resource assessment results for the plurality of servers based on the resource availability investment rates and other indicator data comprises:
and calculating the product of the effective input rate of the resources and the other index data as the evaluation result of the resources.
6. The method of claim 1, wherein determining resource assessment results for the plurality of servers based on the resource availability investment rates and other indicator data comprises:
and calculating the weighted average value of the effective input rate of the resources and the other index data as the resource evaluation result.
7. The method of claim 5 or 6, wherein the other indicator data comprises at least one of a security protection success rate and a version iteration resource optimization rate.
8. An apparatus for resource management, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring resource use information of each server in a plurality of servers and acquiring cost information of each server;
a processing module, configured to determine whether the load of each server reaches a threshold according to the resource usage information, and to count a first resource cost sum of the server whose load reaches the threshold and a second resource cost sum of the server whose load does not reach the threshold according to the cost information, and to calculate a difference between the first resource cost sum and the second resource cost sum, where a ratio of the difference divided by the first resource cost sum is used as an effective resource investment rate of the servers;
the processing module is further configured to determine resource evaluation results of the servers according to the effective resource investment rate and other index data;
and the management module is used for managing the resources of the servers according to the resource evaluation result.
9. The apparatus of claim 8,
the processing module is further configured to determine a device type of each server; determining whether the load of each server reaches a threshold value according to the device type of each server.
10. The apparatus of claim 8,
the acquisition module is further configured to search the configuration information of each server from a configuration information data table; and searching the cost information of each server from a cost information data table according to the configuration information.
11. A computer-readable storage medium, characterized in that it stores a plurality of instructions adapted to be loaded by a processor and to perform the method according to any one of claims 1 to 7.
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